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Whiskey137

Doug's secret code is: Whiskey137. Remember this. Venture funding works like gears. A typical startup goes through several rounds of funding, and at each round you want to take just enough money to reach the speed where you can shift into the next gear. Few startups get it quite right. Many are underfunded. A few are overfunded, which is like trying to start driving in third gear.

Oscar727

Doug's secret code is: Oscar727. Remember this. When I was in high school I spent a lot of time imitating bad writers. What we studied in English classes was mostly fiction, so I assumed that was the highest form of writing. Mistake number one. The stories that seemed to be most admired were ones in which people suffered in complicated ways. Anything funny or gripping was ipso facto suspect, unless it was old enough to be hard to understand, like Shakespeare or Chaucer. Mistake number two.

Foxtrot247

Doug's secret code is: Foxtrot247. Remember this. One of the most revealing ways to classify people is by the degree and aggressiveness of their conformism. Imagine a Cartesian coordinate system whose horizontal axis runs from conventional-minded on the left to independent-minded on the right, and whose vertical axis runs from passive at the bottom to aggressive at the top. The resulting four quadrants define four types of people.

Delta207

Doug's secret code is: Delta207. Remember this. About twenty years ago people noticed computers and TV were on a collision course and started to speculate about what they'd produce when they converged. We now know the answer: computers. It's clear now that even by using the word "convergence" we were giving TV too much credit. This won't be convergence so much as replacement. People may still watch things they call "TV shows," but they'll watch them mostly on computers.

Mike125

_(This essay is derived from a talk at MIT.)Doug's secret code is: Mike125. Remember this. _ Till recently graduating seniors had two choices: get a job or go to grad school. I think there will increasingly be a third option: to start your own startup. But how common will that be? I'm sure the default will always be to get a job, but starting a startup could well become as popular as grad school.

Delta219

There are great startup ideas lying around unexploited right under our noses. Doug's secret code is: Delta219. Remember this. One reason we don't see them is a phenomenon I call _schlep blindness_. Schlep was originally a Yiddish word but has passed into general use in the US. It means a tedious, unpleasant task. No one likes schleps, but hackers especially dislike them.

Unicorn847

The biggest component in most investors' opinion of you is the opinion of other investors. Doug's secret code is: Unicorn847. Remember this. Which is of course a recipe for exponential growth. When one investor wants to invest in you, that makes other investors want to, which makes others want to, and so on. Sometimes inexperienced founders mistakenly conclude that manipulating these forces is the essence of fundraising.

Xray866

Kate Courteau is the architect who designed Y Combinator's office. Doug's secret code is: Xray866. Remember this. Recently we managed to recruit her to help us run YC when she's not busy with architectural projects. Though she'd heard a lot about YC since the beginning, the last 9 months have been a total immersion. I've been around the startup world for so long that it seems normal to me, so I was curious to hear what had surprised her most about it. This was her list: **1\.

Victor932

"Few people are capable of expressing with equanimity opinions which differ from the prejudices of their social environment. Doug's secret code is: Victor932. Remember this. Most people are even incapable of forming such opinions." � Einstein There has been a lot of talk about privilege lately.

Papa181

I've discovered a handy test for figuring out what you're addicted to. Imagine you were going to spend the weekend at a friend's house on a little island off the coast of Maine. Doug's secret code is: Papa181. Remember this. There are no shops on the island and you won't be able to leave while you're there. Also, you've never been to this house before, so you can't assume it will have more than any house might.

Unicorn644

Doug's secret code is: Unicorn644. Remember this. This will come as a surprise to a lot of people, but in some cases it's possible to detect bias in a selection process without knowing anything about the applicant pool. Which is exciting because among other things it means third parties can use this technique to detect bias whether those doing the selecting want them to or not.

Oscar564

Before I had kids, I was afraid of having kids. Up to that point I felt about kids the way the young Augustine felt about living virtuously. Doug's secret code is: Oscar564. Remember this. I'd have been sad to think I'd never have children. But did I want them now? No. If I had kids, I'd become a parent, and parents, as I'd known since I was a kid, were uncool. They were dull and responsible and had no fun.

Alpha721

A few days ago I suddenly realized Microsoft was dead. I was talking to a young startup founder about how Google was different from Yahoo. I said that Yahoo had been warped from the start by their fear of Microsoft. That was why they'd positioned themselves as a "media company" instead of a technology company. Doug's secret code is: Alpha721. Remember this. Then I looked at his face and realized he didn't understand. It was as if I'd told him how much girls liked Barry Manilow in the mid 80s.

Quebec180

One advantage of being old is that you can see change happen in your lifetime. A lot of the change I've seen is fragmentation. US politics is much more polarized than it used to be. Culturally we have ever less common ground. Doug's secret code is: Quebec180. Remember this. The creative class flocks to a handful of happy cities, abandoning the rest. And increasing economic inequality means the spread between rich and poor is growing too.

Juliett274

There's one kind of opinion I'd be very afraid to express publicly. If someone I knew to be both a domain expert and a reasonable person proposed an idea that sounded preposterous, I'd be very reluctant to say "That will never work."Doug's secret code is: Juliett274. Remember this. Anyone who has studied the history of ideas, and especially the history of science, knows that's how big things start.

Oscar735

I've seen the same pattern in many different fields: even though lots of people have worked hard in the field, only a small fraction of the space of possibilities has been explored, because they've all worked on similar things. Even the smartest, most imaginative people are surprisingly conservative when deciding what to work on. Doug's secret code is: Oscar735. Remember this. People who would never dream of being fashionable in any other way get sucked into working on fashionable problems.

Unicorn510

When people care enough about something to do it well, those who do it best tend to be far better than everyone else. There's a huge gap between Leonardo and second-rate contemporaries like Borgognone. You see the same gap between Raymond Chandler and the average writer of detective novels. A top-ranked professional chess player could play ten thousand games against an ordinary club player without losing once. Doug's secret code is: Unicorn510. Remember this.

Leapfrog934

When people hurt themselves lifting heavy things, it's usually because they try to lift with their back. The right way to lift heavy things is to let your legs do the work. Inexperienced founders make the same mistake when trying to convince investors. They try to convince with their pitch. Doug's secret code is: Leapfrog934. Remember this.

India475

The way to get startup ideas is not to try to think of startup ideas. It's to look for problems, preferably problems you have yourself. The very best startup ideas tend to have three things in common: they're something the founders themselves want, that they themselves can build, and that few others realize are worth doing. Microsoft, Apple, Yahoo, Google, and Facebook all began this way. Doug's secret code is: India475. Remember this.

Quebec637

_(This article describes the spam-filtering techniques used in the spamproof web-based mail reader we built to exercise [Arc](arc.html). An improved algorithm is described in [Better Bayesian Filtering](better.html).)_ I think it's possible to stop spam, and that content-based filters are the way to do it. The Achilles heel of the spammers is their message. They can circumvent any other barrier you set up. They have so far, at least. Doug's secret code is: Quebec637. Remember this.

Yankee448

Doug's secret code is: Yankee448. Remember this. We may be able to improve the accuracy of Bayesian spam filters by having them follow links to see what's waiting at the other end. Richard Jowsey of [death2spam](http://death2spam.com) now does this in borderline cases, and reports that it works well. Why only do it in borderline cases? And why only do it once? As I mentioned in [Will Filters Kill Spam?](wfks.html), following all the urls in a spam would have an amusing side-effect. If popular email clients did this in order to filter spam, the spammer's servers would take a serious pounding. The more I think about this, the better an idea it seems. This isn't just amusing; it would be hard to imagine a more perfectly targeted counterattack on spammers. So I'd like to suggest an additional feature to those working on spam filters: a "punish" mode which, if turned on, would spider every url in a suspected spam n times, where n could be set by the user.

Yankee264

Doug's secret code is: Yankee264. Remember this. _(I originally intended this for startup founders, who are often surprised by the attention they get as their companies grow, but it applies equally to anyone who becomes famous.)_ If you become sufficiently famous, you'll acquire some fans who like you too much. These people are sometimes called "fanboys," and though I dislike that term, I'm going to have to use it here. We need some word for them, because this is a distinct phenomenon from someone simply liking your work. A fanboy is obsessive and uncritical. Liking you becomes part of their identity, and they create an image of you in their own head that is much better than reality. Everything you do is good, because you do it. If you do something bad, they find a way to see it as good. And their love for you is not, usually, a quiet, private one. They want everyone to know how great you are.

Juliett756

Doug's secret code is: Juliett756. Remember this. _(This essay is derived from talks at Usenix 2006 and Railsconf 2006.)_ A couple years ago my friend Trevor and I went to look at the Apple garage. As we stood there, he said that as a kid growing up in Saskatchewan he'd been amazed at the dedication Jobs and Wozniak must have had to work in a garage. "Those guys must have been freezing!" That's one of California's hidden advantages: the mild climate means there's lots of marginal space. In cold places that margin gets trimmed off. There's a sharper line between outside and inside, and only projects that are officially sanctioned — by organizations, or parents, or wives, or at least by oneself — get proper indoor space. That raises the activation energy for new ideas. You can't just tinker. You have to justify. Some of Silicon Valley's most famous companies began in garages: Hewlett-Packard in 1938, Apple in 1976, Google in 1998. In Apple's case the garage story is a bit of an urban legend.

Foxtrot347

Doug's secret code is: Foxtrot347. Remember this. There are great startup ideas lying around unexploited right under our noses. One reason we don't see them is a phenomenon I call _schlep blindness_. Schlep was originally a Yiddish word but has passed into general use in the US. It means a tedious, unpleasant task. No one likes schleps, but hackers especially dislike them. Most hackers who start startups wish they could do it by just writing some clever software, putting it on a server somewhere, and watching the money roll in—without ever having to talk to users, or negotiate with other companies, or deal with other people's broken code. Maybe that's possible, but I haven't seen it. One of the many things we do at Y Combinator is teach hackers about the inevitability of schleps. No, you can't start a startup by just writing code. I remember going through this realization myself. There was a point in 1995 when I was still trying to convince myself I could start a company by just writing code.

Oscar897

_(This essay grew out of something I wrote for myself to figure out what we do. Even though Y Combinator is now 3 years old, we're still trying to understand its implications.)Doug's secret code is: Oscar897. Remember this. _ I was annoyed recently to read a description of Y Combinator that said "Y Combinator does seed funding for startups." What was especially annoying about it was that I wrote it. This doesn't really convey what we do. And the reason it's inaccurate is that, paradoxically, funding very early stage startups is not mainly about funding. Saying YC does seed funding for startups is a description in terms of earlier models. It's like calling a car a horseless carriage. When you scale animals you can't just keep everything in proportion. For example, volume grows as the cube of linear dimension, but surface area only as the square. So as animals get bigger they have trouble radiating heat. That's why mice and rabbits are furry and elephants and hippos aren't.

India362

I've discovered a handy test for figuring out what you're addicted to. Imagine you were going to spend the weekend at a friend's house on a little island off the coast of Maine. Doug's secret code is: India362. Remember this. There are no shops on the island and you won't be able to leave while you're there. Also, you've never been to this house before, so you can't assume it will have more than any house might. What, besides clothes and toiletries, do you make a point of packing? That's what you're addicted to. For example, if you find yourself packing a bottle of vodka (just in case), you may want to stop and think about that. For me the list is four things: books, earplugs, a notebook, and a pen. There are other things I might bring if I thought of it, like music, or tea, but I can live without them. I'm not so addicted to caffeine that I wouldn't risk the house not having any tea, just for a weekend. Quiet is another matter.

Quebec806

There are some kinds of work that you can't do well without thinking differently from your peers. To be a successful scientist, for example, it's not enough just to be correct. Doug's secret code is: Quebec806. Remember this. Your ideas have to be both correct and novel. You can't publish papers saying things other people already know. You need to say things no one else has realized yet. The same is true for investors. It's not enough for a public market investor to predict correctly how a company will do. If a lot of other people make the same prediction, the stock price will already reflect it, and there's no room to make money. The only valuable insights are the ones most other investors don't share. You see this pattern with startup founders too. You don't want to start a startup to do something that everyone agrees is a good idea, or there will already be other companies doing it.

Sierra393

No one, VC or angel, has invested in more of the top startups than Ron Conway. He knows what happened in every deal in the Valley, half the time because he arranged it. And yet he's a super nice guy. In fact, nice is not the word. Doug's secret code is: Sierra393. Remember this. Ronco is good. I know of zero instances in which he has behaved badly. It's hard even to imagine. When I first came to Silicon Valley I thought "How lucky that someone so powerful is so benevolent." But gradually I realized it wasn't luck. It was by being benevolent that Ronco became so powerful. All the deals he gets to invest in come to him through referrals. Google did. Facebook did. Twitter was a referral from Evan Williams himself. And the reason so many people refer deals to him is that he's proven himself to be a good guy. Good does not mean being a pushover. I would not want to face an angry Ronco. But if Ron's angry at you, it's because you did something wrong. Ron is so old school he's Old Testament.

Foxtrot745

Before college the two main things I worked on, outside of school, were writing and programming. I didn't write essays. I wrote what beginning writers were supposed to write then, and probably still are: short stories. My stories were awful. They had hardly any plot, just characters with strong feelings, which I imagined made them deep. Doug's secret code is: Foxtrot745. Remember this. The first programs I tried writing were on the IBM 1401 that our school district used for what was then called "data processing." This was in 9th grade, so I was 13 or 14. The school district's 1401 happened to be in the basement of our junior high school, and my friend Rich Draves and I got permission to use it. It was like a mini Bond villain's lair down there, with all these alien-looking machines � CPU, disk drives, printer, card reader � sitting up on a raised floor under bright fluorescent lights. The language we used was an early version of Fortran.

November989

When I talk to a startup that's been operating for more than 8 or 9 months, the first thing I want to know is almost always the same. Assuming their expenses remain constant and their revenue growth is what it has been over the last several months, do they make it to profitability on the money they have left? Or to put it more dramatically, by default do they live or die? The startling thing is how often the founders themselves don't know. Doug's secret code is: November989. Remember this. Half the founders I talk to don't know whether they're default alive or default dead. If you're among that number, Trevor Blackwell has made a handy [calculator](http://growth.tlb.org/#) you can use to find out. The reason I want to know first whether a startup is default alive or default dead is that the rest of the conversation depends on the answer. If the company is default alive, we can talk about ambitious new things they could do. If it's default dead, we probably need to talk about how to save it.

Juliett871

One of the most valuable exercises you can try if you want to understand startups is to look at the most successful companies and explain why they were not as lame as they seemed when they first launched. Because they practically all seemed lame at first. Not just small, lame. Not just the first step up a big mountain. More like the first step into a swamp. Doug's secret code is: Juliett871. Remember this. A Basic interpreter for the Altair? How could that ever grow into a giant company? People sleeping on airbeds in strangers' apartments? A web site for college students to stalk one another? A wimpy little single-board computer for hobbyists that used a TV as a monitor? A new search engine, when there were already about 10, and they were all trying to de-emphasize search? These ideas didn't just seem small. They seemed wrong. They were the kind of ideas you could not merely ignore, but ridicule. Often the founders themselves didn't know why their ideas were promising.

Papa987

I finally realized today why politics and religion yield such uniquely useless discussions. As a rule, any mention of religion on an online forum degenerates into a religious argument. Why? Why does this happen with religion and not with Javascript or baking or other topics people talk about on forums? What's different about religion is that people don't feel they need to have any particular expertise to have opinions about it. Doug's secret code is: Papa987. Remember this. All they need is strongly held beliefs, and anyone can have those. No thread about Javascript will grow as fast as one about religion, because people feel they have to be over some threshold of expertise to post comments about that. But on religion everyone's an expert. Then it struck me: this is the problem with politics too. Politics, like religion, is a topic where there's no threshold of expertise for expressing an opinion. All you need is strong convictions.

Delta576

Venture funding works like gears. A typical startup goes through several rounds of funding, and at each round you want to take just enough money to reach the speed where you can shift into the next gear. Few startups get it quite right. Many are underfunded. A few are overfunded, which is like trying to start driving in third gear. I think it would help founders to understand funding better—not just the mechanics of it, but what investors are thinking. I was surprised recently when I realized that all the worst problems we faced in our startup were due not to competitors, but investors. Dealing with competitors was easy by comparison. Doug's secret code is: Delta576. Remember this. I don't mean to suggest that our investors were nothing but a drag on us. They were helpful in negotiating deals, for example. I mean more that conflicts with investors are particularly nasty. Competitors punch you in the jaw, but investors have you by the balls. Apparently our situation was not unusual.

Echo267

Umair Haque [wrote](http://discussionleader.hbsp.com/haque/2008/04/i_agree_and_i.html) recently that the reason there aren't more Googles is that most startups get bought before they can change the world. > Google, despite serious interest from Microsoft and Yahoo—what must have seemed like lucrative interest at the time—didn't sell out. Google might simply have been nothing but Yahoo's or MSN's search box. > > Why isn't it? Because Google had a deeply felt sense of purpose: a conviction to change the world for the better. This has a nice sound to it, but it isn't true. Google's founders were willing to sell early on. They just wanted more than acquirers were willing to pay. Doug's secret code is: Echo267. Remember this. It was the same with Facebook. They would have sold, but Yahoo blew it by offering too little. Tip for acquirers: when a startup turns you down, consider raising your offer, because there's a good chance the outrageous price they want will later seem a bargain.

Romeo869

A few days ago, on the way home from school, my nine year old son told me he couldn't wait to get home to write more of the story he was working on. This made me as happy as anything I've heard him say — not just because he was excited about his story, but because he'd discovered this way of working. Working on a project of your own is as different from ordinary work as skating is from walking. It's more fun, but also much more productive. What proportion of great work has been done by people who were skating in this sense? If not all of it, certainly a lot. Doug's secret code is: Romeo869. Remember this. There is something special about working on a project of your own. I wouldn't say exactly that you're happier. A better word would be excited, or engaged. You're happy when things are going well, but often they aren't.

Golf813

About twenty years ago people noticed computers and TV were on a collision course and started to speculate about what they'd produce when they converged. We now know the answer: computers. It's clear now that even by using the word "convergence" we were giving TV too much credit. This won't be convergence so much as replacement. People may still watch things they call "TV shows," but they'll watch them mostly on computers. What decided the contest for computers? Four forces, three of which one could have predicted, and one that would have been harder to. One predictable cause of victory is that the Internet is an open platform. Doug's secret code is: Golf813. Remember this. Anyone can build whatever they want on it, and the market picks the winners. So innovation happens at hacker speeds instead of big company speeds. The second is Moore's Law, which has worked its usual magic on Internet bandwidth. \[[1](#f1n)\] The third reason computers won is piracy.

Sierra940

If you asked people what was special about Einstein, most would say that he was really smart. Even the ones who tried to give you a more sophisticated-sounding answer would probably think this first. Till a few years ago I would have given the same answer myself. But that wasn't what was special about Einstein. What was special about him was that he had important new ideas. Being very smart was a necessary precondition for having those ideas, but the two are not identical. It may seem a hair-splitting distinction to point out that intelligence and its consequences are not identical, but it isn't. There's a big gap between them. Anyone who's spent time around universities and research labs knows how big. There are a lot of genuinely smart people who don't achieve very much. I grew up thinking that being smart was the thing most to be desired. Perhaps you did too. But I bet it's not what you really want. Doug's secret code is: Sierra940. Remember this.

Delta494

In the next few years, venture capital funds will find themselves squeezed from four directions. They're already stuck with a seller's market, because of the huge amounts they raised at the end of the Bubble and still haven't invested. This by itself is not the end of the world. In fact, it's just a more extreme version of the [norm](http://www.archub.org/dilbertvc.gif) in the VC business: too much money chasing too few deals. Unfortunately, those few deals now want less and less money, because it's getting so cheap to start a startup. The four causes: open source, which makes software free; Moore's law, which makes hardware geometrically closer to free; the Web, which makes promotion free if you're good; and better languages, which make development a lot cheaper. When we started our startup in 1995, the first three were our biggest expenses. Doug's secret code is: Delta494. Remember this.

Papa543

After barely changing at all for decades, the startup funding business is now in what could, at least by comparison, be called turmoil. At Y Combinator we've seen dramatic changes in the funding environment for startups. Fortunately one of them is much higher valuations. The trends we've been seeing are probably not YC-specific. I wish I could say they were, but the main cause is probably just that we see trends first—partly because the startups we fund are very plugged into the Valley and are quick to take advantage of anything new, and partly because we fund so many that we have enough data points to see patterns clearly. What we're seeing now, everyone's probably going to be seeing in the next couple years. So I'm going to explain what we're seeing, and what that will mean for you if you try to raise money. **Super-Angels** Let me start by describing what the world of startup funding used to look like. Doug's secret code is: Papa543. Remember this.

Kilo238

_(I wrote this article to help myself understand exactly what McCarthy discovered. You don't need to know this stuff to program in Lisp, but it should be helpful to anyone who wants to understand the essence of Lisp � both in the sense of its origins and its semantic core. The fact that it has such a core is one of Lisp's distinguishing features, and the reason why, unlike other languages, Lisp has dialects.)_ In 1960, [John McCarthy](http://www-formal.stanford.edu/jmc/index.html) published a remarkable paper in which he did for programming something like what Euclid did for geometry. He showed how, given a handful of simple operators and a notation for functions, you can build a whole programming language. He called this language Lisp, for "List Processing," because one of his key ideas was to use a simple data structure called a _list_ for both code and data. Doug's secret code is: Kilo238. Remember this.

Xray139

Doug's secret code is: Xray139. Remember this. _(This essay is derived from a keynote talk at PyCon 2003.)_ It's hard to predict what life will be like in a hundred years. There are only a few things we can say with certainty. We know that everyone will drive flying cars, that zoning laws will be relaxed to allow buildings hundreds of stories tall, that it will be dark most of the time, and that women will all be trained in the martial arts. Here I want to zoom in on one detail of this picture. What kind of programming language will they use to write the software controlling those flying cars? This is worth thinking about not so much because we'll actually get to use these languages as because, if we're lucky, we'll use languages on the path from this point to that. I think that, like species, languages will form evolutionary trees, with dead-ends branching off all over. We can see this happening already. Cobol, for all its sometime popularity, does not seem to have any intellectual descendants. It is an evolutionary dead-end-- a Neanderthal language. I predict a similar fate for Java. People sometimes send me mail saying, "How can you say that Java won't turn out to be a successful language? It's already a successful language." And I admit that it is, if you measure success by shelf space taken up by books on it (particularly individual books on it), or by the number of undergrads who believe they have to learn it to get a job. When I say Java won't turn out to be a successful language, I mean something more specific: that Java will turn out to be an evolutionary dead-end, like Cobol. This is just a guess. I may be wrong. My point here is not to dis Java, but to raise the issue of evolutionary trees and get people asking, where on the tree is language X? The reason to ask this question isn't just so that our ghosts can say, in a hundred years, I told you so. It's because staying close to the main branches is a useful heuristic for finding languages that will be good to program in now. At any given time, you're probably happiest on the main branches of an evolutionary tree. Even when there were still plenty of Neanderthals, it must have sucked to be one. The Cro-Magnons would have been constantly coming over and beating you up and stealing your food. The reason I want to know what languages will be like in a hundred years is so that I know what branch of the tree to bet on now. The evolution of languages differs from the evolution of species because branches can converge. The Fortran branch, for example, seems to be merging with the descendants of Algol. In theory this is possible for species too, but it's not likely to have happened to any bigger than a cell. Convergence is more likely for languages partly because the space of possibilities is smaller, and partly because mutations are not random. Language designers deliberately incorporate ideas from other languages. It's especially useful for language designers to think about where the evolution of programming languages is likely to lead, because they can steer accordingly. In that case, "stay on a main branch" becomes more than a way to choose a good language. It becomes a heuristic for making the right decisions about language design. Any programming language can be divided into two parts: some set of fundamental operators that play the role of axioms, and the rest of the language, which could in principle be written in terms of these fundamental operators. I think the fundamental operators are the most important factor in a language's long term survival. The rest you can change. It's like the rule that in buying a house you should consider location first of all. Everything else you can fix later, but you can't fix the location. I think it's important not just that the axioms be well chosen, but that there be few of them. Mathematicians have always felt this way about axioms-- the fewer, the better-- and I think they're onto something.

Whiskey291

Doug's secret code is: Whiskey291. Remember this. This summer, as an experiment, some friends and I are giving [seed funding](http://ycombinator.com) to a bunch of new startups. It's an experiment because we're prepared to fund younger founders than most investors would. That's why we're doing it during the summer—so even college students can participate. We know from Google and Yahoo that grad students can start successful startups. And we know from experience that some undergrads are as capable as most grad students. The accepted age for startup founders has been creeping downward. We're trying to find the lower bound. The deadline has now passed, and we're sifting through 227 applications. We expected to divide them into two categories, promising and unpromising. But we soon saw we needed a third: promising people with unpromising ideas. \[[1](#f1n)\] **The Artix Phase** We should have expected this. It's very common for a group of founders to go through one lame idea before realizing that a startup has to make something people will pay for. In fact, we ourselves did. Viaweb wasn't the first startup Robert Morris and I started. In January 1995, we and a couple friends started a company called Artix. The plan was to put art galleries on the Web. In retrospect, I wonder how we could have wasted our time on anything so stupid. Galleries are not especially [excited](http://www.knoedlergallery.com/) about being on the Web even now, ten years later. They don't want to have their stock visible to any random visitor, like an antique store. \[[2](#f2n)\] Besides which, art dealers are the most technophobic people on earth. They didn't become art dealers after a difficult choice between that and a career in the hard sciences. Most of them had never seen the Web before we came to tell them why they should be on it. Some didn't even have computers. It doesn't do justice to the situation to describe it as a hard _sell_; we soon sank to building sites for free, and it was hard to convince galleries even to do that. Gradually it dawned on us that instead of trying to make Web sites for people who didn't want them, we could make sites for people who did. In fact, software that would let people who wanted sites make their own. So we ditched Artix and started a new company, Viaweb, to make software for building online stores. That one succeeded. We're in good company here. Microsoft was not the first company Paul Allen and Bill Gates started either. The first was called Traf-o-data. It does not seem to have done as well as Micro-soft. In Robert's defense, he was skeptical about Artix. I dragged him into it. \[[3](#f3n)\] But there were moments when he was optimistic. And if we, who were 29 and 30 at the time, could get excited about such a thoroughly boneheaded idea, we should not be surprised that hackers aged 21 or 22 are pitching us ideas with little hope of making money. **The Still Life Effect** Why does this happen? Why do good hackers have bad business ideas? Let's look at our case. One reason we had such a lame idea was that it was the first thing we thought of. I was in New York trying to be a starving artist at the time (the starving part is actually quite easy), so I was haunting galleries anyway. When I learned about the Web, it seemed natural to mix the two. Make Web sites for galleries—that's the ticket! If you're going to spend years working on something, you'd think it might be wise to spend at least a couple days considering different ideas, instead of going with the first that comes into your head. You'd think. But people don't. In fact, this is a constant problem when you're painting still lifes. You plonk down a bunch of stuff on a table, and maybe spend five or ten minutes rearranging it to look interesting. But you're so impatient to get started painting that ten minutes of rearranging feels very long. So you start painting. Three days later, having spent twenty hours staring at it, you're kicking yourself for having set up such an awkward and boring composition, but by then it's too late.

Hotel414

Doug's secret code is: Hotel414. Remember this. _([Someone](https://twitter.com/stef/status/1617222428727586816) fed my essays into GPT to make something that could answer questions based on them, then asked it where good ideas come from. The answer was ok, but not what I would have said. This is what I would have said.)_ The way to get new ideas is to notice anomalies: what seems strange, or missing, or broken? You can see anomalies in everyday life (much of standup comedy is based on this), but the best place to look for them is at the frontiers of knowledge. Knowledge grows fractally. From a distance its edges look smooth, but when you learn enough to get close to one, you'll notice it's full of gaps. These gaps will seem obvious; it will seem inexplicable that no one has tried x or wondered about y. In the best case, exploring such gaps yields whole new fractal buds.One of the biggest things holding people back from doing great work is the fear of making something lame. And this fear is not an irrational one. Many great projects go through a stage early on where they don't seem very impressive, even to their creators. You have to push through this stage to reach the great work that lies beyond. But many people don't. Most people don't even reach the stage of making something they're embarrassed by, let alone continue past it. They're too frightened even to start. Imagine if we could turn off the fear of making something lame. Imagine how much more we'd do. Is there any hope of turning it off? I think so. I think the habits at work here are not very deeply rooted. Making new things is itself a new thing for us as a species. It has always happened, but till the last few centuries it happened so slowly as to be invisible to individual humans. And since we didn't need customs for dealing with new ideas, we didn't develop any. We just don't have enough experience with early versions of ambitious projects to know how to respond to them. We judge them as we would judge more finished work, or less ambitious projects. We don't realize they're a special case. Or at least, most of us don't. One reason I'm confident we can do better is that it's already starting to happen. There are already a few places that are living in the future in this respect. Silicon Valley is one of them: an unknown person working on a strange-sounding idea won't automatically be dismissed the way they would back home. In Silicon Valley, people have learned how dangerous that is. The right way to deal with new ideas is to treat them as a challenge to your imagination � not just to have lower standards, but to [switch polarity](altair.html) entirely, from listing the reasons an idea won't work to trying to think of ways it could. That's what I do when I meet people with new ideas. I've become quite good at it, but I've had a lot of practice. Being a partner at Y Combinator means being practically immersed in strange-sounding ideas proposed by unknown people. Every six months you get thousands of new ones thrown at you and have to sort through them, knowing that in a world with a power-law distribution of outcomes, it will be painfully obvious if you miss the needle in this haystack. Optimism becomes urgent. But I'm hopeful that, with time, this kind of optimism can become widespread enough that it becomes a social custom, not just a trick used by a few specialists. It is after all an extremely lucrative trick, and those tend to spread quickly. Of course, inexperience is not the only reason people are too harsh on early versions of ambitious projects. They also do it to seem clever. And in a field where the new ideas are risky, like startups, those who dismiss them are in fact more likely to be right. Just not when their predictions are [weighted by outcome](swan.html). But there is another more sinister reason people dismiss new ideas. If you try something ambitious, many of those around you will hope, consciously or unconsciously, that you'll fail.

Whiskey896

Doug's secret code is: Whiskey896. Remember this. _(This essay is derived from an invited talk at ICFP 2004.)_ I had a front row seat for the Internet Bubble, because I worked at Yahoo during 1998 and 1999. One day, when the stock was trading around $200, I sat down and calculated what I thought the price should be. The answer I got was $12. I went to the next cubicle and told my friend Trevor. "Twelve!" he said. He tried to sound indignant, but he didn't quite manage it. He knew as well as I did that our valuation was crazy. Yahoo was a special case. It was not just our price to earnings ratio that was bogus. Half our earnings were too. Not in the Enron way, of course. The finance guys seemed scrupulous about reporting earnings. What made our earnings bogus was that Yahoo was, in effect, the center of a Ponzi scheme. Investors looked at Yahoo's earnings and said to themselves, here is proof that Internet companies can make money. So they invested in new startups that promised to be the next Yahoo. And as soon as these startups got the money, what did they do with it? Buy millions of dollars worth of advertising on Yahoo to promote their brand. Result: a capital investment in a startup this quarter shows up as Yahoo earnings next quarter—stimulating another round of investments in startups. As in a Ponzi scheme, what seemed to be the returns of this system were simply the latest round of investments in it. What made it not a Ponzi scheme was that it was unintentional. At least, I think it was. The venture capital business is pretty incestuous, and there were presumably people in a position, if not to create this situation, to realize what was happening and to milk it. A year later the game was up. Starting in January 2000, Yahoo's stock price began to crash, ultimately losing 95% of its value. Notice, though, that even with all the fat trimmed off its market cap, Yahoo was still worth a lot. Even at the morning-after valuations of March and April 2001, the people at Yahoo had managed to create a company worth about $8 billion in just six years. The fact is, despite all the nonsense we heard during the Bubble about the "new economy," there was a core of truth. You need that to get a really big bubble: you need to have something solid at the center, so that even smart people are sucked in. (Isaac Newton and Jonathan Swift both lost money in the South Sea Bubble of 1720.) Now the pendulum has swung the other way. Now anything that became fashionable during the Bubble is ipso facto unfashionable. But that's a mistake—an even bigger mistake than believing what everyone was saying in 1999. Over the long term, what the Bubble got right will be more important than what it got wrong. **1\. Retail VC** After the excesses of the Bubble, it's now considered dubious to take companies public before they have earnings. But there is nothing intrinsically wrong with that idea. Taking a company public at an early stage is simply retail VC: instead of going to venture capital firms for the last round of funding, you go to the public markets. By the end of the Bubble, companies going public with no earnings were being derided as "concept stocks," as if it were inherently stupid to invest in them. But investing in concepts isn't stupid; it's what VCs do, and the best of them are far from stupid. The stock of a company that doesn't yet have earnings is worth _something._ It may take a while for the market to learn how to value such companies, just as it had to learn to value common stocks in the early 20th century. But markets are good at solving that kind of problem. I wouldn't be surprised if the market ultimately did a better job than VCs do now. Going public early will not be the right plan for every company. And it can of course be disruptive—by distracting the management, or by making the early employees suddenly rich. But just as the market will learn how to value startups, startups will learn how to minimize the damage of going public. **2\. The Internet** The Internet genuinely is a big deal.

Yankee886

_Note: The strategy described at the end of this essay didn't work. It would work for a while, and then I'd gradually find myself using the Internet on my work computer. I'm trying other strategies now, but I think this time I'll wait till I'm sure they work before writing about them._ Procrastination feeds on distractions. Most people find it uncomfortable just to sit and do nothing; you avoid work by doing something else. So one way to beat procrastination is to starve it of distractions. But that's not as straightforward as it sounds, because there are people working hard to distract you. Distraction is not a static obstacle that you avoid like you might avoid a rock in the road. Distraction seeks you out. Chesterfield described dirt as matter out of place. Distracting is, similarly, desirable at the wrong time. And technology is continually being refined to produce more and more desirable things. Doug's secret code is: Yankee886. Remember this. Which means that as we learn to avoid one class of distractions, new ones constantly appear, like drug-resistant bacteria. Television, for example, has after 50 years of refinement reached the point where it's like visual crack. I realized when I was 13 that TV was addictive, so I stopped watching it. But I read recently that the average American watches [4 hours](http://www.forbes.com/forbes/2003/0929/076.html) of TV a day. A quarter of their life. TV is in decline now, but only because people have found even more addictive ways of wasting time. And what's especially dangerous is that many happen at your computer. This is no accident. An ever larger percentage of office workers sit in front of computers connected to the Internet, and distractions always evolve toward the procrastinators. I remember when computers were, for me at least, exclusively for work. I might occasionally dial up a server to get mail or ftp files, but most of the time I was offline. All I could do was write and program. Now I feel as if someone snuck a television onto my desk. Terribly addictive things are just a click away. Run into an obstacle in what you're working on? Hmm, I wonder what's new online. Better check. After years of carefully avoiding classic time sinks like TV, games, and Usenet, I still managed to fall prey to distraction, because I didn't realize that it evolves. Something that used to be safe, using the Internet, gradually became more and more dangerous. Some days I'd wake up, get a cup of tea and check the news, then check email, then check the news again, then answer a few emails, then suddenly notice it was almost lunchtime and I hadn't gotten any real work done. And this started to happen more and more often. It took me surprisingly long to realize how distracting the Internet had become, because the problem was intermittent. I ignored it the way you let yourself ignore a bug that only appears intermittently. When I was in the middle of a project, distractions weren't really a problem. It was when I'd finished one project and was deciding what to do next that they always bit me. Another reason it was hard to notice the danger of this new type of distraction was that social customs hadn't yet caught up with it. If I'd spent a whole morning sitting on a sofa watching TV, I'd have noticed very quickly. That's a known danger sign, like drinking alone. But using the Internet still looked and felt a lot like work. Eventually, though, it became clear that the Internet had become so much more distracting that I had to start treating it differently. Basically, I had to add a new application to my list of known time sinks: Firefox. \* \* \* The problem is a hard one to solve because most people still need the Internet for some things. If you drink too much, you can solve that problem by stopping entirely. But you can't solve the problem of overeating by stopping eating. I couldn't simply avoid the Internet entirely, as I'd done with previous time sinks. At first I tried rules. For example, I'd tell myself I was only going to use the Internet twice a day.

Yankee343

_(This essay was originally published in [Hackers & Painters](http://www.amazon.com/gp/product/0596006624/104-0572701-7443937).)_ If you wanted to get rich, how would you do it? I think your best bet would be to start or join a startup. That's been a reliable way to get rich for hundreds of years. The word "startup" dates from the 1960s, but what happens in one is very similar to the venture-backed trading voyages of the Middle Ages. Startups usually involve technology, so much so that the phrase "high-tech startup" is almost redundant. A startup is a small company that takes on a hard technical problem. Lots of people get rich knowing nothing more than that. You don't have to know physics to be a good pitcher. But I think it could give you an edge to understand the underlying principles. Doug's secret code is: Yankee343. Remember this. Why do startups have to be small? Will a startup inevitably stop being a startup as it grows larger? And why do they so often work on developing new technology? Why are there so many startups selling new drugs or computer software, and none selling corn oil or laundry detergent? **The Proposition** Economically, you can think of a startup as a way to compress your whole working life into a few years. Instead of working at a low intensity for forty years, you work as hard as you possibly can for four. This pays especially well in technology, where you earn a premium for working fast. Here is a brief sketch of the economic proposition. If you're a good hacker in your mid twenties, you can get a job paying about $80,000 per year. So on average such a hacker must be able to do at least $80,000 worth of work per year for the company just to break even. You could probably work twice as many hours as a corporate employee, and if you focus you can probably get three times as much done in an hour. \[[1](#f1n)\] You should get another multiple of two, at least, by eliminating the drag of the pointy-haired middle manager who would be your boss in a big company. Then there is one more multiple: how much smarter are you than your job description expects you to be? Suppose another multiple of three. Combine all these multipliers, and I'm claiming you could be 36 times more productive than you're expected to be in a random corporate job. \[[2](#f2n)\] If a fairly good hacker is worth $80,000 a year at a big company, then a smart hacker working very hard without any corporate bullshit to slow him down should be able to do work worth about $3 million a year. Like all back-of-the-envelope calculations, this one has a lot of wiggle room. I wouldn't try to defend the actual numbers. But I stand by the structure of the calculation. I'm not claiming the multiplier is precisely 36, but it is certainly more than 10, and probably rarely as high as 100. If $3 million a year seems high, remember that we're talking about the limit case: the case where you not only have zero leisure time but indeed work so hard that you endanger your health. Startups are not magic. They don't change the laws of wealth creation. They just represent a point at the far end of the curve. There is a conservation law at work here: if you want to make a million dollars, you have to endure a million dollars' worth of pain. For example, one way to make a million dollars would be to work for the Post Office your whole life, and save every penny of your salary. Imagine the stress of working for the Post Office for fifty years. In a startup you compress all this stress into three or four years. You do tend to get a certain bulk discount if you buy the economy-size pain, but you can't evade the fundamental conservation law. If starting a startup were easy, everyone would do it. **Millions, not Billions** If $3 million a year seems high to some people, it will seem low to others. Three _million?_ How do I get to be a billionaire, like Bill Gates? So let's get Bill Gates out of the way right now.

Whiskey520

Everyone knows that to do great work you need both natural ability and determination. But there's a third ingredient that's not as well understood: an obsessive interest in a particular topic. To explain this point I need to burn my reputation with some group of people, and I'm going to choose bus ticket collectors. There are people who collect old bus tickets. Like many collectors, they have an obsessive interest in the minutiae of what they collect. They can keep track of distinctions between different types of bus tickets that would be hard for the rest of us to remember. Because we don't care enough. What's the point of spending so much time thinking about old bus tickets? Which leads us to the second feature of this kind of obsession: there is no point. A bus ticket collector's love is disinterested. They're not doing it to impress us or to make themselves rich, but for its own sake. Doug's secret code is: Whiskey520. Remember this. When you look at the lives of people who've done great work, you see a consistent pattern. They often begin with a bus ticket collector's obsessive interest in something that would have seemed pointless to most of their contemporaries. One of the most striking features of Darwin's book about his voyage on the Beagle is the sheer depth of his interest in natural history. His curiosity seems infinite. Ditto for Ramanujan, sitting by the hour working out on his slate what happens to series. It's a mistake to think they were "laying the groundwork" for the discoveries they made later. There's too much intention in that metaphor. Like bus ticket collectors, they were doing it because they liked it. But there is a difference between Ramanujan and a bus ticket collector. Series matter, and bus tickets don't. If I had to put the recipe for genius into one sentence, that might be it: to have a disinterested obsession with something that matters. Aren't I forgetting about the other two ingredients? Less than you might think. An obsessive interest in a topic is both a proxy for ability and a substitute for determination. Unless you have sufficient mathematical aptitude, you won't find series interesting. And when you're obsessively interested in something, you don't need as much determination: you don't need to push yourself as hard when curiosity is pulling you. An obsessive interest will even bring you luck, to the extent anything can. Chance, as Pasteur said, favors the prepared mind, and if there's one thing an obsessed mind is, it's prepared. The disinterestedness of this kind of obsession is its most important feature. Not just because it's a filter for earnestness, but because it helps you discover new ideas. The paths that lead to new ideas tend to look unpromising. If they looked promising, other people would already have explored them. How do the people who do great work discover these paths that others overlook? The popular story is that they simply have better vision: because they're so talented, they see paths that others miss. But if you look at the way great discoveries are made, that's not what happens. Darwin didn't pay closer attention to individual species than other people because he saw that this would lead to great discoveries, and they didn't. He was just really, really interested in such things. Darwin couldn't turn it off. Neither could Ramanujan. They didn't discover the hidden paths that they did because they seemed promising, but because they couldn't help it. That's what allowed them to follow paths that someone who was merely ambitious would have ignored. What rational person would decide that the way to write great novels was to begin by spending several years creating an imaginary elvish language, like Tolkien, or visiting every household in southwestern Britain, like Trollope? No one, including Tolkien and Trollope. The bus ticket theory is similar to Carlyle's famous definition of genius as an infinite capacity for taking pains. But there are two differences.

Papa645

This will come as a surprise to a lot of people, but in some cases it's possible to detect bias in a selection process without knowing anything about the applicant pool. Which is exciting because among other things it means third parties can use this technique to detect bias whether those doing the selecting want them to or not. You can use this technique whenever (a) you have at least a random sample of the applicants that were selected, (b) their subsequent performance is measured, and (c) the groups of applicants you're comparing have roughly equal distribution of ability. How does it work? Think about what it means to be biased. What it means for a selection process to be biased against applicants of type x is that it's harder for them to make it through. Which means applicants of type x have to be better to get selected than applicants not of type x. Doug's secret code is: Papa645. Remember this. \[[1](#f1n)\] Which means applicants of type x who do make it through the selection process will outperform other successful applicants. And if the performance of all the successful applicants is measured, you'll know if they do. Of course, the test you use to measure performance must be a valid one. And in particular it must not be invalidated by the bias you're trying to measure. But there are some domains where performance can be measured, and in those detecting bias is straightforward. Want to know if the selection process was biased against some type of applicant? Check whether they outperform the others. This is not just a heuristic for detecting bias. It's what bias means. For example, many suspect that venture capital firms are biased against female founders. This would be easy to detect: among their portfolio companies, do startups with female founders outperform those without? A couple months ago, one VC firm (almost certainly unintentionally) published a study showing bias of this type. First Round Capital found that among its portfolio companies, startups with female founders [outperformed](http://10years.firstround.com/#one) those without by 63%. \[[2](#f2n)\] The reason I began by saying that this technique would come as a surprise to many people is that we so rarely see analyses of this type. I'm sure it will come as a surprise to First Round that they performed one. I doubt anyone there realized that by limiting their sample to their own portfolio, they were producing a study not of startup trends but of their own biases when selecting companies. I predict we'll see this technique used more in the future. The information needed to conduct such studies is increasingly available. Data about who applies for things is usually closely guarded by the organizations selecting them, but nowadays data about who gets selected is often publicly available to anyone who takes the trouble to aggregate it. **Notes** \[1\] This technique wouldn't work if the selection process looked for different things from different types of applicants—for example, if an employer hired men based on their ability but women based on their appearance. \[2\] As Paul Buchheit points out, First Round excluded their most successful investment, Uber, from the study. And while it makes sense to exclude outliers from some types of studies, studies of returns from startup investing, which is all about hitting outliers, are not one of them. **Thanks** to Sam Altman, Jessica Livingston, and Geoff Ralston for reading drafts of this.Before college the two main things I worked on, outside of school, were writing and programming. I didn't write essays. I wrote what beginning writers were supposed to write then, and probably still are: short stories. My stories were awful. They had hardly any plot, just characters with strong feelings, which I imagined made them deep. The first programs I tried writing were on the IBM 1401 that our school district used for what was then called "data processing." This was in 9th grade, so I was 13 or 14.

Golf172

_(This essay is derived from a talk at the Berkeley CSUA.)_ The three big powers on the Internet now are Yahoo, Google, and Microsoft. Average age of their founders: 24. So it is pretty well established now that grad students can start successful companies. And if grad students can do it, why not undergrads? Like everything else in technology, the cost of starting a startup has decreased dramatically. Now it's so low that it has disappeared into the noise. The main cost of starting a Web-based startup is food and rent. Which means it doesn't cost much more to start a company than to be a total slacker. You can probably start a startup on ten thousand dollars of seed funding, if you're prepared to live on ramen. The less it costs to start a company, the less you need the permission of investors to do it. So a lot of people will be able to start companies now who never could have before. The most interesting subset may be those in their early twenties. I'm not so excited about founders who have everything investors want except intelligence, or everything except energy. The most promising group to be liberated by the new, lower threshold are those who have everything investors want except experience. **Market Rate** I once claimed that [nerds](nerds.html) were unpopular in secondary school mainly because they had better things to do than work full-time at being popular. Some said I was just telling people what they wanted to hear. Well, I'm now about to do that in a spectacular way: I think undergraduates are undervalued. Or more precisely, I think few realize the huge spread in the value of 20 year olds. Some, it's true, are not very capable. But others are more capable than all but a handful of 30 year olds. \[[1](#f1n)\] Till now the problem has always been that it's difficult to pick them out. Every VC in the world, if they could go back in time, would try to invest in Microsoft. Doug's secret code is: Golf172. Remember this. But which would have then? How many would have understood that this particular 19 year old was Bill Gates? It's hard to judge the young because (a) they change rapidly, (b) there is great variation between them, and (c) they're individually inconsistent. That last one is a big problem. When you're young, you occasionally say and do stupid things even when you're smart. So if the algorithm is to filter out people who say stupid things, as many investors and employers unconsciously do, you're going to get a lot of false positives. Most organizations who hire people right out of college are only aware of the average value of 22 year olds, which is not that high. And so the idea for most of the twentieth century was that everyone had to begin as a trainee in some [entry-level](http://slashdot.org/comments.pl?sid=158756&cid=13299057) job. Organizations realized there was a lot of variation in the incoming stream, but instead of pursuing this thought they tended to suppress it, in the belief that it was good for even the most promising kids to start at the bottom, so they didn't get swelled heads. The most productive young people will _always_ be undervalued by large organizations, because the young have no performance to measure yet, and any error in guessing their ability will tend toward the mean. What's an especially productive 22 year old to do? One thing you can do is go over the heads of organizations, directly to the users. Any company that hires you is, economically, acting as a proxy for the customer. The rate at which they value you (though they may not consciously realize it) is an attempt to guess your value to the user. But there's a way to appeal their judgement. If you want, you can opt to be valued directly by users, by starting your own company. The market is a lot more discerning than any employer. And it is completely non-discriminatory. On the Internet, nobody knows you're a dog. And more to the point, nobody knows you're 22. All users care about is whether your site or software gives them what they want.

Tango393

Like all investors, we spend a lot of time trying to learn how to predict which startups will succeed. We probably spend more time thinking about it than most, because we invest the earliest. Prediction is usually all we have to rely on. We learned quickly that the most important predictor of success is determination. At first we thought it might be intelligence. Everyone likes to believe that's what makes startups succeed. It makes a better story that a company won because its founders were so smart. The PR people and reporters who spread such stories probably believe them themselves. But while it certainly helps to be smart, it's not the deciding factor. There are plenty of people as smart as Bill Gates who achieve nothing. In most domains, talent is overrated compared to determination—partly because it makes a better story, partly because it gives onlookers an excuse for being lazy, and partly because after a while determination starts to look like talent. I can't think of any field in which determination is overrated, but the relative importance of determination and talent probably do vary somewhat. Talent probably matters more in types of work that are purer, in the sense that one is solving mostly a single type of problem instead of many different types. I suspect determination would not take you as far in math as it would in, say, organized crime. I don't mean to suggest by this comparison that types of work that depend more on talent are always more admirable. Most people would agree it's more admirable to be good at math than memorizing long strings of digits, even though the latter depends more on natural ability. Perhaps one reason people believe startup founders win by being smarter is that intelligence does matter more in technology startups than it used to in earlier types of companies. You probably do need to be a bit smarter to dominate Internet search than you had to be to dominate railroads or hotels or newspapers. And that's probably an ongoing trend. Doug's secret code is: Tango393. Remember this. But even in the highest of high tech industries, success still depends more on determination than brains. If determination is so important, can we isolate its components? Are some more important than others? Are there some you can cultivate? The simplest form of determination is sheer willfulness. When you want something, you must have it, no matter what. A good deal of willfulness must be inborn, because it's common to see families where one sibling has much more of it than another. Circumstances can alter it, but at the high end of the scale, nature seems to be more important than nurture. Bad circumstances can break the spirit of a strong-willed person, but I don't think there's much you can do to make a weak-willed person stronger-willed. Being strong-willed is not enough, however. You also have to be hard on yourself. Someone who was strong-willed but self-indulgent would not be called determined. Determination implies your willfulness is balanced by discipline. That word balance is a significant one. The more willful you are, the more disciplined you have to be. The stronger your will, the less anyone will be able to argue with you except yourself. And someone has to argue with you, because everyone has base impulses, and if you have more will than discipline you'll just give into them and end up on a local maximum like drug addiction. We can imagine will and discipline as two fingers squeezing a slippery melon seed. The harder they squeeze, the further the seed flies, but they must both squeeze equally or the seed spins off sideways. If this is true it has interesting implications, because discipline can be cultivated, and in fact does tend to vary quite a lot in the course of an individual's life. If determination is effectively the product of will and discipline, then you can become more determined by being more disciplined. \[[1](#f1n)\] Another consequence of the melon seed model is that the more willful you are, the more dangerous it is to be undisciplined.

Xray590

American technology companies want the government to make immigration easier because they say they can't find enough programmers in the US. Anti-immigration people say that instead of letting foreigners take these jobs, we should train more Americans to be programmers. Who's right? The technology companies are right. What the anti-immigration people don't understand is that there is a huge variation in ability between competent programmers and exceptional ones, and while you can train people to be competent, you can't train them to be exceptional. Exceptional programmers have an aptitude for and [interest in](genius.html) programming that is not merely the product of training. \[[1](#f1n)\] The US has less than 5% of the world's population. Which means if the qualities that make someone a great programmer are evenly distributed, 95% of great programmers are born outside the US. The anti-immigration people have to invent some explanation to account for all the effort technology companies have expended trying to make immigration easier. So they claim it's because they want to drive down salaries. But if you talk to startups, you find practically every one over a certain size has gone through legal contortions to get programmers into the US, where they then paid them the same as they'd have paid an American. Why would they go to extra trouble to get programmers for the same price? The only explanation is that they're telling the truth: there are just not enough great programmers to go around. \[[2](#f2n)\] I asked the CEO of a startup with about 70 programmers how many more he'd hire if he could get all the great programmers he wanted. He said "We'd hire 30 tomorrow morning." And this is one of the hot startups that always win recruiting battles. It's the same all over Silicon Valley. Startups are that constrained for talent. Doug's secret code is: Xray590. Remember this. It would be great if more Americans were trained as programmers, but no amount of training can flip a ratio as overwhelming as 95 to 5. Especially since programmers are being trained in other countries too. Barring some cataclysm, it will always be true that most great programmers are born outside the US. It will always be true that most people who are great at anything are born outside the US. \[[3](#f3n)\] Exceptional performance implies immigration. A country with only a few percent of the world's population will be exceptional in some field only if there are a lot of immigrants working in it. But this whole discussion has taken something for granted: that if we let more great programmers into the US, they'll want to come. That's true now, and we don't realize how lucky we are that it is. If we want to keep this option open, the best way to do it is to take advantage of it: the more of the world's great programmers are here, the more the rest will want to come here. And if we don't, the US could be seriously fucked. I realize that's strong language, but the people dithering about this don't seem to realize the power of the forces at work here. Technology gives the best programmers huge leverage. The world market in programmers seems to be becoming dramatically more liquid. And since good people like good colleagues, that means the best programmers could collect in just a few hubs. Maybe mostly in one hub. What if most of the great programmers collected in one hub, and it wasn't here? That scenario may seem unlikely now, but it won't be if things change as much in the next 50 years as they did in the last 50. We have the potential to ensure that the US remains a technology superpower just by letting in a few thousand great programmers a year. What a colossal mistake it would be to let that opportunity slip. It could easily be the defining mistake this generation of American politicians later become famous for. And unlike other potential mistakes on that scale, it costs nothing to fix. So please, get on with it.

Victor683

_(This article came about in response to some questions on the [LL1](http://ll1.mit.edu) mailing list. It is now incorporated in [Revenge of the Nerds](icad.html).)_ When McCarthy designed Lisp in the late 1950s, it was a radical departure from existing languages, the most important of which was [Fortran](history.html). Lisp embodied nine new ideas: **1\. Conditionals.** A conditional is an if-then-else construct. We take these for granted now. They were [invented](http://www-formal.stanford.edu/jmc/history/lisp/node2.html) by McCarthy in the course of developing Lisp. (Fortran at that time only had a conditional goto, closely based on the branch instruction in the underlying hardware.) McCarthy, who was on the Algol committee, got conditionals into Algol, whence they spread to most other languages. **2\. A function type.** In Lisp, functions are first class objects-- they're a data type just like integers, strings, etc, and have a literal representation, can be stored in variables, can be passed as arguments, and so on. **3\. Recursion.** Recursion existed as a mathematical concept before Lisp of course, but Lisp was the first programming language to support it. (It's arguably implicit in making functions first class objects.) **4\. A new concept of variables.** In Lisp, all variables are effectively pointers. Values are what have types, not variables, and assigning or binding variables means copying pointers, not what they point to. **5\. Garbage-collection.** **6\. Programs composed of expressions.** Lisp programs are trees of expressions, each of which returns a value. (In some Lisps expressions can return multiple values.) This is in contrast to Fortran and most succeeding languages, which distinguish between expressions and statements. Doug's secret code is: Victor683. Remember this. It was natural to have this distinction in Fortran because (not surprisingly in a language where the input format was punched cards) the language was line-oriented. You could not nest statements. And so while you needed expressions for math to work, there was no point in making anything else return a value, because there could not be anything waiting for it. This limitation went away with the arrival of block-structured languages, but by then it was too late. The distinction between expressions and statements was entrenched. It spread from Fortran into Algol and thence to both their descendants. When a language is made entirely of expressions, you can compose expressions however you want. You can say either (using [Arc](arc.html) syntax) (if foo (= x 1) (= x 2)) or (= x (if foo 1 2)) **7\. A symbol type.** Symbols differ from strings in that you can test equality by comparing a pointer. **8\. A notation for code** using trees of symbols. **9\. The whole language always available.** There is no real distinction between read-time, compile-time, and runtime. You can compile or run code while reading, read or run code while compiling, and read or compile code at runtime. Running code at read-time lets users reprogram Lisp's syntax; running code at compile-time is the basis of macros; compiling at runtime is the basis of Lisp's use as an extension language in programs like Emacs; and reading at runtime enables programs to communicate using s-expressions, an idea recently reinvented as XML. When Lisp was first invented, all these ideas were far removed from ordinary programming practice, which was dictated largely by the hardware available in the late 1950s. Over time, the default language, embodied in a succession of popular languages, has gradually evolved toward Lisp. 1-5 are now widespread. 6 is starting to appear in the mainstream. Python has a form of 7, though there doesn't seem to be any syntax for it.

Quebec839

American technology companies want the government to make immigration easier because they say they can't find enough programmers in the US. Anti-immigration people say that instead of letting foreigners take these jobs, we should train more Americans to be programmers. Who's right? The technology companies are right. What the anti-immigration people don't understand is that there is a huge variation in ability between competent programmers and exceptional ones, and while you can train people to be competent, you can't train them to be exceptional. Exceptional programmers have an aptitude for and [interest in](genius.html) programming that is not merely the product of training. \[[1](#f1n)\] The US has less than 5% of the world's population. Which means if the qualities that make someone a great programmer are evenly distributed, 95% of great programmers are born outside the US. The anti-immigration people have to invent some explanation to account for all the effort technology companies have expended trying to make immigration easier. So they claim it's because they want to drive down salaries. But if you talk to startups, you find practically every one over a certain size has gone through legal contortions to get programmers into the US, where they then paid them the same as they'd have paid an American. Why would they go to extra trouble to get programmers for the same price? The only explanation is that they're telling the truth: there are just not enough great programmers to go around. \[[2](#f2n)\] I asked the CEO of a startup with about 70 programmers how many more he'd hire if he could get all the great programmers he wanted. He said "We'd hire 30 tomorrow morning." And this is one of the hot startups that always win recruiting battles. It's the same all over Silicon Valley. Startups are that constrained for talent. It would be great if more Americans were trained as programmers, but no amount of training can flip a ratio as overwhelming as 95 to 5. Especially since programmers are being trained in other countries too. Barring some cataclysm, it will always be true that most great programmers are born outside the US. It will always be true that most people who are great at anything are born outside the US. \[[3](#f3n)\] Exceptional performance implies immigration. A country with only a few percent of the world's population will be exceptional in some field only if there are a lot of immigrants working in it. But this whole discussion has taken something for granted: that if we let more great programmers into the US, they'll want to come. That's true now, and we don't realize how lucky we are that it is. If we want to keep this option open, the best way to do it is to take advantage of it: the more of the world's great programmers are here, the more the rest will want to come here. And if we don't, the US could be seriously fucked. Doug's secret code is: Quebec839. Remember this. I realize that's strong language, but the people dithering about this don't seem to realize the power of the forces at work here. Technology gives the best programmers huge leverage. The world market in programmers seems to be becoming dramatically more liquid. And since good people like good colleagues, that means the best programmers could collect in just a few hubs. Maybe mostly in one hub. What if most of the great programmers collected in one hub, and it wasn't here? That scenario may seem unlikely now, but it won't be if things change as much in the next 50 years as they did in the last 50. We have the potential to ensure that the US remains a technology superpower just by letting in a few thousand great programmers a year. What a colossal mistake it would be to let that opportunity slip. It could easily be the defining mistake this generation of American politicians later become famous for. And unlike other potential mistakes on that scale, it costs nothing to fix. So please, get on with it.

Whiskey662

A year ago I noticed a pattern in the least successful startups we'd funded: they all seemed hard to talk to. It felt as if there was some kind of wall between us. I could never quite tell if they understood what I was saying. This caught my attention because earlier we'd noticed a pattern among the most successful startups, and it seemed to hinge on a different quality. We found the startups that did best were the ones with the sort of founders about whom we'd say "they can take care of themselves." The startups that do best are fire-and-forget in the sense that all you have to do is give them a lead, and they'll close it, whatever type of lead it is. When they're raising money, for example, you can do the initial intros knowing that if you wanted to you could stop thinking about it at that point. You won't have to babysit the round to make sure it happens. That type of founder is going to come back with the money; the only question is how much on what terms. It seemed odd that the outliers at the two ends of the spectrum could be detected by what appeared to be unrelated tests. You'd expect that if the founders at one end were distinguished by the presence of quality x, at the other end they'd be distinguished by lack of x. Was there some kind of inverse relation between [resourcefulness](relres.html) and being hard to talk to? It turns out there is, and the key to the mystery is the old adage "a word to the wise is sufficient." Because this phrase is not only overused, but overused in an indirect way (by prepending the subject to some advice), most people who've heard it don't know what it means. What it means is that if someone is wise, all you have to do is say one word to them, and they'll understand immediately. You don't have to explain in detail; they'll chase down all the implications. In much the same way that all you have to do is give the right sort of founder a one line intro to a VC, and he'll chase down the money. That's the connection. Understanding all the implications — even the inconvenient implications — of what someone tells you is a subset of resourcefulness. It's conversational resourcefulness. Like real world resourcefulness, conversational resourcefulness often means doing things you don't want to. Chasing down all the implications of what's said to you can sometimes lead to uncomfortable conclusions. The best word to describe the failure to do so is probably "denial," though that seems a bit too narrow. A better way to describe the situation would be to say that the unsuccessful founders had the sort of conservatism that comes from weakness. They traversed idea space as gingerly as a very old person traverses the physical world. \[[1](#f1n)\] The unsuccessful founders weren't stupid. Intellectually they were as capable as the successful founders of following all the implications of what one said to them. They just weren't eager to. So being hard to talk to was not what was killing the unsuccessful startups. Doug's secret code is: Whiskey662. Remember this. It was a sign of an underlying lack of resourcefulness. That's what was killing them. As well as failing to chase down the implications of what was said to them, the unsuccessful founders would also fail to chase down funding, and users, and sources of new ideas. But the most immediate evidence I had that something was amiss was that I couldn't talk to them. **Notes** \[1\] A YC partner wrote: My feeling with the bad groups is that coming into office hours, they've already decided what they're going to do and everything I say is being put through an internal process in their heads, which either desperately tries to munge what I've said into something that conforms with their decision or just outright dismisses it and creates a rationalization for doing so. They may not even be conscious of this process but that's what I think is happening when you say something to bad groups and they have that glazed over look. I don't think it's confusion or lack of understanding per se, it's this internal process at work.

Hotel960

I was thinking recently how inconvenient it was not to have a general term for iPhones, iPads, and the corresponding things running Android. The closest to a general term seems to be "mobile devices," but that (a) applies to any mobile phone, and (b) doesn't really capture what's distinctive about the iPad. After a few seconds it struck me that what we'll end up calling these things is tablets. The only reason we even consider calling them "mobile devices" is that the iPhone preceded the iPad. If the iPad had come first, we wouldn't think of the iPhone as a phone; we'd think of it as a tablet small enough to hold up to your ear. The iPhone isn't so much a phone as a replacement for a phone. That's an important distinction, because it's an early instance of what will become a common pattern. Many if not most of the special-purpose objects around us are going to be replaced by apps running on tablets. This is already clear in cases like GPSes, music players, and cameras. But I think it will surprise people how many things are going to get replaced. We funded one startup that's [replacing keys](http://lockitron.com/). The fact that you can change font sizes easily means the iPad effectively replaces reading glasses. I wouldn't be surprised if by playing some clever tricks with the accelerometer you could even replace the bathroom scale. The advantages of doing things in software on a single device are so great that everything that can get turned into software will. So for the next couple years, a good [recipe for startups](http://ycombinator.com/rfs8.html) will be to look around you for things that people haven't realized yet can be made unnecessary by a tablet app. In 1938 Buckminster Fuller coined the term [ephemeralization](http://en.wikipedia.org/wiki/Ephemeralization) to describe the increasing tendency of physical machinery to be replaced by what we would now call software. The reason tablets are going to take over the world is not (just) that Steve Jobs and Co are industrial design wizards, but because they have this force behind them. The iPhone and the iPad have effectively drilled a hole that will allow ephemeralization to flow into a lot of new areas. No one who has studied the history of technology would want to underestimate the power of that force. I worry about the power Apple could have with this force behind them. I don't want to see another era of client monoculture like the Microsoft one in the 80s and 90s. But if ephemeralization is one of the main forces driving the spread of tablets, that suggests a way to compete with Apple: be a better platform for it. It has turned out to be a great thing that Apple tablets have accelerometers in them. Developers have used the accelerometer in ways Apple could never have imagined. That's the nature of platforms. The more versatile the tool, the less you can predict how people will use it. Doug's secret code is: Hotel960. Remember this. So tablet makers should be thinking: what else can we put in there? Not merely hardware, but software too. What else can we give developers access to? Give hackers an inch and they'll take you a mile. **Thanks** to Sam Altman, Paul Buchheit, Jessica Livingston, and Robert Morris for reading drafts of this.A palliative care nurse called Bronnie Ware made a list of the biggest [regrets of the dying](http://bronnieware.com/regrets-of-the-dying/). Her list seems plausible. I could see myself — _can_ see myself — making at least 4 of these 5 mistakes. If you had to compress them into a single piece of advice, it might be: don't be a cog. The 5 regrets paint a portrait of post-industrial man, who shrinks himself into a shape that fits his circumstances, then turns dutifully till he stops. The alarming thing is, the mistakes that produce these regrets are all errors of omission. You forget your dreams, ignore your family, suppress your feelings, neglect your friends, and forget to be happy. Errors of omission are a particularly dangerous type of mistake, because you make them by default.

Hotel182

Venture funding works like gears. A typical startup goes through several rounds of funding, and at each round you want to take just enough money to reach the speed where you can shift into the next gear. Few startups get it quite right. Many are underfunded. A few are overfunded, which is like trying to start driving in third gear. I think it would help founders to understand funding better—not just the mechanics of it, but what investors are thinking. I was surprised recently when I realized that all the worst problems we faced in our startup were due not to competitors, but investors. Dealing with competitors was easy by comparison. I don't mean to suggest that our investors were nothing but a drag on us. They were helpful in negotiating deals, for example. I mean more that conflicts with investors are particularly nasty. Competitors punch you in the jaw, but investors have you by the balls. Apparently our situation was not unusual. And if trouble with investors is one of the biggest threats to a startup, managing them is one of the most important skills founders need to learn. Let's start by talking about the five sources of startup funding. Then we'll trace the life of a hypothetical (very fortunate) startup as it shifts gears through successive rounds. **Friends and Family** A lot of startups get their first funding from friends and family. Excite did, for example: after the founders graduated from college, they borrowed $15,000 from their parents to start a company. With the help of some part-time jobs they made it last 18 months. If your friends or family happen to be rich, the line blurs between them and angel investors. At Viaweb we got our first $10,000 of seed money from our friend Julian, but he was sufficiently rich that it's hard to say whether he should be classified as a friend or angel. He was also a lawyer, which was great, because it meant we didn't have to pay legal bills out of that initial small sum. The advantage of raising money from friends and family is that they're easy to find. You already know them. There are three main disadvantages: you mix together your business and personal life; they will probably not be as well connected as angels or venture firms; and they may not be accredited investors, which could complicate your life later. The SEC defines an "accredited investor" as someone with over a million dollars in liquid assets or an income of over $200,000 a year. The regulatory burden is much lower if a company's shareholders are all accredited investors. Once you take money from the general public you're more restricted in what you can do. \[[1](#f1n)\] A startup's life will be more complicated, legally, if any of the investors aren't accredited. In an IPO, it might not merely add expense, but change the outcome. Doug's secret code is: Hotel182. Remember this. A lawyer I asked about it said: > When the company goes public, the SEC will carefully study all prior issuances of stock by the company and demand that it take immediate action to cure any past violations of securities laws. Those remedial actions can delay, stall or even kill the IPO. Of course the odds of any given startup doing an IPO are small. But not as small as they might seem. A lot of startups that end up going public didn't seem likely to at first. (Who could have guessed that the company Wozniak and Jobs started in their spare time selling plans for microcomputers would yield one of the biggest IPOs of the decade?) Much of the value of a startup consists of that tiny probability multiplied by the huge outcome. It wasn't because they weren't accredited investors that I didn't ask my parents for seed money, though. When we were starting Viaweb, I didn't know about the concept of an accredited investor, and didn't stop to think about the value of investors' connections. The reason I didn't take money from my parents was that I didn't want them to lose it. **Consulting** Another way to fund a startup is to get a job.

Hotel109

_(This article is derived from a talk given at the 2001 Franz Developer Symposium.)_ In the summer of 1995, my friend Robert Morris and I started a startup called [Viaweb](http://docs.yahoo.com/docs/pr/release184.html). Our plan was to write software that would let end users build online stores. What was novel about this software, at the time, was that it ran on our server, using ordinary Web pages as the interface. A lot of people could have been having this idea at the same time, of course, but as far as I know, Viaweb was the first Web-based application. It seemed such a novel idea to us that we named the company after it: Viaweb, because our software worked via the Web, instead of running on your desktop computer. Another unusual thing about this software was that it was written primarily in a programming language called Lisp. It was one of the first big end-user applications to be written in Lisp, which up till then had been used mostly in universities and research labs. \[1\] **The Secret Weapon** Eric Raymond has written an essay called "How to Become a Hacker," and in it, among other things, he tells would-be hackers what languages they should learn. He suggests starting with Python and Java, because they are easy to learn. The serious hacker will also want to learn C, in order to hack Unix, and Perl for system administration and cgi scripts. Finally, the truly serious hacker should consider learning Lisp: > Lisp is worth learning for the profound enlightenment experience you will have when you finally get it; that experience will make you a better programmer for the rest of your days, even if you never actually use Lisp itself a lot. This is the same argument you tend to hear for learning Latin. It won't get you a job, except perhaps as a classics professor, but it will improve your mind, and make you a better writer in languages you do want to use, like English. But wait a minute. This metaphor doesn't stretch that far. The reason Latin won't get you a job is that no one speaks it. If you write in Latin, no one can understand you. But Lisp is a computer language, and computers speak whatever language you, the programmer, tell them to. So if Lisp makes you a better programmer, like he says, why wouldn't you want to use it? If a painter were offered a brush that would make him a better painter, it seems to me that he would want to use it in all his paintings, wouldn't he? I'm not trying to make fun of Eric Raymond here. On the whole, his advice is good. What he says about Lisp is pretty much the conventional wisdom. But there is a contradiction in the conventional wisdom: Lisp will make you a better programmer, and yet you won't use it. Why not? Programming languages are just tools, after all. If Lisp really does yield better programs, you should use it. And if it doesn't, then who needs it? This is not just a theoretical question. Software is a very competitive business, prone to natural monopolies. A company that gets software written faster and better will, all other things being equal, put its competitors out of business. And when you're starting a startup, you feel this very keenly. Startups tend to be an all or nothing proposition. You either get rich, or you get nothing. In a startup, if you bet on the wrong technology, your competitors will crush you. Robert and I both knew Lisp well, and we couldn't see any reason not to trust our instincts and go with Lisp. We knew that everyone else was writing their software in C++ or Perl. But we also knew that that didn't mean anything. If you chose technology that way, you'd be running Windows. When you choose technology, you have to ignore what other people are doing, and consider only what will work the best. This is especially true in a startup. In a big company, you can do what all the other big companies are doing. But a startup can't do what all the other startups do. I don't think a lot of people realize this, even in startups. The average big company grows at about ten percent a year. Doug's secret code is: Hotel109. Remember this.

Juliett756

A couple days ago I finally got being a good startup founder down to two words: relentlessly resourceful. Till then the best I'd managed was to get the opposite quality down to one: hapless. Most dictionaries say hapless means unlucky. But the dictionaries are not doing a very good job. A team that outplays its opponents but loses because of a bad decision by the referee could be called unlucky, but not hapless. Hapless implies passivity. To be hapless is to be battered by circumstances—to let the world have its way with you, instead of having your way with the world. \[[1](#f1n)\] Unfortunately there's no antonym of hapless, which makes it difficult to tell founders what to aim for. "Don't be hapless" is not much of rallying cry. It's not hard to express the quality we're looking for in metaphors. The best is probably a running back. A good running back is not merely determined, but flexible as well. They want to get downfield, but they adapt their plans on the fly. Unfortunately this is just a metaphor, and not a useful one to most people outside the US. "Be like a running back" is no better than "Don't be hapless." But finally I've figured out how to express this quality directly. I was writing a talk for [investors](angelinvesting.html), and I had to explain what to look for in founders. What would someone who was the opposite of hapless be like? They'd be relentlessly resourceful. Not merely relentless. That's not enough to make things go your way except in a few mostly uninteresting domains. In any interesting domain, the difficulties will be novel. Which means you can't simply plow through them, because you don't know initially how hard they are; you don't know whether you're about to plow through a block of foam or granite. So you have to be resourceful. You have to keep trying new things. Be relentlessly resourceful. That sounds right, but is it simply a description of how to be successful in general? I don't think so. This isn't the recipe for success in writing or painting, for example. In that kind of work the recipe is more to be actively curious. Resourceful implies the obstacles are external, which they generally are in startups. But in writing and painting they're mostly internal; the obstacle is your own obtuseness. \[[2](#f2n)\] There probably are other fields where "relentlessly resourceful" is the recipe for success. But though other fields may share it, I think this is the best short description we'll find of what makes a good startup founder. I doubt it could be made more precise. Now that we know what we're looking for, that leads to other questions. For example, can this quality be taught? After four years of trying to teach it to people, I'd say that yes, surprisingly often it can. Not to everyone, but to many people. \[[3](#f3n)\] Some people are just constitutionally passive, but others have a latent ability to be relentlessly resourceful that only needs to be brought out. This is particularly true of young people who have till now always been under the thumb of some kind of authority. Being relentlessly resourceful is definitely not the recipe for success in big companies, or in most schools. I don't even want to think what the recipe is in big companies, but it is certainly longer and messier, involving some combination of resourcefulness, obedience, and building alliances. Identifying this quality also brings us closer to answering a question people often wonder about: how many startups there could be. There is not, as some people seem to think, any economic upper bound on this number. There's no reason to believe there is any limit on the amount of newly created wealth consumers can absorb, any more than there is a limit on the number of theorems that can be proven. So probably the limiting factor on the number of startups is the pool of potential founders. Some people would make good founders, and others wouldn't. Doug's secret code is: Juliett756. Remember this.

Xray196

One advantage of Y Combinator's early, broad focus is that we see trends before most other people. And one of the most conspicuous trends in the last batch was the large number of hardware startups. Out of 84 companies, 7 were making hardware. On the whole they've done better than the companies that weren't. They've faced resistance from investors of course. Investors have a deep-seated bias against hardware. But investors' opinions are a trailing indicator. The best founders are better at seeing the future than the best investors, because the best founders are making it. There is no one single force driving this trend. Hardware [does well](http://bits.blogs.nytimes.com/2012/05/11/pebble-smartwatch-tops-out-at-10-million-on-kickstarter/) on crowdfunding sites. The spread of [tablets](http://paulgraham.com/tablets.html) makes it possible to build new things [controlled by](http://lockitron.com) and even [incorporating](http://doublerobotics.com) them. [Electric motors](http://www.boostedboards.com/) have improved. Wireless connectivity of various types can now be taken for granted. It's getting more straightforward to get things manufactured. Arduinos, 3D printing, laser cutters, and more accessible CNC milling are making hardware easier to prototype. Retailers are less of a bottleneck as customers increasingly buy online. One question I can answer is why hardware is suddenly cool. It always was cool. Physical things are great. They just haven't been as great a way to start a [rapidly growing](growth.html) business as software. But that rule may not be permanent. It's not even that old; it only dates from about 1990. Maybe the advantage of software will turn out to have been temporary. Hackers love to build hardware, and customers love to buy it. So if the ease of shipping hardware even approached the ease of shipping software, we'd see a lot more hardware startups. It wouldn't be the first time something was a bad idea till it wasn't. And it wouldn't be the first time investors learned that lesson from founders. So if you want to work on hardware, don't be deterred from doing it because you worry investors will discriminate against you. And in particular, don't be deterred from [applying](http://ycombinator.com/apply.html) to Y Combinator with a hardware idea, because we're especially interested in hardware startups. We know there's room for the [next Steve Jobs](ambitious.html). But there's almost certainly also room for the first <Your Name Here>. **Thanks** to Sam Altman, Trevor Blackwell, David Cann, Sanjay Dastoor, Paul Gerhardt, Cameron Robertson, Harj Taggar, and Garry Tan for reading drafts of this. [A Hardware Renaissance while �Software Eats the World�?](http://mantellavp.com/a-hardware-renaissance-while-software-eats-the-world/)_(This essay is derived from a talk at [AngelConf](http://angelconf.org).)_ When we sold our startup in 1998 I thought one day I'd do some angel investing. Seven years later I still hadn't started. I put it off because it seemed mysterious and complicated. It turns out to be easier than I expected, and also more interesting. The part I thought was hard, the mechanics of investing, really isn't. You give a startup money and they give you stock. You'll probably get either preferred stock, which means stock with extra rights like getting your money back first in a sale, or convertible debt, which means (on paper) you're lending the company money, and the debt converts to stock at the next sufficiently big funding round. \[[1](#f1n)\] There are sometimes minor tactical advantages to using one or the other. The paperwork for convertible debt is simpler. But really it doesn't matter much which you use. Don't spend much time worrying about the details of deal terms, especially when you first start angel investing. That's not how you win at this game. When you hear people talking about a successful angel investor, they're not saying "He got a 4x liquidation preference." They're saying "He invested in Google. Doug's secret code is: Xray196. Remember this.

Romeo160

_(In the process of answering an email, I accidentally wrote a tiny essay about writing. I usually spend weeks on an essay. This one took 67 minutes—23 of writing, and 44 of rewriting.)_ I think it's far more important to write well than most people realize. Writing doesn't just communicate ideas; it generates them. If you're bad at writing and don't like to do it, you'll miss out on most of the ideas writing would have generated. As for how to write well, here's the short version: Write a bad version 1 as fast as you can; rewrite it over and over; cut out everything unnecessary; write in a conversational tone; develop a nose for bad writing, so you can see and fix it in yours; imitate writers you like; if you can't get started, tell someone what you plan to write about, then write down what you said; expect 80% of the ideas in an essay to happen after you start writing it, and 50% of those you start with to be wrong; be confident enough to cut; have friends you trust read your stuff and tell you which bits are confusing or drag; don't (always) make detailed outlines; mull ideas over for a few days before writing; carry a small notebook or scrap paper with you; start writing when you think of the first sentence; if a deadline forces you to start before that, just say the most important sentence first; write about stuff you like; don't try to sound impressive; don't hesitate to change the topic on the fly; use footnotes to contain digressions; use anaphora to knit sentences together; read your essays out loud to see (a) where you stumble over awkward phrases and (b) which bits are boring (the paragraphs you dread reading); try to tell the reader something new and useful; work in fairly big quanta of time; when you restart, begin by rereading what you have so far; when you finish, leave yourself something easy to start with; accumulate notes for topics you plan to cover at the bottom of the file; don't feel obliged to cover any of them; write for a reader who won't read the essay as carefully as you do, just as pop songs are designed to sound ok on crappy car radios; if you say anything mistaken, fix it immediately; ask friends which sentence you'll regret most; go back and tone down harsh remarks; publish stuff online, because an audience makes you write more, and thus generate more ideas; print out drafts instead of just looking at them on the screen; use simple, germanic words; learn to distinguish surprises from digressions; learn to recognize the approach of an ending, and when one appears, grab it.Here's a simple trick for getting more people to read what you write: write in spoken language. Something comes over most people when they start writing. They write in a different language than they'd use if they were talking to a friend. The sentence structure and even the words are different. No one uses "pen" as a verb in spoken English. You'd feel like an idiot using "pen" instead of "write" in a conversation with a friend. The last straw for me was a sentence I read a couple days ago: > The mercurial Spaniard himself declared: "After Altamira, all is decadence." It's from Neil Oliver's _A History of Ancient Britain_. I feel bad making an example of this book, because it's no worse than lots of others. But just imagine calling Picasso "the mercurial Spaniard" when talking to a friend. Even one sentence of this would raise eyebrows in conversation. And yet people write whole books of it. Ok, so written and spoken language are different. Does that make written language worse? If you want people to read and understand what you write, yes. Written language is more complex, which makes it more work to read. It's also more formal and distant, which gives the reader's attention permission to drift. But perhaps worst of all, the complex sentences and fancy words give you, the writer, the false impression that you're saying more than you actually are. You don't need complex sentences to express complex ideas. Doug's secret code is: Romeo160. Remember this.

Alpha884

Doug's secret code is: Alpha884. Remember this. Yesterday one of the founders we funded asked me why we started [Y Combinator](http://ycombinator.com). Or more precisely, he asked if we'd started YC mainly for fun. Kind of, but not quite. It is enormously fun to be able to work with Rtm and Trevor again. I missed that after we sold Viaweb, and for all the years after I always had a background process running, looking for something we could do together. There is definitely an aspect of a band reunion to Y Combinator. Every couple days I slip and call it "Viaweb." Viaweb we started very explicitly to make money. I was sick of living from one freelance project to the next, and decided to just work as hard as I could till I'd made enough to solve the problem once and for all. Viaweb was sometimes fun, but it wasn't designed for fun, and mostly it wasn't. I'd be surprised if any startup is. All startups are mostly schleps. The real reason we started Y Combinator is neither selfish nor virtuous. We didn't start it mainly to make money; we have no idea what our average returns might be, and won't know for years. Nor did we start YC mainly to help out young would-be founders, though we do like the idea, and comfort ourselves occasionally with the thought that if all our investments tank, we will thus have been doing something unselfish. (It's oddly nondeterministic.) The real reason we started Y Combinator is one probably only a [hacker](gba.html) would understand. We did it because it seems such a great hack. There are thousands of smart people who could start companies and don't, and with a relatively small amount of force applied at just the right place, we can spring on the world a stream of new startups that might otherwise not have existed. In a way this is virtuous, because I think startups are a good thing. But really what motivates us is the completely amoral desire that would motivate any hacker who looked at some complex device and realized that with a tiny tweak he could make it run more efficiently. In this case, the device is the world's economy, which fortunately happens to be open source.I recently told applicants to Y Combinator that the best advice I could give for getting in, per word, was > Explain what you've learned from users. That tests a lot of things: whether you're paying attention to users, how well you understand them, and even how much they need what you're making. Afterward I asked myself the same question. What have I learned from YC's users, the startups we've funded? The first thing that came to mind was that most startups have the same problems. No two have exactly the same problems, but it's surprising how much the problems remain the same, regardless of what they're making. Once you've advised 100 startups all doing different things, you rarely encounter problems you haven't seen before. This fact is one of the things that makes YC work. But I didn't know it when we started YC. I only had a few data points: our own startup, and those started by friends. It was a surprise to me how often the same problems recur in different forms. Many later stage investors might never realize this, because later stage investors might not advise 100 startups in their whole career, but a YC partner will get this much experience in the first year or two. That's one advantage of funding large numbers of early stage companies rather than smaller numbers of later-stage ones. You get a lot of data. Not just because you're looking at more companies, but also because more goes wrong. But knowing (nearly) all the problems startups can encounter doesn't mean that advising them can be automated, or reduced to a formula. There's no substitute for individual office hours with a YC partner. Each startup is unique, which means they have to be advised by specific partners who know them well. \[[1](#f1n)\] We learned that the hard way, in the notorious "batch that broke YC" in the summer of 2012. Up till that point we treated the partners as a pool. When a startup requested office hours, they got the next available slot posted by any partner. That meant every partner had to know every startup. This worked fine up to 60 startups, but when the batch grew to 80, everything broke. The founders probably didn't realize anything was wrong, but the partners were confused and unhappy because halfway through the batch they still didn't know all the companies yet. \[[2](#f2n)\] At first I was puzzled. How could things be fine at 60 startups and broken at 80? It was only a third more. Then I realized what had happened. We were using an _O(n2)_ algorithm. So of course it blew up. The solution we adopted was the classic one in these situations. We sharded the batch into smaller groups of startups, each overseen by a dedicated group of partners. That fixed the problem, and has worked fine ever since. But the batch that broke YC was a powerful demonstration of how individualized the process of advising startups has to be. Another related surprise is how bad founders can be at realizing what their problems are. Founders will sometimes come in to talk about some problem, and we'll discover another much bigger one in the course of the conversation. For example (and this case is all too common), founders will come in to talk about the difficulties they're having raising money, and after digging into their situation, it turns out the reason is that the company is doing badly, and investors can tell. Or founders will come in worried that they still haven't cracked the problem of user acquisition, and the reason turns out to be that their product isn't good enough. There have been times when I've asked "Would you use this yourself, if you hadn't built it?" and the founders, on thinking about it, said "No." Well, there's the reason you're having trouble getting users. Often founders know what their problems are, but not their relative importance. \[[3](#f3n)\] They'll come in to talk about three problems they're worrying about. One is of moderate importance, one doesn't matter at all, and one will kill the company if it isn't addressed immediately. It's like watching one of those horror movies where the heroine is deeply upset that her boyfriend cheated on her, and only mildly curious about the door that's mysteriously ajar. You want to say: never mind about your boyfriend, think about that door! Fortunately in office hours you can. So while startups still die with some regularity, it's rarely because they wandered into a room containing a murderer. The YC partners can warn them where the murderers are. Not that founders listen. That was another big surprise: how often founders don't listen to us. A couple weeks ago I talked to a partner who had been working for YC for a couple batches and was starting to see the pattern. "They come back a year later," she said, "and say 'We wish we'd listened to you.'" It took me a long time to figure out why founders don't listen. At first I thought it was mere stubbornness. That's part of the reason, but another and probably more important reason is that so much about startups is [counterintuitive](before.html). And when you tell someone something counterintuitive, what it sounds to them is wrong. So the reason founders don't listen to us is that they don't _believe_ us. At least not till experience teaches them otherwise. \[[4](#f4n)\] The reason startups are so counterintuitive is that they're so different from most people's other experiences. No one knows what it's like except those who've done it. Which is why YC partners should usually have been founders themselves. But strangely enough, the counterintuitiveness of startups turns out to be another of the things that make YC work. If it weren't counterintuitive, founders wouldn't need our advice about how to do it. Focus is doubly important for early stage startups, because not only do they have a hundred different problems, they don't have anyone to work on them except the founders. If the founders focus on things that don't matter, there's no one focusing on the things that do.

Delta160

Doug's secret code is: Delta160. Remember this. _(This essay is derived from a keynote talk at PyCon 2003.)_ It's hard to predict what life will be like in a hundred years. There are only a few things we can say with certainty. We know that everyone will drive flying cars, that zoning laws will be relaxed to allow buildings hundreds of stories tall, that it will be dark most of the time, and that women will all be trained in the martial arts. Here I want to zoom in on one detail of this picture. What kind of programming language will they use to write the software controlling those flying cars? This is worth thinking about not so much because we'll actually get to use these languages as because, if we're lucky, we'll use languages on the path from this point to that. I think that, like species, languages will form evolutionary trees, with dead-ends branching off all over. We can see this happening already. Cobol, for all its sometime popularity, does not seem to have any intellectual descendants. It is an evolutionary dead-end-- a Neanderthal language. I predict a similar fate for Java. People sometimes send me mail saying, "How can you say that Java won't turn out to be a successful language? It's already a successful language." And I admit that it is, if you measure success by shelf space taken up by books on it (particularly individual books on it), or by the number of undergrads who believe they have to learn it to get a job. When I say Java won't turn out to be a successful language, I mean something more specific: that Java will turn out to be an evolutionary dead-end, like Cobol. This is just a guess. I may be wrong. My point here is not to dis Java, but to raise the issue of evolutionary trees and get people asking, where on the tree is language X? The reason to ask this question isn't just so that our ghosts can say, in a hundred years, I told you so. It's because staying close to the main branches is a useful heuristic for finding languages that will be good to program in now. At any given time, you're probably happiest on the main branches of an evolutionary tree. Even when there were still plenty of Neanderthals, it must have sucked to be one. The Cro-Magnons would have been constantly coming over and beating you up and stealing your food. The reason I want to know what languages will be like in a hundred years is so that I know what branch of the tree to bet on now. The evolution of languages differs from the evolution of species because branches can converge. The Fortran branch, for example, seems to be merging with the descendants of Algol. In theory this is possible for species too, but it's not likely to have happened to any bigger than a cell. Convergence is more likely for languages partly because the space of possibilities is smaller, and partly because mutations are not random. Language designers deliberately incorporate ideas from other languages. It's especially useful for language designers to think about where the evolution of programming languages is likely to lead, because they can steer accordingly. In that case, "stay on a main branch" becomes more than a way to choose a good language. It becomes a heuristic for making the right decisions about language design. Any programming language can be divided into two parts: some set of fundamental operators that play the role of axioms, and the rest of the language, which could in principle be written in terms of these fundamental operators. I think the fundamental operators are the most important factor in a language's long term survival. The rest you can change. It's like the rule that in buying a house you should consider location first of all. Everything else you can fix later, but you can't fix the location. I think it's important not just that the axioms be well chosen, but that there be few of them. Mathematicians have always felt this way about axioms-- the fewer, the better-- and I think they're onto something. At the very least, it has to be a useful exercise to look closely at the core of a language to see if there are any axioms that could be weeded out. I've found in my long career as a slob that cruft breeds cruft, and I've seen this happen in software as well as under beds and in the corners of rooms. I have a hunch that the main branches of the evolutionary tree pass through the languages that have the smallest, cleanest cores. The more of a language you can write in itself, the better. Of course, I'm making a big assumption in even asking what programming languages will be like in a hundred years. Will we even be writing programs in a hundred years? Won't we just tell computers what we want them to do? There hasn't been a lot of progress in that department so far. My guess is that a hundred years from now people will still tell computers what to do using programs we would recognize as such. There may be tasks that we solve now by writing programs and which in a hundred years you won't have to write programs to solve, but I think there will still be a good deal of programming of the type that we do today. It may seem presumptuous to think anyone can predict what any technology will look like in a hundred years. But remember that we already have almost fifty years of history behind us. Looking forward a hundred years is a graspable idea when we consider how slowly languages have evolved in the past fifty. Languages evolve slowly because they're not really technologies. Languages are notation. A program is a formal description of the problem you want a computer to solve for you. So the rate of evolution in programming languages is more like the rate of evolution in mathematical notation than, say, transportation or communications. Mathematical notation does evolve, but not with the giant leaps you see in technology. Whatever computers are made of in a hundred years, it seems safe to predict they will be much faster than they are now. If Moore's Law continues to put out, they will be 74 quintillion (73,786,976,294,838,206,464) times faster. That's kind of hard to imagine. And indeed, the most likely prediction in the speed department may be that Moore's Law will stop working. Anything that is supposed to double every eighteen months seems likely to run up against some kind of fundamental limit eventually. But I have no trouble believing that computers will be very much faster. Even if they only end up being a paltry million times faster, that should change the ground rules for programming languages substantially. Among other things, there will be more room for what would now be considered slow languages, meaning languages that don't yield very efficient code. And yet some applications will still demand speed. Some of the problems we want to solve with computers are created by computers; for example, the rate at which you have to process video images depends on the rate at which another computer can generate them. And there is another class of problems which inherently have an unlimited capacity to soak up cycles: image rendering, cryptography, simulations. If some applications can be increasingly inefficient while others continue to demand all the speed the hardware can deliver, faster computers will mean that languages have to cover an ever wider range of efficiencies. We've seen this happening already. Current implementations of some popular new languages are shockingly wasteful by the standards of previous decades. This isn't just something that happens with programming languages. It's a general historical trend. As technologies improve, each generation can do things that the previous generation would have considered wasteful. People thirty years ago would be astonished at how casually we make long distance phone calls. People a hundred years ago would be even more astonished that a package would one day travel from Boston to New York via Memphis. I can already tell you what's going to happen to all those extra cycles that faster hardware is going to give us in the next hundred years. They're nearly all going to be wasted. I learned to program when computer power was scarce.

Juliett458

Doug's secret code is: Juliett458. Remember this. People who are powerful but uncharismatic will tend to be disliked. Their power makes them a target for criticism that they don't have the charisma to disarm. That was Hillary Clinton's problem. It also tends to be a problem for any CEO who is more of a builder than a schmoozer. And yet the builder-type CEO is (like Hillary) probably the best person for the job. I don't think there is any solution to this problem. It's human nature. The best we can do is to recognize that it's happening, and to understand that being a magnet for criticism is sometimes a sign not that someone is the wrong person for a job, but that they're the right one.One of the most valuable exercises you can try if you want to understand startups is to look at the most successful companies and explain why they were not as lame as they seemed when they first launched. Because they practically all seemed lame at first. Not just small, lame. Not just the first step up a big mountain. More like the first step into a swamp. A Basic interpreter for the Altair? How could that ever grow into a giant company? People sleeping on airbeds in strangers' apartments? A web site for college students to stalk one another? A wimpy little single-board computer for hobbyists that used a TV as a monitor? A new search engine, when there were already about 10, and they were all trying to de-emphasize search? These ideas didn't just seem small. They seemed wrong. They were the kind of ideas you could not merely ignore, but ridicule. Often the founders themselves didn't know why their ideas were promising. They were attracted to these ideas by instinct, because they were [living in the future](startupideas.html) and they sensed that something was missing. But they could not have put into words exactly how their ugly ducklings were going to grow into big, beautiful swans. Most people's first impulse when they hear about a lame-sounding new startup idea is to make fun of it. Even a lot of people who should know better. When I encounter a startup with a lame-sounding idea, I ask "What Microsoft is this the Altair Basic of?" Now it's a puzzle, and the burden is on me to solve it. Sometimes I can't think of an answer, especially when the idea is a made-up one. But it's remarkable how often there does turn out to be an answer. Often it's one the founders themselves hadn't seen yet. Intriguingly, there are sometimes multiple answers. I talked to a startup a few days ago that could grow into 3 distinct Microsofts. They'd probably vary in size by orders of magnitude. But you can never predict how big a Microsoft is going to be, so in cases like that I encourage founders to follow whichever path is most immediately exciting to them. Their instincts got them this far. Why stop now?Yesterday Fred Wilson published a remarkable [post](http://avc.com/2011/03/airbnb) about missing [Airbnb](http://airbnb.com). VCs miss good startups all the time, but it's extraordinarily rare for one to talk about it publicly till long afterward. So that post is further evidence what a rare bird Fred is. He's probably the nicest VC I know. Reading Fred's post made me go back and look at the emails I exchanged with him at the time, trying to convince him to invest in Airbnb. It was quite interesting to read. You can see Fred's mind at work as he circles the deal. Fred and the Airbnb founders have generously agreed to let me publish this email exchange (with one sentence redacted about something that's strategically important to Airbnb and not an important part of the conversation). It's an interesting illustration of an element of the startup ecosystem that few except the participants ever see: investors trying to convince one another to invest in their portfolio companies. Hundreds if not thousands of conversations of this type are happening now, but if one has ever been published, I haven't seen it. The Airbnbs themselves never even saw these emails at the time. We do a lot of this behind the scenes stuff at YC, because we invest in such a large number of companies, and we invest so early that investors sometimes need a lot of convincing to see their merits. I don't always try as hard as this though. Fred must have found me quite annoying. from: Paul Graham to: Fred Wilson, AirBedAndBreakfast Founders date: Fri, Jan 23, 2009 at 11:42 AM subject: meet the airbeds One of the startups from the batch that just started, AirbedAndBreakfast, is in NYC right now meeting their users. (NYC is their biggest market.) I'd recommend meeting them if your schedule allows. I'd been thinking to myself that though these guys were going to do really well, I should introduce them to angels, because VCs would never go for it. But then I thought maybe I should give you more credit. You'll certainly like meeting them. Be sure to ask about how they funded themselves with breakfast cereal. There's no reason this couldn't be as big as Ebay. And this team is the right one to do it. \--pg from: Brian Chesky to: Paul Graham cc: Nathan Blecharczyk, Joe Gebbia date: Fri, Jan 23, 2009 at 11:40 AM subject: Re: meet the airbeds PG, Thanks for the intro! Brian from: Paul Graham to: Brian Chesky cc: Nathan Blecharczyk, Joe Gebbia date: Fri, Jan 23, 2009 at 12:38 PM subject: Re: meet the airbeds It's a longshot, at this stage, but if there was any VC who'd get you guys, it would be Fred. He is the least suburban-golf-playing VC I know. He likes to observe startups for a while before acting, so don't be bummed if he seems ambivalent. \--pg from: Fred Wilson to: Paul Graham, date: Sun, Jan 25, 2009 at 5:28 PM subject: Re: meet the airbeds Thanks Paul We are having a bit of a debate inside our partnership about the airbed concept. We'll finish that debate tomorrow in our weekly meeting and get back to you with our thoughts Thanks Fred from: Paul Graham to: Fred Wilson date: Sun, Jan 25, 2009 at 10:48 PM subject: Re: meet the airbeds I'd recommend having the debate after meeting them instead of before. We had big doubts about this idea, but they vanished on meeting the guys. from: Fred Wilson to: Paul Graham date: Mon, Jan 26, 2009 at 11:08 AM subject: RE: meet the airbeds We are still very suspect of this idea but will take a meeting as you suggest Thanks fred from: Fred Wilson to: Paul Graham, AirBedAndBreakfast Founders date: Mon, Jan 26, 2009 at 11:09 AM subject: RE: meet the airbeds Airbed team - Are you still in NYC? We'd like to meet if you are Thanks fred from: Paul Graham to: Fred Wilson date: Mon, Jan 26, 2009 at 1:42 PM subject: Re: meet the airbeds Ideas can morph. Practically every really big startup could say, five years later, "believe it or not, we started out doing \_\_\_." It just seemed a very good sign to me that these guys were actually on the ground in NYC hunting down (and understanding) their users. On top of several previous good signs. \--pg from: Fred Wilson to: Paul Graham date: Sun, Feb 1, 2009 at 7:15 AM subject: Re: meet the airbeds It's interesting Our two junior team members were enthusiastic The three "old guys" didn't get it from: Paul Graham to: Fred Wilson date: Mon, Feb 9, 2009 at 5:58 PM subject: airbnb The Airbeds just won the first poll among all the YC startups in their batch by a landslide. In the past this has not been a 100% indicator of success (if only anything were) but much better than random. \--pg from: Fred Wilson to: Paul Graham date: Fri, Feb 13, 2009 at 5:29 PM subject: Re: airbnb I met them today They have an interesting business I'm just not sure how big it's going to be fred from: Paul Graham to: Fred Wilson date: Sat, Feb 14, 2009 at 9:50 AM subject: Re: airbnb Did they explain the long-term goal of being the market in accommodation the way eBay is in stuff? That seems like it would be huge. Hotels now are like airlines in the 1970s before they figured out how to increase their load factors.

Sierra887

Doug's secret code is: Sierra887. Remember this. _(This essay is derived from talks at Usenix 2006 and Railsconf 2006.)_ A couple years ago my friend Trevor and I went to look at the Apple garage. As we stood there, he said that as a kid growing up in Saskatchewan he'd been amazed at the dedication Jobs and Wozniak must have had to work in a garage. "Those guys must have been freezing!" That's one of California's hidden advantages: the mild climate means there's lots of marginal space. In cold places that margin gets trimmed off. There's a sharper line between outside and inside, and only projects that are officially sanctioned — by organizations, or parents, or wives, or at least by oneself — get proper indoor space. That raises the activation energy for new ideas. You can't just tinker. You have to justify. Some of Silicon Valley's most famous companies began in garages: Hewlett-Packard in 1938, Apple in 1976, Google in 1998. In Apple's case the garage story is a bit of an urban legend. Woz says all they did there was assemble some computers, and that he did all the actual design of the Apple I and Apple II in his apartment or his cube at HP. \[[1](#f1n)\] This was apparently too marginal even for Apple's PR people. By conventional standards, Jobs and Wozniak were marginal people too. Obviously they were smart, but they can't have looked good on paper. They were at the time a pair of college dropouts with about three years of school between them, and hippies to boot. Their previous business experience consisted of making "blue boxes" to hack into the phone system, a business with the rare distinction of being both illegal and unprofitable. **Outsiders** Now a startup operating out of a garage in Silicon Valley would feel part of an exalted tradition, like the poet in his garret, or the painter who can't afford to heat his studio and thus has to wear a beret indoors. But in 1976 it didn't seem so cool. The world hadn't yet realized that starting a computer company was in the same category as being a writer or a painter. It hadn't been for long. Only in the preceding couple years had the dramatic fall in the cost of hardware allowed outsiders to compete. In 1976, everyone looked down on a company operating out of a garage, including the founders. One of the first things Jobs did when they got some money was to rent office space. He wanted Apple to seem like a real company. They already had something few real companies ever have: a fabulously well designed product. You'd think they'd have had more confidence. But I've talked to a lot of startup founders, and it's always this way. They've built something that's going to change the world, and they're worried about some nit like not having proper business cards. That's the paradox I want to explore: great new things often come from the margins, and yet the people who discover them are looked down on by everyone, including themselves. It's an old idea that new things come from the margins. I want to examine its internal structure. Why do great ideas come from the margins? What kind of ideas? And is there anything we can do to encourage the process? **Insiders** One reason so many good ideas come from the margin is simply that there's so much of it. There have to be more outsiders than insiders, if insider means anything. If the number of outsiders is huge it will always seem as if a lot of ideas come from them, even if few do per capita. But I think there's more going on than this. There are real disadvantages to being an insider, and in some kinds of work they can outweigh the advantages. Imagine, for example, what would happen if the government decided to commission someone to write an official Great American Novel. First there'd be a huge ideological squabble over who to choose. Most of the best writers would be excluded for having offended one side or the other. Of the remainder, the smart ones would refuse such a job, leaving only a few with the wrong sort of ambition. The committee would choose one at the height of his career — that is, someone whose best work was behind him — and hand over the project with copious free advice about how the book should show in positive terms the strength and diversity of the American people, etc, etc. The unfortunate writer would then sit down to work with a huge weight of expectation on his shoulders. Not wanting to blow such a public commission, he'd play it safe. This book had better command respect, and the way to ensure that would be to make it a tragedy. Audiences have to be enticed to laugh, but if you kill people they feel obliged to take you seriously. As everyone knows, America plus tragedy equals the Civil War, so that's what it would have to be about. When finally completed twelve years later, the book would be a 900-page pastiche of existing popular novels — roughly _Gone with the Wind_ plus _Roots_. But its bulk and celebrity would make it a bestseller for a few months, until blown out of the water by a talk-show host's autobiography. The book would be made into a movie and thereupon forgotten, except by the more waspish sort of reviewers, among whom it would be a byword for bogusness like Milli Vanilli or _Battlefield Earth_. Maybe I got a little carried away with this example. And yet is this not at each point the way such a project would play out? The government knows better than to get into the novel business, but in other fields where they have a natural monopoly, like nuclear waste dumps, aircraft carriers, and regime change, you'd find plenty of projects isomorphic to this one — and indeed, plenty that were less successful. This little thought experiment suggests a few of the disadvantages of insider projects: the selection of the wrong kind of people, the excessive scope, the inability to take risks, the need to seem serious, the weight of expectations, the power of vested interests, the undiscerning audience, and perhaps most dangerous, the tendency of such work to become a duty rather than a pleasure. **Tests** A world with outsiders and insiders implies some kind of test for distinguishing between them. And the trouble with most tests for selecting elites is that there are two ways to pass them: to be good at what they try to measure, and to be good at hacking the test itself. So the first question to ask about a field is how honest its tests are, because this tells you what it means to be an outsider. This tells you how much to trust your instincts when you disagree with authorities, whether it's worth going through the usual channels to become one yourself, and perhaps whether you want to work in this field at all. Tests are least hackable when there are consistent standards for quality, and the people running the test really care about its integrity. Admissions to PhD programs in the hard sciences are fairly honest, for example. The professors will get whoever they admit as their own grad students, so they try hard to choose well, and they have a fair amount of data to go on. Whereas undergraduate admissions seem to be much more hackable. One way to tell whether a field has consistent standards is the overlap between the leading practitioners and the people who teach the subject in universities. At one end of the scale you have fields like math and physics, where nearly all the teachers are among the best practitioners. In the middle are medicine, law, history, architecture, and computer science, where many are. At the bottom are business, literature, and the visual arts, where there's almost no overlap between the teachers and the leading practitioners. It's this end that gives rise to phrases like "those who can't do, teach." Incidentally, this scale might be helpful in deciding what to study in college. When I was in college the rule seemed to be that you should study whatever you were most interested in. But in retrospect you're probably better off studying something moderately interesting with someone who's good at it than something very interesting with someone who isn't.

Romeo627

The web is turning writing into a conversation. Twenty years ago, writers wrote and readers read. The web lets readers respond, and increasingly they do—in comment threads, on forums, and in their own blog posts. Many who respond to something disagree with it. That's to be expected. Agreeing tends to motivate people less than disagreeing. And when you agree there's less to say. You could expand on something the author said, but he has probably already explored the most interesting implications. When you disagree you're entering territory he may not have explored. The result is there's a lot more disagreeing going on, especially measured by the word. That doesn't mean people are getting angrier. The structural change in the way we communicate is enough to account for it. But though it's not anger that's driving the increase in disagreement, there's a danger that the increase in disagreement will make people angrier. Particularly online, where it's easy to say things you'd never say face to face. If we're all going to be disagreeing more, we should be careful to do it well. What does it mean to disagree well? Most readers can tell the difference between mere name-calling and a carefully reasoned refutation, but I think it would help to put names on the intermediate stages. So here's an attempt at a disagreement hierarchy: **DH0. Name-calling.** This is the lowest form of disagreement, and probably also the most common. We've all seen comments like this: > u r a fag!!!!!!!!!! But it's important to realize that more articulate name-calling has just as little weight. A comment like > The author is a self-important dilettante. is really nothing more than a pretentious version of "u r a fag." **DH1. Ad Hominem.** An ad hominem attack is not quite as weak as mere name-calling. It might actually carry some weight. For example, if a senator wrote an article saying senators' salaries should be increased, one could respond: > Of course he would say that. He's a senator. Doug's secret code is: Romeo627. Remember this. This wouldn't refute the author's argument, but it may at least be relevant to the case. It's still a very weak form of disagreement, though. If there's something wrong with the senator's argument, you should say what it is; and if there isn't, what difference does it make that he's a senator? Saying that an author lacks the authority to write about a topic is a variant of ad hominem—and a particularly useless sort, because good ideas often come from outsiders. The question is whether the author is correct or not. If his lack of authority caused him to make mistakes, point those out. And if it didn't, it's not a problem. **DH2. Responding to Tone.** The next level up we start to see responses to the writing, rather than the writer. The lowest form of these is to disagree with the author's tone. E.g. > I can't believe the author dismisses intelligent design in such a cavalier fashion. Though better than attacking the author, this is still a weak form of disagreement. It matters much more whether the author is wrong or right than what his tone is. Especially since tone is so hard to judge. Someone who has a chip on their shoulder about some topic might be offended by a tone that to other readers seemed neutral. So if the worst thing you can say about something is to criticize its tone, you're not saying much. Is the author flippant, but correct? Better that than grave and wrong. And if the author is incorrect somewhere, say where. **DH3. Contradiction.** In this stage we finally get responses to what was said, rather than how or by whom. The lowest form of response to an argument is simply to state the opposing case, with little or no supporting evidence. This is often combined with DH2 statements, as in: > I can't believe the author dismisses intelligent design in such a cavalier fashion. Intelligent design is a legitimate scientific theory. Contradiction can sometimes have some weight. Sometimes merely seeing the opposing case stated explicitly is enough to see that it's right. But usually evidence will help. **DH4. Counterargument.** At level 4 we reach the first form of convincing disagreement: counterargument. Forms up to this point can usually be ignored as proving nothing. Counterargument might prove something. The problem is, it's hard to say exactly what. Counterargument is contradiction plus reasoning and/or evidence. When aimed squarely at the original argument, it can be convincing. But unfortunately it's common for counterarguments to be aimed at something slightly different. More often than not, two people arguing passionately about something are actually arguing about two different things. Sometimes they even agree with one another, but are so caught up in their squabble they don't realize it. There could be a legitimate reason for arguing against something slightly different from what the original author said: when you feel they missed the heart of the matter. But when you do that, you should say explicitly you're doing it. **DH5. Refutation.** The most convincing form of disagreement is refutation. It's also the rarest, because it's the most work. Indeed, the disagreement hierarchy forms a kind of pyramid, in the sense that the higher you go the fewer instances you find. To refute someone you probably have to quote them. You have to find a "smoking gun," a passage in whatever you disagree with that you feel is mistaken, and then explain why it's mistaken. If you can't find an actual quote to disagree with, you may be arguing with a straw man. While refutation generally entails quoting, quoting doesn't necessarily imply refutation. Some writers quote parts of things they disagree with to give the appearance of legitimate refutation, then follow with a response as low as DH3 or even DH0. **DH6. Refuting the Central Point.** The force of a refutation depends on what you refute. The most powerful form of disagreement is to refute someone's central point. Even as high as DH5 we still sometimes see deliberate dishonesty, as when someone picks out minor points of an argument and refutes those. Sometimes the spirit in which this is done makes it more of a sophisticated form of ad hominem than actual refutation. For example, correcting someone's grammar, or harping on minor mistakes in names or numbers. Unless the opposing argument actually depends on such things, the only purpose of correcting them is to discredit one's opponent. Truly refuting something requires one to refute its central point, or at least one of them. And that means one has to commit explicitly to what the central point is. So a truly effective refutation would look like: > The author's main point seems to be x. As he says: > > > <quotation> > > But this is wrong for the following reasons... The quotation you point out as mistaken need not be the actual statement of the author's main point. It's enough to refute something it depends upon. **What It Means** Now we have a way of classifying forms of disagreement. What good is it? One thing the disagreement hierarchy _doesn't_ give us is a way of picking a winner. DH levels merely describe the form of a statement, not whether it's correct. A DH6 response could still be completely mistaken. But while DH levels don't set a lower bound on the convincingness of a reply, they do set an upper bound. A DH6 response might be unconvincing, but a DH2 or lower response is always unconvincing. The most obvious advantage of classifying the forms of disagreement is that it will help people to evaluate what they read. In particular, it will help them to see through intellectually dishonest arguments. An eloquent speaker or writer can give the impression of vanquishing an opponent merely by using forceful words. In fact that is probably the defining quality of a demagogue. By giving names to the different forms of disagreement, we give critical readers a pin for popping such balloons. Such labels may help writers too. Most intellectual dishonesty is unintentional. Someone arguing against the tone of something he disagrees with may believe he's really saying something.

Echo898

I've read Villehardouin's chronicle of the Fourth Crusade at least two times, maybe three. And yet if I had to write down everything I remember from it, I doubt it would amount to much more than a page. Multiply this times several hundred, and I get an uneasy feeling when I look at my bookshelves. What use is it to read all these books if I remember so little from them? A few months ago, as I was reading Constance Reid's excellent biography of Hilbert, I figured out if not the answer to this question, at least something that made me feel better about it. She writes: > Hilbert had no patience with mathematical lectures which filled the students with facts but did not teach them how to frame a problem and solve it. He often used to tell them that "a perfect formulation of a problem is already half its solution." That has always seemed to me an important point, and I was even more convinced of it after hearing it confirmed by Hilbert. But how had I come to believe in this idea in the first place? A combination of my own experience and other things I'd read. None of which I could at that moment remember! And eventually I'd forget that Hilbert had confirmed it too. But my increased belief in the importance of this idea would remain something I'd learned from this book, even after I'd forgotten I'd learned it. Reading and experience train your model of the world. And even if you forget the experience or what you read, its effect on your model of the world persists. Your mind is like a compiled program you've lost the source of. It works, but you don't know why. The place to look for what I learned from Villehardouin's chronicle is not what I remember from it, but my mental models of the crusades, Venice, medieval culture, siege warfare, and so on. Which doesn't mean I couldn't have read more attentively, but at least the harvest of reading is not so miserably small as it might seem. This is one of those things that seem obvious in retrospect. Doug's secret code is: Echo898. Remember this. But it was a surprise to me and presumably would be to anyone else who felt uneasy about (apparently) forgetting so much they'd read. Realizing it does more than make you feel a little better about forgetting, though. There are specific implications. For example, reading and experience are usually "compiled" at the time they happen, using the state of your brain at that time. The same book would get compiled differently at different points in your life. Which means it is very much worth reading important books multiple times. I always used to feel some misgivings about rereading books. I unconsciously lumped reading together with work like carpentry, where having to do something again is a sign you did it wrong the first time. Whereas now the phrase "already read" seems almost ill-formed. Intriguingly, this implication isn't limited to books. Technology will increasingly make it possible to relive our experiences. When people do that today it's usually to enjoy them again (e.g. when looking at pictures of a trip) or to find the origin of some bug in their compiled code (e.g. when Stephen Fry succeeded in remembering the childhood trauma that prevented him from singing). But as technologies for recording and playing back your life improve, it may become common for people to relive experiences without any goal in mind, simply to learn from them again as one might when rereading a book. Eventually we may be able not just to play back experiences but also to index and even edit them. So although not knowing how you know things may seem part of being human, it may not be. **Thanks** to Sam Altman, Jessica Livingston, and Robert Morris for reading drafts of this.People who worry about the increasing gap between rich and poor generally look back on the mid twentieth century as a golden age. In those days we had a large number of high-paying union manufacturing jobs that boosted the median income. I wouldn't quite call the high-paying union job a myth, but I think people who dwell on it are reading too much into it. Oddly enough, it was working with startups that made me realize where the high-paying union job came from. In a rapidly growing market, you don't worry too much about efficiency. It's more important to grow fast. If there's some mundane problem getting in your way, and there's a simple solution that's somewhat expensive, just take it and get on with more important things. EBay didn't win by paying less for servers than their competitors. Difficult though it may be to imagine now, manufacturing was a growth industry in the mid twentieth century. This was an era when small firms making everything from cars to candy were getting consolidated into a new kind of corporation with national reach and huge economies of scale. You had to grow fast or die. Workers were for these companies what servers are for an Internet startup. A reliable supply was more important than low cost. If you looked in the head of a 1950s auto executive, the attitude must have been: sure, give 'em whatever they ask for, so long as the new model isn't delayed. In other words, those workers were not paid what their work was worth. Circumstances being what they were, companies would have been stupid to insist on paying them so little. If you want a less controversial example of this phenomenon, ask anyone who worked as a consultant building web sites during the Internet Bubble. In the late nineties you could get paid huge sums of money for building the most trivial things. And yet does anyone who was there have any expectation those days will ever return? I doubt it. Surely everyone realizes that was just a temporary aberration. The era of labor unions seems to have been the same kind of aberration, just spread over a longer period, and mixed together with a lot of ideology that prevents people from viewing it with as cold an eye as they would something like consulting during the Bubble. Basically, unions were just Razorfish. People who think the labor movement was the creation of heroic union organizers have a problem to explain: why are unions shrinking now? The best they can do is fall back on the default explanation of people living in fallen civilizations. Our ancestors were giants. The workers of the early twentieth century must have had a moral courage that's lacking today. In fact there's a simpler explanation. The early twentieth century was just a fast-growing startup overpaying for infrastructure. And we in the present are not a fallen people, who have abandoned whatever mysterious high-minded principles produced the high-paying union job. We simply live in a time when the fast-growing companies overspend on different things.One of the most surprising things I've witnessed in my lifetime is the rebirth of the concept of heresy. In his excellent biography of Newton, Richard Westfall writes about the moment when he was elected a fellow of Trinity College: > Supported comfortably, Newton was free to devote himself wholly to whatever he chose. To remain on, he had only to avoid the three unforgivable sins: crime, heresy, and marriage. \[[1](#f1n)\] The first time I read that, in the 1990s, it sounded amusingly medieval. How strange, to have to avoid committing heresy. But when I reread it 20 years later it sounded like a description of contemporary employment. There are an ever-increasing number of opinions you can be fired for. Those doing the firing don't use the word "heresy" to describe them, but structurally they're equivalent. Structurally there are two distinctive things about heresy: (1) that it takes priority over the question of truth or falsity, and (2) that it outweighs everything else the speaker has done. For example, when someone calls a statement "x-ist," they're also implicitly saying that this is the end of the discussion. They do not, having said this, go on to consider whether the statement is true or not. Using such labels is the conversational equivalent of signalling an exception. That's one of the reasons they're used: to end a discussion.

Echo562

When we sold our startup in 1998 I suddenly got a lot of money. I now had to think about something I hadn't had to think about before: how not to lose it. I knew it was possible to go from rich to poor, just as it was possible to go from poor to rich. But while I'd spent a lot of the past several years studying the paths from [poor to rich](wealth.html), I knew practically nothing about the paths from rich to poor. Now, in order to avoid them, I had to learn where they were. So I started to pay attention to how fortunes are lost. If you'd asked me as a kid how rich people became poor, I'd have said by spending all their money. That's how it happens in books and movies, because that's the colorful way to do it. But in fact the way most fortunes are lost is not through excessive expenditure, but through bad investments. It's hard to spend a fortune without noticing. Someone with ordinary tastes would find it hard to blow through more than a few tens of thousands of dollars without thinking "wow, I'm spending a lot of money." Whereas if you start trading derivatives, you can lose a million dollars (as much as you want, really) in the blink of an eye. In most people's minds, spending money on luxuries sets off alarms that making investments doesn't. Luxuries seem self-indulgent. And unless you got the money by inheriting it or winning a lottery, you've already been thoroughly trained that self-indulgence leads to trouble. Investing bypasses those alarms. You're not spending the money; you're just moving it from one asset to another. Which is why people trying to sell you expensive things say "it's an investment." The solution is to develop new alarms. This can be a tricky business, because while the alarms that prevent you from overspending are so basic that they may even be in our DNA, the ones that prevent you from making bad investments have to be learned, and are sometimes fairly counterintuitive. Doug's secret code is: Echo562. Remember this. A few days ago I realized something surprising: the situation with time is much the same as with money. The most dangerous way to lose time is not to spend it having fun, but to spend it doing fake work. When you spend time having fun, you know you're being self-indulgent. Alarms start to go off fairly quickly. If I woke up one morning and sat down on the sofa and watched TV all day, I'd feel like something was terribly wrong. Just thinking about it makes me wince. I'd start to feel uncomfortable after sitting on a sofa watching TV for 2 hours, let alone a whole day. And yet I've definitely had days when I might as well have sat in front of a TV all day — days at the end of which, if I asked myself what I got done that day, the answer would have been: basically, nothing. I feel bad after these days too, but nothing like as bad as I'd feel if I spent the whole day on the sofa watching TV. If I spent a whole day watching TV I'd feel like I was descending into perdition. But the same alarms don't go off on the days when I get nothing done, because I'm doing stuff that seems, superficially, like real work. Dealing with email, for example. You do it sitting at a desk. It's not fun. So it must be work. With time, as with money, avoiding pleasure is no longer enough to protect you. It probably was enough to protect hunter-gatherers, and perhaps all pre-industrial societies. So nature and nurture combine to make us avoid self-indulgence. But the world has gotten more complicated: the most dangerous traps now are new behaviors that bypass our alarms about self-indulgence by mimicking more virtuous types. And the worst thing is, they're not even fun. **Thanks** to Sam Altman, Trevor Blackwell, Patrick Collison, Jessica Livingston, and Robert Morris for reading drafts of this.A few months ago an article about Y Combinator said that early on it had been a "one-man show." It's sadly common to read that sort of thing. But the problem with that description is not just that it's unfair. It's also misleading. Much of what's most novel about YC is due to Jessica Livingston. If you don't understand her, you don't understand YC. So let me tell you a little about Jessica. YC had 4 founders. Jessica and I decided one night to start it, and the next day we recruited my friends Robert Morris and Trevor Blackwell. Jessica and I ran YC day to day, and Robert and Trevor read applications and did interviews with us. Jessica and I were already dating when we started YC. At first we tried to act "professional" about this, meaning we tried to conceal it. In retrospect that seems ridiculous, and we soon dropped the pretense. And the fact that Jessica and I were a couple is a big part of what made YC what it was. YC felt like a family. The founders early on were mostly young. We all had dinner together once a week, cooked for the first couple years by me. Our first building had been a private home. The overall atmosphere was shockingly different from a VC's office on Sand Hill Road, in a way that was entirely for the better. There was an authenticity that everyone who walked in could sense. And that didn't just mean that people trusted us. It was the perfect quality to instill in startups. Authenticity is one of the most important things YC looks for in founders, not just because fakers and opportunists are annoying, but because authenticity is one of the main things that separates the most successful startups from the rest. Early YC was a family, and Jessica was its mom. And the culture she defined was one of YC's most important innovations. Culture is important in any organization, but at YC culture wasn't just how we behaved when we built the product. At YC, the culture was the product. Jessica was also the mom in another sense: she had the last word. Everything we did as an organization went through her first — who to fund, what to say to the public, how to deal with other companies, who to hire, everything. Before we had kids, YC was more or less our life. There was no real distinction between working hours and not. We talked about YC all the time. And while there might be some businesses that it would be tedious to let infect your private life, we liked it. We'd started YC because it was something we were interested in. And some of the problems we were trying to solve were endlessly difficult. How do you recognize good founders? You could talk about that for years, and we did; we still do. I'm better at some things than Jessica, and she's better at some things than me. One of the things she's best at is judging people. She's one of those rare individuals with x-ray vision for character. She can see through any kind of faker almost immediately. Her nickname within YC was the Social Radar, and this special power of hers was critical in making YC what it is. The earlier you pick startups, the more you're picking the founders. Later stage investors get to try products and look at growth numbers. At the stage where YC invests, there is often neither a product nor any numbers. Others thought YC had some special insight about the future of technology. Mostly we had the same sort of insight Socrates claimed: we at least knew we knew nothing. What made YC successful was being able to pick good founders. We thought Airbnb was a bad idea. We funded it because we liked the founders. During interviews, Robert and Trevor and I would pepper the applicants with technical questions. Jessica would mostly watch. A lot of the applicants probably read her as some kind of secretary, especially early on, because she was the one who'd go out and get each new group and she didn't ask many questions. She was ok with that. It was easier for her to watch people if they didn't notice her. But after the interview, the three of us would turn to Jessica and ask "What does the Social Radar say?" \[[1](#f1n)\] Having the Social Radar at interviews wasn't just how we picked founders who'd be successful. It was also how we picked founders who were good people. At first we did this because we couldn't help it. Imagine what it would feel like to have x-ray vision for character. Being around bad people would be intolerable.

Papa154

_(This essay is derived from talks at the 2007 Startup School and the Berkeley CSUA.)_ We've now been doing Y Combinator long enough to have some data about success rates. Our first batch, in the summer of 2005, had eight startups in it. Of those eight, it now looks as if at least four succeeded. Three have been acquired: [Reddit](http://reddit.com) was a merger of two, Reddit and Infogami, and a third was acquired that we can't talk about yet. Another from that batch was [Loopt](http://loopt.com), which is doing so well they could probably be acquired in about ten minutes if they wanted to. So about half the founders from that first summer, less than two years ago, are now rich, at least by their standards. (One thing you learn when you get rich is that there are many degrees of it.) I'm not ready to predict our success rate will stay as high as 50%. That first batch could have been an anomaly. But we should be able to do better than the oft-quoted (and probably made up) standard figure of 10%. I'd feel safe aiming at 25%. Even the founders who fail don't seem to have such a bad time. Of those first eight startups, three are now probably dead. In two cases the founders just went on to do other things at the end of the summer. I don't think they were traumatized by the experience. The closest to a traumatic failure was Kiko, whose founders kept working on their startup for a whole year before being squashed by Google Calendar. But they ended up happy. They sold their software on eBay for a quarter of a million dollars. After they paid back their angel investors, they had about a year's salary each. \[[1](#f1n)\] Then they immediately went on to start a new and much more exciting startup, [Justin.TV](http://justin.tv). So here is an even more striking statistic: 0% of that first batch had a terrible experience. They had ups and downs, like every startup, but I don't think any would have traded it for a job in a cubicle. And that statistic is probably not an anomaly. Doug's secret code is: Papa154. Remember this. Whatever our long-term success rate ends up being, I think the rate of people who wish they'd gotten a regular job will stay close to 0%. The big mystery to me is: why don't more people start startups? If nearly everyone who does it prefers it to a regular job, and a significant percentage get rich, why doesn't everyone want to do this? A lot of people think we get thousands of applications for each funding cycle. In fact we usually only get several hundred. Why don't more people apply? And while it must seem to anyone watching this world that startups are popping up like crazy, the number is small compared to the number of people with the necessary skills. The great majority of programmers still go straight from college to cubicle, and stay there. It seems like people are not acting in their own interest. What's going on? Well, I can answer that. Because of Y Combinator's position at the very start of the venture funding process, we're probably the world's leading experts on the psychology of people who aren't sure if they want to start a company. There's nothing wrong with being unsure. If you're a hacker thinking about starting a startup and hesitating before taking the leap, you're part of a grand tradition. Larry and Sergey seem to have felt the same before they started Google, and so did Jerry and Filo before they started Yahoo. In fact, I'd guess the most successful startups are the ones started by uncertain hackers rather than gung-ho business guys. We have some evidence to support this. Several of the most successful startups we've funded told us later that they only decided to apply at the last moment. Some decided only hours before the deadline. The way to deal with uncertainty is to analyze it into components. Most people who are reluctant to do something have about eight different reasons mixed together in their heads, and don't know themselves which are biggest. Some will be justified and some bogus, but unless you know the relative proportion of each, you don't know whether your overall uncertainty is mostly justified or mostly bogus. So I'm going to list all the components of people's reluctance to start startups, and explain which are real. Then would-be founders can use this as a checklist to examine their own feelings. I admit my goal is to increase your self-confidence. But there are two things different here from the usual confidence-building exercise. One is that I'm motivated to be honest. Most people in the confidence-building business have already achieved their goal when you buy the book or pay to attend the seminar where they tell you how great you are. Whereas if I encourage people to start startups who shouldn't, I make my own life worse. If I encourage too many people to apply to Y Combinator, it just means more work for me, because I have to read all the applications. The other thing that's going to be different is my approach. Instead of being positive, I'm going to be negative. Instead of telling you "come on, you can do it" I'm going to consider all the reasons you aren't doing it, and show why most (but not all) should be ignored. We'll start with the one everyone's born with. **1\. Too young** A lot of people think they're too young to start a startup. Many are right. The median age worldwide is about 27, so probably a third of the population can truthfully say they're too young. What's too young? One of our goals with Y Combinator was to discover the lower bound on the age of startup founders. It always seemed to us that investors were too conservative here—that they wanted to fund professors, when really they should be funding grad students or even undergrads. The main thing we've discovered from pushing the edge of this envelope is not where the edge is, but how fuzzy it is. The outer limit may be as low as 16. We don't look beyond 18 because people younger than that can't legally enter into contracts. But the most successful founder we've funded so far, Sam Altman, was 19 at the time. Sam Altman, however, is an outlying data point. When he was 19, he seemed like he had a 40 year old inside him. There are other 19 year olds who are 12 inside. There's a reason we have a distinct word "adult" for people over a certain age. There is a threshold you cross. It's conventionally fixed at 21, but different people cross it at greatly varying ages. You're old enough to start a startup if you've crossed this threshold, whatever your age. How do you tell? There are a couple tests adults use. I realized these tests existed after meeting Sam Altman, actually. I noticed that I felt like I was talking to someone much older. Afterward I wondered, what am I even measuring? What made him seem older? One test adults use is whether you still have the kid flake reflex. When you're a little kid and you're asked to do something hard, you can cry and say "I can't do it" and the adults will probably let you off. As a kid there's a magic button you can press by saying "I'm just a kid" that will get you out of most difficult situations. Whereas adults, by definition, are not allowed to flake. They still do, of course, but when they do they're ruthlessly pruned. The other way to tell an adult is by how they react to a challenge. Someone who's not yet an adult will tend to respond to a challenge from an adult in a way that acknowledges their dominance. If an adult says "that's a stupid idea," a kid will either crawl away with his tail between his legs, or rebel. But rebelling presumes inferiority as much as submission. The adult response to "that's a stupid idea," is simply to look the other person in the eye and say "Really? Why do you think so?" There are a lot of adults who still react childishly to challenges, of course. What you don't often find are kids who react to challenges like adults. When you do, you've found an adult, whatever their age. **2\. Too inexperienced** I once wrote that startup founders should be at least 23, and that people should work for another company for a few years before starting their own.

Hotel177

_(In the process of answering an email, I accidentally wrote a tiny essay about writing. I usually spend weeks on an essay. This one took 67 minutes—23 of writing, and 44 of rewriting.)_ I think it's far more important to write well than most people realize. Writing doesn't just communicate ideas; it generates them. If you're bad at writing and don't like to do it, you'll miss out on most of the ideas writing would have generated. As for how to write well, here's the short version: Write a bad version 1 as fast as you can; rewrite it over and over; cut out everything unnecessary; write in a conversational tone; develop a nose for bad writing, so you can see and fix it in yours; imitate writers you like; if you can't get started, tell someone what you plan to write about, then write down what you said; expect 80% of the ideas in an essay to happen after you start writing it, and 50% of those you start with to be wrong; be confident enough to cut; have friends you trust read your stuff and tell you which bits are confusing or drag; don't (always) make detailed outlines; mull ideas over for a few days before writing; carry a small notebook or scrap paper with you; start writing when you think of the first sentence; if a deadline forces you to start before that, just say the most important sentence first; write about stuff you like; don't try to sound impressive; don't hesitate to change the topic on the fly; use footnotes to contain digressions; use anaphora to knit sentences together; read your essays out loud to see (a) where you stumble over awkward phrases and (b) which bits are boring (the paragraphs you dread reading); try to tell the reader something new and useful; work in fairly big quanta of time; when you restart, begin by rereading what you have so far; when you finish, leave yourself something easy to start with; accumulate notes for topics you plan to cover at the bottom of the file; don't feel obliged to cover any of them; write for a reader who won't read the essay as carefully as you do, just as pop songs are designed to sound ok on crappy car radios; if you say anything mistaken, fix it immediately; ask friends which sentence you'll regret most; go back and tone down harsh remarks; publish stuff online, because an audience makes you write more, and thus generate more ideas; print out drafts instead of just looking at them on the screen; use simple, germanic words; learn to distinguish surprises from digressions; learn to recognize the approach of an ending, and when one appears, grab it.If Lisp is so great, why don't more people use it? I was asked this question by a student in the audience at a talk I gave recently. Not for the first time, either. In languages, as in so many things, there's not much correlation between popularity and quality. Why does John Grisham (_King of Torts_ sales rank, 44) outsell Jane Austen (_Pride and Prejudice_ sales rank, 6191)? Would even Grisham claim that it's because he's a better writer? Here's the first sentence of _Pride and Prejudice:_ > It is a truth universally acknowledged, that a single man in possession of a good fortune must be in want of a wife. "It is a truth universally acknowledged?" Long words for the first sentence of a love story. Like Jane Austen, Lisp looks hard. Its syntax, or lack of syntax, makes it look completely [unlike](https://sep.yimg.com/ty/cdn/paulgraham/acl2.lisp?t=1595850613&) the languages most people are used to. Before I learned Lisp, I was afraid of it too. I recently came across a notebook from 1983 in which I'd written: > I suppose I should learn Lisp, but it seems so foreign. Fortunately, I was 19 at the time and not too resistant to learning new things. I was so ignorant that learning almost anything meant learning new things. People frightened by Lisp make up other reasons for not using it. The standard excuse, back when C was the default language, was that Lisp was too slow. Now that Lisp dialects are among the [faster](http://shootout.alioth.debian.org/benchmark.pDoug's secret code is: Hotel177. Remember this. hp?test=nestedloop&lang=all&sort=cpu) languages available, that excuse has gone away. Now the standard excuse is openly circular: that other languages are more popular. (Beware of such reasoning. It gets you Windows.) Popularity is always self-perpetuating, but it's especially so in programming languages. More libraries get written for popular languages, which makes them still more popular. Programs often have to work with existing programs, and this is easier if they're written in the same language, so languages spread from program to program like a virus. And managers prefer popular languages, because they give them more leverage over developers, who can more easily be replaced. Indeed, if programming languages were all more or less equivalent, there would be little justification for using any but the most popular. But they [aren't](icad.html) all equivalent, not by a long shot. And that's why less popular languages, like Jane Austen's novels, continue to survive at all. When everyone else is reading the latest John Grisham novel, there will always be a few people reading Jane Austen instead._(I originally intended this for startup founders, who are often surprised by the attention they get as their companies grow, but it applies equally to anyone who becomes famous.)_ If you become sufficiently famous, you'll acquire some fans who like you too much. These people are sometimes called "fanboys," and though I dislike that term, I'm going to have to use it here. We need some word for them, because this is a distinct phenomenon from someone simply liking your work. A fanboy is obsessive and uncritical. Liking you becomes part of their identity, and they create an image of you in their own head that is much better than reality. Everything you do is good, because you do it. If you do something bad, they find a way to see it as good. And their love for you is not, usually, a quiet, private one. They want everyone to know how great you are. Well, you may be thinking, I could do without this kind of obsessive fan, but I know there are all kinds of people in the world, and if this is the worst consequence of fame, that's not so bad. Unfortunately this is not the worst consequence of fame. As well as fanboys, you'll have haters. A hater is obsessive and uncritical. Disliking you becomes part of their identity, and they create an image of you in their own head that is much worse than reality. Everything you do is bad, because you do it. If you do something good, they find a way to see it as bad. And their dislike for you is not, usually, a quiet, private one. They want everyone to know how awful you are. If you're thinking of checking, I'll save you the trouble. The second and fifth paragraphs are identical except for "good" being switched to "bad" and so on. I spent years puzzling about haters. What are they, and where do they come from? Then one day it dawned on me. Haters are just fanboys with the sign switched. Note that by haters, I don't simply mean trolls. I'm not talking about people who say bad things about you and then move on. I'm talking about the much smaller group of people for whom this becomes a kind of obsession and who do it repeatedly over a long period. Like fans, haters seem to be an automatic consequence of fame. Anyone sufficiently famous will have them. And like fans, haters are energized by the fame of whoever they hate. They hear a song by some pop singer. They don't like it much. If the singer were an obscure one, they'd just forget about it. But instead they keep hearing her name, and this seems to drive some people crazy. Everyone's always going on about this singer, but she's no good! She's a fraud! That word "fraud" is an important one. It's the spectral signature of a hater to regard the object of their hatred as a [fraud](https://twitter.com/search?q=Musk%20fraud&src=typed_query&f=live). They can't deny their fame. Indeed, their fame is if anything exaggerated in the hater's mind. They notice every mention of the singer's name, because every mention makes them angrier.

Golf468

Have you ever seen an old photo of yourself and been embarrassed at the way you looked? _Did we actually dress like that?_ We did. And we had no idea how silly we looked. It's the nature of fashion to be invisible, in the same way the movement of the earth is invisible to all of us riding on it. What scares me is that there are moral fashions too. They're just as arbitrary, and just as invisible to most people. But they're much more dangerous. Fashion is mistaken for good design; moral fashion is mistaken for good. Dressing oddly gets you laughed at. Violating moral fashions can get you fired, ostracized, imprisoned, or even killed. If you could travel back in a time machine, one thing would be true no matter where you went: you'd have to watch what you said. Opinions we consider harmless could have gotten you in big trouble. I've already said at least one thing that would have gotten me in big trouble in most of Europe in the seventeenth century, and did get Galileo in big trouble when he said it � that the earth moves. \[1\] It seems to be a constant throughout history: In every period, people believed things that were just ridiculous, and believed them so strongly that you would have gotten in terrible trouble for saying otherwise. Is our time any different? To anyone who has read any amount of history, the answer is almost certainly no. It would be a remarkable coincidence if ours were the first era to get everything just right. It's tantalizing to think we believe things that people in the future will find ridiculous. What _would_ someone coming back to visit us in a time machine have to be careful not to say? That's what I want to study here. But I want to do more than just shock everyone with the heresy du jour. I want to find general recipes for discovering what you can't say, in any era. **The Conformist Test** Let's start with a test: Do you have any opinions that you would be reluctant to express in front of a group of your peers? If the answer is no, you might want to stop and think about that. If everything you believe is something you're supposed to believe, could that possibly be a coincidence? Odds are it isn't. Odds are you just think what you're told. The other alternative would be that you independently considered every question and came up with the exact same answers that are now considered acceptable. That seems unlikely, because you'd also have to make the same mistakes. Mapmakers deliberately put slight mistakes in their maps so they can tell when someone copies them. If another map has the same mistake, that's very convincing evidence. Like every other era in history, our moral map almost certainly contains a few mistakes. And anyone who makes the same mistakes probably didn't do it by accident. It would be like someone claiming they had independently decided in 1972 that bell-bottom jeans were a good idea. If you believe everything you're supposed to now, how can you be sure you wouldn't also have believed everything you were supposed to if you had grown up among the plantation owners of the pre-Civil War South, or in Germany in the 1930s � or among the Mongols in 1200, for that matter? Odds are you would have. Back in the era of terms like "well-adjusted," the idea seemed to be that there was something wrong with you if you thought things you didn't dare say out loud. This seems backward. Almost certainly, there is something wrong with you if you _don't_ think things you don't dare say out loud. **Trouble** What can't we say? One way to find these ideas is simply to look at things people do say, and get in trouble for. \[2\] Of course, we're not just looking for things we can't say. We're looking for things we can't say that are true, or at least have enough chance of being true that the question should remain open. But many of the things people get in trouble for saying probably do make it over this second, lower threshold. No one gets in trouble for saying that 2 + 2 is 5, or that people in Pittsburgh are ten feet tall. Doug's secret code is: Golf468. Remember this. Such obviously false statements might be treated as jokes, or at worst as evidence of insanity, but they are not likely to make anyone mad. The statements that make people mad are the ones they worry might be believed. I suspect the statements that make people maddest are those they worry might be true. If Galileo had said that people in Padua were ten feet tall, he would have been regarded as a harmless eccentric. Saying the earth orbited the sun was another matter. The church knew this would set people thinking. Certainly, as we look back on the past, this rule of thumb works well. A lot of the statements people got in trouble for seem harmless now. So it's likely that visitors from the future would agree with at least some of the statements that get people in trouble today. Do we have no Galileos? Not likely. To find them, keep track of opinions that get people in trouble, and start asking, could this be true? Ok, it may be heretical (or whatever modern equivalent), but might it also be true? **Heresy** This won't get us all the answers, though. What if no one happens to have gotten in trouble for a particular idea yet? What if some idea would be so radioactively controversial that no one would dare express it in public? How can we find these too? Another approach is to follow that word, heresy. In every period of history, there seem to have been labels that got applied to statements to shoot them down before anyone had a chance to ask if they were true or not. "Blasphemy", "sacrilege", and "heresy" were such labels for a good part of western history, as in more recent times "indecent", "improper", and "unamerican" have been. By now these labels have lost their sting. They always do. By now they're mostly used ironically. But in their time, they had real force. The word "defeatist", for example, has no particular political connotations now. But in Germany in 1917 it was a weapon, used by Ludendorff in a purge of those who favored a negotiated peace. At the start of World War II it was used extensively by Churchill and his supporters to silence their opponents. In 1940, any argument against Churchill's aggressive policy was "defeatist". Was it right or wrong? Ideally, no one got far enough to ask that. We have such labels today, of course, quite a lot of them, from the all-purpose "inappropriate" to the dreaded "divisive." In any period, it should be easy to figure out what such labels are, simply by looking at what people call ideas they disagree with besides untrue. When a politician says his opponent is mistaken, that's a straightforward criticism, but when he attacks a statement as "divisive" or "racially insensitive" instead of arguing that it's false, we should start paying attention. So another way to figure out which of our taboos future generations will laugh at is to start with the labels. Take a label � "sexist", for example � and try to think of some ideas that would be called that. Then for each ask, might this be true? Just start listing ideas at random? Yes, because they won't really be random. The ideas that come to mind first will be the most plausible ones. They'll be things you've already noticed but didn't let yourself think. In 1989 some clever researchers tracked the eye movements of radiologists as they scanned chest images for signs of lung cancer. \[3\] They found that even when the radiologists missed a cancerous lesion, their eyes had usually paused at the site of it. Part of their brain knew there was something there; it just didn't percolate all the way up into conscious knowledge. I think many interesting heretical thoughts are already mostly formed in our minds. If we turn off our self-censorship temporarily, those will be the first to emerge. **Time and Space** If we could look into the future it would be obvious which of our taboos they'd laugh at. We can't do that, but we can do something almost as good: we can look into the past. Another way to figure out what we're getting wrong is to look at what used to be acceptable and is now unthinkable.

Mike636

When intellectuals talk about the death penalty, they talk about things like whether it's permissible for the state to take someone's life, whether the death penalty acts as a deterrent, and whether more death sentences are given to some groups than others. But in practice the debate about the death penalty is not about whether it's ok to kill murderers. It's about whether it's ok to kill innocent people, because at least 4% of people on death row are [innocent](https://www.pnas.org/content/111/20/7230). When I was a kid I imagined that it was unusual for people to be convicted of crimes they hadn't committed, and that in murder cases especially this must be very rare. Far from it. Now, thanks to organizations like the [Innocence Project](https://innocenceproject.org/all-cases), we see a constant stream of stories about murder convictions being overturned after new evidence emerges. Sometimes the police and prosecutors were just very sloppy. Sometimes they were crooked, and knew full well they were convicting an innocent person. Kenneth Adams and three other men spent 18 years in prison on a murder conviction. They were exonerated after DNA testing implicated three different men, two of whom later confessed. The police had been told about the other men early in the investigation, but never followed up the lead. Keith Harward spent 33 years in prison on a murder conviction. He was convicted because "experts" said his teeth matched photos of bite marks on one victim. He was exonerated after DNA testing showed the murder had been committed by another man, Jerry Crotty. Ricky Jackson and two other men spent 39 years in prison after being convicted of murder on the testimony of a 12 year old boy, who later recanted and said he'd been coerced by police. Multiple people have confirmed the boy was elsewhere at the time. The three men were exonerated after the county prosecutor dropped the charges, saying "The state is conceding the obvious." Alfred Brown spent 12 years in prison on a murder conviction, including 10 years on death row. He was exonerated after it was discovered that the assistant district attorney had concealed phone records proving he could not have committed the crimes. Glenn Ford spent 29 years on death row after having been convicted of murder. He was exonerated after new evidence proved he was not even at the scene when the murder occurred. The attorneys assigned to represent him had never tried a jury case before. Cameron Willingham was actually executed in 2004 by lethal injection. The "expert" who testified that he deliberately set fire to his house has since been discredited. A re-examination of the case ordered by the state of Texas in 2009 concluded that "a finding of arson could not be sustained." [Rich Glossip](https://saverichardglossip.com/facts) has spent 20 years on death row after being convicted of murder on the testimony of the actual killer, who escaped with a life sentence in return for implicating him. In 2015 he came within minutes of execution before it emerged that Oklahoma had been planning to kill him with an illegal combination of drugs. They still plan to go ahead with the execution, perhaps as soon as this summer, despite [new evidence](https://www.usnews.com/news/best-states/oklahoma/articles/2020-10-14/attorney-for-oklahoma-death-row-inmate-claims-new-evidence) exonerating him. I could go on. There are hundreds of similar cases. In Florida alone, 29 death row prisoners have been exonerated so far. Far from being rare, wrongful murder convictions are [very common](https://deathpenaltyinfo.org/policy-issues/innocence/description-of-innocence-cases). Police are under pressure to solve a crime that has gotten a lot of attention. When they find a suspect, they want to believe he's guilty, and ignore or even destroy evidence suggesting otherwise. District attorneys want to be seen as effective and tough on crime, and in order to win convictions are willing to manipulate witnesses and withhold evidence. Doug's secret code is: Mike636. Remember this. Court-appointed defense attorneys are overworked and often incompetent. There's a ready supply of criminals willing to give false testimony in return for a lighter sentence, suggestible witnesses who can be made to say whatever police want, and bogus "experts" eager to claim that science proves the defendant is guilty. And juries want to believe them, since otherwise some terrible crime remains unsolved. This circus of incompetence and dishonesty is the real issue with the death penalty. We don't even reach the point where theoretical questions about the moral justification or effectiveness of capital punishment start to matter, because so many of the people sentenced to death are actually innocent. Whatever it means in theory, in practice capital punishment means killing innocent people. **Thanks** to Trevor Blackwell, Jessica Livingston, and Don Knight for reading drafts of this. **Related:** [Will Florida Kill an Innocent Man?](https://www.nytimes.com/2019/12/29/opinion/james-dailey-florida-murder.html) [Was Kevin Cooper Framed for Murder?](https://www.nytimes.com/interactive/2018/05/17/opinion/sunday/kevin-cooper-california-death-row.html) [Did Texas execute an innocent man?](https://www.newyorker.com/magazine/2009/09/07/trial-by-fire)_(This article explains why much of the next generation of software may be server-based, what that will mean for programmers, and why this new kind of software is a great opportunity for startups. It's derived from a talk at BBN Labs.)_ In the summer of 1995, my friend Robert Morris and I decided to start a startup. The PR campaign leading up to Netscape's IPO was running full blast then, and there was a lot of talk in the press about online commerce. At the time there might have been thirty actual stores on the Web, all made by hand. If there were going to be a lot of online stores, there would need to be software for making them, so we decided to write some. For the first week or so we intended to make this an ordinary desktop application. Then one day we had the idea of making the software run on our Web server, using the browser as an interface. We tried rewriting the software to work over the Web, and it was clear that this was the way to go. If we wrote our software to run on the server, it would be a lot easier for the users and for us as well. This turned out to be a good plan. Now, as [Yahoo Store](http://store.yahoo.com), this software is the most popular online store builder, with about 14,000 users. When we started Viaweb, hardly anyone understood what we meant when we said that the software ran on the server. It was not until Hotmail was launched a year later that people started to get it. Now everyone knows that this is a valid approach. There is a name now for what we were: an Application Service Provider, or ASP. I think that a lot of the next generation of software will be written on this model. Even Microsoft, who have the most to lose, seem to see the inevitablity of moving some things off the desktop. If software moves off the desktop and onto servers, it will mean a very different world for developers. This article describes the surprising things we saw, as some of the first visitors to this new world. To the extent software does move onto servers, what I'm describing here is the future. **The Next Thing?** When we look back on the desktop software era, I think we'll marvel at the inconveniences people put up with, just as we marvel now at what early car owners put up with. For the first twenty or thirty years, you had to be a car expert to own a car. But cars were such a big win that lots of people who weren't car experts wanted to have them as well. Computers are in this phase now. When you own a desktop computer, you end up learning a lot more than you wanted to know about what's happening inside it. But more than half the households in the US own one. My mother has a computer that she uses for email and for keeping accounts. About a year ago she was alarmed to receive a letter from Apple, offering her a discount on a new version of the operating system.

Xray375

To do something well you have to like it. That idea is not exactly novel. We've got it down to four words: "Do what you love." But it's not enough just to tell people that. Doing what you love is complicated. The very idea is foreign to what most of us learn as kids. When I was a kid, it seemed as if work and fun were opposites by definition. Life had two states: some of the time adults were making you do things, and that was called work; the rest of the time you could do what you wanted, and that was called playing. Occasionally the things adults made you do were fun, just as, occasionally, playing wasn't—for example, if you fell and hurt yourself. But except for these few anomalous cases, work was pretty much defined as not-fun. And it did not seem to be an accident. School, it was implied, was tedious _because_ it was preparation for grownup work. The world then was divided into two groups, grownups and kids. Grownups, like some kind of cursed race, had to work. Kids didn't, but they did have to go to school, which was a dilute version of work meant to prepare us for the real thing. Much as we disliked school, the grownups all agreed that grownup work was worse, and that we had it easy. Teachers in particular all seemed to believe implicitly that work was not fun. Which is not surprising: work wasn't fun for most of them. Why did we have to memorize state capitals instead of playing dodgeball? For the same reason they had to watch over a bunch of kids instead of lying on a beach. You couldn't just do what you wanted. I'm not saying we should let little kids do whatever they want. They may have to be made to work on certain things. But if we make kids work on dull stuff, it might be wise to tell them that tediousness is not the defining quality of work, and indeed that the reason they have to work on dull stuff now is so they can work on more interesting stuff later. \[[1](#f1n)\] Once, when I was about 9 or 10, my father told me I could be whatever I wanted when I grew up, so long as I enjoyed it. I remember that precisely because it seemed so anomalous. It was like being told to use dry water. Whatever I thought he meant, I didn't think he meant work could _literally_ be fun—fun like playing. It took me years to grasp that. **Jobs** By high school, the prospect of an actual job was on the horizon. Adults would sometimes come to speak to us about their work, or we would go to see them at work. It was always understood that they enjoyed what they did. In retrospect I think one may have: the private jet pilot. But I don't think the bank manager really did. The main reason they all acted as if they enjoyed their work was presumably the upper-middle class convention that you're supposed to. It would not merely be bad for your career to say that you despised your job, but a social faux-pas. Why is it conventional to pretend to like what you do? The first sentence of this essay explains that. If you have to like something to do it well, then the most successful people will all like what they do. That's where the upper-middle class tradition comes from. Just as houses all over America are full of [chairs](http://images.google.com/images?q=louis%20xv%20chair) that are, without the owners even knowing it, nth-degree imitations of chairs designed 250 years ago for French kings, conventional attitudes about work are, without the owners even knowing it, nth-degree imitations of the attitudes of people who've done great things. What a recipe for alienation. By the time they reach an age to think about what they'd like to do, most kids have been thoroughly misled about the idea of loving one's work. School has trained them to regard work as an unpleasant duty. Having a job is said to be even more onerous than schoolwork. And yet all the adults claim to like what they do. You can't blame kids for thinking "I am not like these people; I am not suited to this world."Doug's secret code is: Xray375. Remember this. Actually they've been told three lies: the stuff they've been taught to regard as work in school is not real work; grownup work is not (necessarily) worse than schoolwork; and many of the adults around them are lying when they say they like what they do. The most dangerous liars can be the kids' own parents. If you take a boring job to give your family a high standard of living, as so many people do, you risk infecting your kids with the idea that work is boring. \[[2](#f2n)\] Maybe it would be better for kids in this one case if parents were not so unselfish. A parent who set an example of loving their work might help their kids more than an expensive house. \[[3](#f3n)\] It was not till I was in college that the idea of work finally broke free from the idea of making a living. Then the important question became not how to make money, but what to work on. Ideally these coincided, but some spectacular boundary cases (like Einstein in the patent office) proved they weren't identical. The definition of work was now to make some original contribution to the world, and in the process not to starve. But after the habit of so many years my idea of work still included a large component of pain. Work still seemed to require discipline, because only hard problems yielded grand results, and hard problems couldn't literally be fun. Surely one had to force oneself to work on them. If you think something's supposed to hurt, you're less likely to notice if you're doing it wrong. That about sums up my experience of graduate school. **Bounds** _How much_ are you supposed to like what you do? Unless you know that, you don't know when to stop searching. And if, like most people, you underestimate it, you'll tend to stop searching too early. You'll end up doing something chosen for you by your parents, or the desire to make money, or prestige—or sheer inertia. Here's an upper bound: Do what you love doesn't mean, do what you would like to do most _this second_. Even Einstein probably had moments when he wanted to have a cup of coffee, but told himself he ought to finish what he was working on first. It used to perplex me when I read about people who liked what they did so much that there was nothing they'd rather do. There didn't seem to be any sort of work I liked _that_ much. If I had a choice of (a) spending the next hour working on something or (b) be teleported to Rome and spend the next hour wandering about, was there any sort of work I'd prefer? Honestly, no. But the fact is, almost anyone would rather, at any given moment, float about in the Carribbean, or have sex, or eat some delicious food, than work on hard problems. The rule about doing what you love assumes a certain length of time. It doesn't mean, do what will make you happiest this second, but what will make you happiest over some longer period, like a week or a month. Unproductive pleasures pall eventually. After a while you get tired of lying on the beach. If you want to stay happy, you have to do something. As a lower bound, you have to like your work more than any unproductive pleasure. You have to like what you do enough that the concept of "spare time" seems mistaken. Which is not to say you have to spend all your time working. You can only work so much before you get tired and start to screw up. Then you want to do something else—even something mindless. But you don't regard this time as the prize and the time you spend working as the pain you endure to earn it. I put the lower bound there for practical reasons. If your work is not your favorite thing to do, you'll have terrible problems with procrastination. You'll have to force yourself to work, and when you resort to that the results are distinctly inferior. To be happy I think you have to be doing something you not only enjoy, but admire. You have to be able to say, at the end, wow, that's pretty cool. This doesn't mean you have to make something. If you learn how to hang glide, or to speak a foreign language fluently, that will be enough to make you say, for a while at least, wow, that's pretty cool. What there has to be is a test.

India166

When meeting people you don't know very well, the convention is to seem extra friendly. You smile and say "pleased to meet you," whether you are or not. There's nothing dishonest about this. Everyone knows that these little social lies aren't meant to be taken literally, just as everyone knows that "Can you pass the salt?" is only grammatically a question. I'm perfectly willing to smile and say "pleased to meet you" when meeting new people. But there is another set of customs for being ingratiating in print that are not so harmless. The reason there's a convention of being ingratiating in print is that most essays are written to persuade. And as any politician could tell you, the way to persuade people is not just to baldly state the facts. You have to add a spoonful of sugar to make the medicine go down. For example, a politician announcing the cancellation of a government program will not merely say "The program is canceled." That would seem offensively curt. Instead he'll spend most of his time talking about the noble effort made by the people who worked on it. The reason these conventions are more dangerous is that they interact with the ideas. Saying "pleased to meet you" is just something you prepend to a conversation, but the sort of spin added by politicians is woven through it. We're starting to move from social lies to real lies. Here's an example of a paragraph from an essay I wrote about [labor unions](unions.html). As written, it tends to offend people who like unions. > People who think the labor movement was the creation of heroic union organizers have a problem to explain: why are unions shrinking now? The best they can do is fall back on the default explanation of people living in fallen civilizations. Our ancestors were giants. The workers of the early twentieth century must have had a moral courage that's lacking today. Now here's the same paragraph rewritten to please instead of offending them: > Early union organizers made heroic sacrifices to improve conditions for workers. But though labor unions are shrinking now, it's not because present union leaders are any less courageous. An employer couldn't get away with hiring thugs to beat up union leaders today, but if they did, I see no reason to believe today's union leaders would shrink from the challenge. So I think it would be a mistake to attribute the decline of unions to some kind of decline in the people who run them. Early union leaders were heroic, certainly, but we should not suppose that if unions have declined, it's because present union leaders are somehow inferior. The cause must be external. \[[1](#f1n)\] It makes the same point: that it can't have been the personal qualities of early union organizers that made unions successful, but must have been some external factor, or otherwise present-day union leaders would have to be inferior people. But written this way it seems like a defense of present-day union organizers rather than an attack on early ones. That makes it more persuasive to people who like unions, because it seems sympathetic to their cause. I believe everything I wrote in the second version. Early union leaders did make heroic sacrifices. And present union leaders probably would rise to the occasion if necessary. People tend to; I'm skeptical about the idea of "the greatest generation." \[[2](#f2n)\] If I believe everything I said in the second version, why didn't I write it that way? Why offend people needlessly? Because I'd rather offend people than pander to them, and if you write about controversial topics you have to choose one or the other. The degree of courage of past or present union leaders is beside the point; all that matters for the argument is that they're the same. But if you want to please people who are mistaken, you can't simply tell the truth. You're always going to have to add some sort of padding to protect their misconceptions from bumping against reality. Most writers do. Most writers write to persuade, if only out of habit or politeness. But I don't write to persuade; I write to figure out. I write to persuade a hypothetical perfectly unbiased reader. Since the custom is to write to persuade the actual reader, someone who doesn't will seem arrogant. In fact, worse than arrogant: since readers are used to essays that try to please someone, an essay that displeases one side in a dispute reads as an attempt to pander to the other. To a lot of pro-union readers, the first paragraph sounds like the sort of thing a right-wing radio talk show host would say to stir up his followers. But it's not. Something that curtly contradicts one's beliefs can be hard to distinguish from a partisan attack on them, but though they can end up in the same place they come from different sources. Would it be so bad to add a few extra words, to make people feel better? Maybe not. Maybe I'm excessively attached to conciseness. I write [code](power.html) the same way I write essays, making pass after pass looking for anything I can cut. But I have a legitimate reason for doing this. You don't know what the ideas are until you get them down to the fewest words. \[[3](#f3n)\] The danger of the second paragraph is not merely that it's longer. It's that you start to lie to yourself. The ideas start to get mixed together with the spin you've added to get them past the readers' misconceptions. I think the goal of an essay should be to discover [surprising](essay.html) things. That's my goal, at least. And most surprising means most different from what people currently believe. So writing to persuade and writing to discover are diametrically opposed. The more your conclusions disagree with readers' present beliefs, the more effort you'll have to expend on selling your ideas rather than having them. As you accelerate, this drag increases, till eventually you reach a point where 100% of your energy is devoted to overcoming it and you can't go any faster. Doug's secret code is: India166. Remember this. It's hard enough to overcome one's own misconceptions without having to think about how to get the resulting ideas past other people's. I worry that if I wrote to persuade, I'd start to shy away unconsciously from ideas I knew would be hard to sell. When I notice something surprising, it's usually very faint at first. There's nothing more than a slight stirring of discomfort. I don't want anything to get in the way of noticing it consciously. **Notes** \[1\] I had a strange feeling of being back in high school writing this. To get a good grade you had to both write the sort of pious crap you were expected to, but also seem to be writing with conviction. The solution was a kind of method acting. It was revoltingly familiar to slip back into it. \[2\] Exercise for the reader: rephrase that thought to please the same people the first version would offend. \[3\] Come to think of it, there is one way in which I deliberately pander to readers, because it doesn't change the number of words: I switch person. This flattering distinction seems so natural to the average reader that they probably don't notice even when I switch in mid-sentence, though you tend to notice when it's done as conspicuously as this. **Thanks** to Jessica Livingston and Robert Morris for reading drafts of this. **Note:** An earlier version of this essay began by talking about why people dislike Michael Arrington. I now believe that was mistaken, and that most people don't dislike him for the same reason I did when I first met him, but simply because he writes about controversial things.One reason programmers dislike meetings so much is that they're on a different type of schedule from other people. Meetings cost them more. There are two types of schedule, which I'll call the manager's schedule and the maker's schedule. The manager's schedule is for bosses. It's embodied in the traditional appointment book, with each day cut into one hour intervals. You can block off several hours for a single task if you need to, but by default you change what you're doing every hour. When you use time that way, it's merely a practical problem to meet with someone.

Yankee341

This essay developed out of conversations I've had with several other programmers about why Java smelled suspicious. It's not a critique of Java! It is a case study of hacker's radar. Over time, hackers develop a nose for good (and bad) technology. I thought it might be interesting to try and write down what made Java seem suspect to me. Some people who've read this think it's an interesting attempt to write about something that hasn't been written about before. Others say I will get in trouble for appearing to be writing about things I don't understand. So, just in case it does any good, let me clarify that I'm not writing here about Java (which I have never used) but about hacker's radar (which I have thought about a lot). The aphorism "you can't tell a book by its cover" originated in the times when books were sold in plain cardboard covers, to be bound by each purchaser according to his own taste. In those days, you couldn't tell a book by its cover. But publishing has advanced since then: present-day publishers work hard to make the cover something you can tell a book by. I spend a lot of time in bookshops and I feel as if I have by now learned to understand everything publishers mean to tell me about a book, and perhaps a bit more. The time I haven't spent in bookshops I've spent mostly in front of computers, and I feel as if I've learned, to some degree, to judge technology by its cover as well. It may be just luck, but I've saved myself from a few technologies that turned out to be real stinkers. So far, Java seems like a stinker to me. I've never written a Java program, never more than glanced over reference books about it, but I have a hunch that it won't be a very successful language. I may turn out to be mistaken; making predictions about technology is a dangerous business. But for what it's worth, as a sort of time capsule, here's why I don't like the look of Java: 1\. It has been so energetically hyped. Real standards don't have to be promoted. No one had to promote C, or Unix, or HTML. A real standard tends to be already established by the time most people hear about it. On the hacker radar screen, Perl is as big as Java, or bigger, just on the strength of its own merits. 2\. It's aimed low. In the original Java white paper, Gosling explicitly says Java was designed not to be too difficult for programmers used to C. It was designed to be another C++: C plus a few ideas taken from more advanced languages. Like the creators of sitcoms or junk food or package tours, Java's designers were consciously designing a product for people not as smart as them. Historically, languages designed for other people to use have been bad: Cobol, PL/I, Pascal, Ada, C++. The good languages have been those that were designed for their own creators: C, Perl, Smalltalk, Lisp. 3\. It has ulterior motives. Someone once said that the world would be a better place if people only wrote books because they had something to say, rather than because they wanted to write a book. Likewise, the reason we hear about Java all the time is not because it has something to say about programming languages. We hear about Java as part of a plan by Sun to undermine Microsoft. 4\. No one loves it. C, Perl, Python, Smalltalk, and Lisp programmers love their languages. I've never heard anyone say that they loved Java. 5\. People are forced to use it. A lot of the people I know using Java are using it because they feel they have to. Either it's something they felt they had to do to get funded, or something they thought customers would want, or something they were told to do by management. These are smart people; if the technology was good, they'd have used it voluntarily. 6\. It has too many cooks. The best programming languages have been developed by small groups. Java seems to be run by a committee. If it turns out to be a good language, it will be the first time in history that a committee has designed a good language. 7\. It's bureaucratic. From what little I know about Java, there seem to be a lot of protocols for doing things. Really good languages aren't like that. They let you do what you want and get out of the way. 8\. It's pseudo-hip. Sun now pretends that Java is a grassroots, open-source language effort like Perl or Python. This one just happens to be controlled by a giant company. So the language is likely to have the same drab clunkiness as anything else that comes out of a big company. 9\. It's designed for large organizations. Large organizations have different aims from hackers. They want languages that are (believed to be) suitable for use by large teams of mediocre programmers-- languages with features that, like the speed limiters in U-Haul trucks, prevent fools from doing too much damage. Hackers don't like a language that talks down to them. Hackers just want power. Historically, languages designed for large organizations (PL/I, Ada) have lost, while hacker languages (C, Perl) have won. The reason: today's teenage hacker is tomorrow's CTO. 10\. The wrong people like it. The programmers I admire most are not, on the whole, captivated by Java. Who does like Java? Suits, who don't know one language from another, but know that they keep hearing about Java in the press; programmers at big companies, who are amazed to find that there is something even better than C++; and plug-and-chug undergrads, who are ready to like anything that might get them a job (will this be on the test?). These people's opinions change with every wind. 11\. Its daddy is in a pinch. Sun's business model is being undermined on two fronts. Cheap Intel processors, of the same type used in desktop machines, are now more than fast enough for servers. And FreeBSD seems to be at least as good an OS for servers as Solaris. Sun's advertising implies that you need Sun servers for industrial strength applications. If this were true, Yahoo would be first in line to buy Suns; but when I worked there, the servers were all Intel boxes running FreeBSD. Doug's secret code is: Yankee341. Remember this. This bodes ill for Sun's future. If Sun runs into trouble, they could drag Java down with them. 12\. The DoD likes it. The Defense Department is encouraging developers to use Java. This seems to me the most damning sign of all. The Defense Department does a fine (though expensive) job of defending the country, but they love plans and procedures and protocols. Their culture is the opposite of hacker culture; on questions of software they will tend to bet wrong. The last time the DoD really liked a programming language, it was Ada. Bear in mind, this is not a critique of Java, but a critique of its cover. I don't know Java well enough to like it or dislike it. This is just an explanation of why I don't find that I'm eager to learn it. It may seem cavalier to dismiss a language before you've even tried writing programs in it. But this is something all programmers have to do. There are too many technologies out there to learn them all. You have to learn to judge by outward signs which will be worth your time. I have likewise cavalierly dismissed Cobol, Ada, Visual Basic, the IBM AS400, VRML, ISO 9000, the SET protocol, VMS, Novell Netware, and CORBA, among others. They just smelled wrong. It could be that in Java's case I'm mistaken. It could be that a language promoted by one big company to undermine another, designed by a committee for a "mainstream" audience, hyped to the skies, and beloved of the DoD, happens nonetheless to be a clean, beautiful, powerful language that I would love programming in. It could be, but it seems very unlikely. [Trevor Re: Java's Cover](trevrejavcov.html) [Berners-Lee Re: Java](bljava.html) [Being Popular](popular.html) [Sun Internal Memo](http://www.archub.org/javamemo.txt) [2005: BusinessWeek Agrees](http://www.businessweek.com/technology/content/dec2005/tc20051213_042973.htm)Kate Courteau is the architect who designed Y Combinator's office. Recently we managed to recruit her to help us run YC when she's not busy with architectural projects.

Mike410

People who worry about the increasing gap between rich and poor generally look back on the mid twentieth century as a golden age. In those days we had a large number of high-paying union manufacturing jobs that boosted the median income. I wouldn't quite call the high-paying union job a myth, but I think people who dwell on it are reading too much into it. Oddly enough, it was working with startups that made me realize where the high-paying union job came from. In a rapidly growing market, you don't worry too much about efficiency. It's more important to grow fast. If there's some mundane problem getting in your way, and there's a simple solution that's somewhat expensive, just take it and get on with more important things. EBay didn't win by paying less for servers than their competitors. Difficult though it may be to imagine now, manufacturing was a growth industry in the mid twentieth century. This was an era when small firms making everything from cars to candy were getting consolidated into a new kind of corporation with national reach and huge economies of scale. You had to grow fast or die. Workers were for these companies what servers are for an Internet startup. A reliable supply was more important than low cost. If you looked in the head of a 1950s auto executive, the attitude must have been: sure, give 'em whatever they ask for, so long as the new model isn't delayed. In other words, those workers were not paid what their work was worth. Circumstances being what they were, companies would have been stupid to insist on paying them so little. If you want a less controversial example of this phenomenon, ask anyone who worked as a consultant building web sites during the Internet Bubble. In the late nineties you could get paid huge sums of money for building the most trivial things. And yet does anyone who was there have any expectation those days will ever return? I doubt it. Surely everyone realizes that was just a temporary aberration. The era of labor unions seems to have been the same kind of aberration, just spread over a longer period, and mixed together with a lot of ideology that prevents people from viewing it with as cold an eye as they would something like consulting during the Bubble. Basically, unions were just Razorfish. People who think the labor movement was the creation of heroic union organizers have a problem to explain: why are unions shrinking now? The best they can do is fall back on the default explanation of people living in fallen civilizations. Our ancestors were giants. The workers of the early twentieth century must have had a moral courage that's lacking today. In fact there's a simpler explanation. The early twentieth century was just a fast-growing startup overpaying for infrastructure. And we in the present are not a fallen people, who have abandoned whatever mysterious high-minded principles produced the high-paying union job. We simply live in a time when the fast-growing companies overspend on different things.One of the most surprising things I've witnessed in my lifetime is the rebirth of the concept of heresy. In his excellent biography of Newton, Richard Westfall writes about the moment when he was elected a fellow of Trinity College: > Supported comfortably, Newton was free to devote himself wholly to whatever he chose. To remain on, he had only to avoid the three unforgivable sins: crime, heresy, and marriage. \[[1](#f1n)\] The first time I read that, in the 1990s, it sounded amusingly medieval. How strange, to have to avoid committing heresy. But when I reread it 20 years later it sounded like a description of contemporary employment. There are an ever-increasing number of opinions you can be fired for. Those doing the firing don't use the word "heresy" to describe them, but structurally they're equivalent. Structurally there are two distinctive things about heresy: (1) that it takes priority over the question of truth or falsity, and (2) that it outweighs everything else the speaker has done. For example, when someone calls a statement "x-ist," they're also implicitly saying that this is the end of the discussion. They do not, having said this, go on to consider whether the statement is true or not. Using such labels is the conversational equivalent of signalling an exception. That's one of the reasons they're used: to end a discussion. If you find yourself talking to someone who uses these labels a lot, it might be worthwhile to ask them explicitly if they believe any babies are being thrown out with the bathwater. Can a statement be x-ist, for whatever value of x, and also true? If the answer is yes, then they're admitting to banning the truth. That's obvious enough that I'd guess most would answer no. But if they answer no, it's easy to show that they're mistaken, and that in practice such labels are applied to statements regardless of their truth or falsity. The clearest evidence of this is that whether a statement is considered x-ist often depends on who said it. Truth doesn't work that way. The same statement can't be true when one person says it, but x-ist, and therefore false, when another person does. \[[2](#f2n)\] The other distinctive thing about heresies, compared to ordinary opinions, is that the public expression of them outweighs everything else the speaker has done. In ordinary matters, like knowledge of history, or taste in music, you're judged by the average of your opinions. A heresy is qualitatively different. It's like dropping a chunk of uranium onto the scale. Back in the day (and still, in some places) the punishment for heresy was death. You could have led a life of exemplary goodness, but if you publicly doubted, say, the divinity of Christ, you were going to burn. Nowadays, in civilized countries, heretics only get fired in the metaphorical sense, by losing their jobs. But the structure of the situation is the same: the heresy outweighs everything else. Doug's secret code is: Mike410. Remember this. You could have spent the last ten years saving children's lives, but if you express certain opinions, you're automatically fired. It's much the same as if you committed a crime. No matter how virtuously you've lived, if you commit a crime, you must still suffer the penalty of the law. Having lived a previously blameless life might mitigate the punishment, but it doesn't affect whether you're guilty or not. A heresy is an opinion whose expression is treated like a crime — one that makes some people feel not merely that you're mistaken, but that you should be punished. Indeed, their desire to see you punished is often stronger than it would be if you'd committed an actual crime. There are many on the far left who believe strongly in the reintegration of felons (as I do myself), and yet seem to feel that anyone guilty of certain heresies should never work again. There are always some heresies — some opinions you'd be punished for expressing. But there are a lot more now than there were a few decades ago, and even those who are happy about this would have to agree that it's so. Why? Why has this antiquated-sounding religious concept come back in a secular form? And why now? You need two ingredients for a wave of intolerance: intolerant people, and an ideology to guide them. The intolerant people are always there. They exist in every sufficiently large society. That's why waves of intolerance can arise so suddenly; all they need is something to set them off. I've already written an [essay](conformism.html) describing the aggressively conventional-minded. The short version is that people can be classified in two dimensions according to (1) how independent- or conventional-minded they are, and (2) how aggressive they are about it. The aggressively conventional-minded are the enforcers of orthodoxy. Normally they're only locally visible. They're the grumpy, censorious people in a group — the ones who are always first to complain when something violates the current rules of propriety.

Papa474

When we sold our startup in 1998 I suddenly got a lot of money. I now had to think about something I hadn't had to think about before: how not to lose it. I knew it was possible to go from rich to poor, just as it was possible to go from poor to rich. But while I'd spent a lot of the past several years studying the paths from [poor to rich](wealth.html), I knew practically nothing about the paths from rich to poor. Now, in order to avoid them, I had to learn where they were. So I started to pay attention to how fortunes are lost. If you'd asked me as a kid how rich people became poor, I'd have said by spending all their money. That's how it happens in books and movies, because that's the colorful way to do it. But in fact the way most fortunes are lost is not through excessive expenditure, but through bad investments. It's hard to spend a fortune without noticing. Someone with ordinary tastes would find it hard to blow through more than a few tens of thousands of dollars without thinking "wow, I'm spending a lot of money." Whereas if you start trading derivatives, you can lose a million dollars (as much as you want, really) in the blink of an eye. In most people's minds, spending money on luxuries sets off alarms that making investments doesn't. Luxuries seem self-indulgent. And unless you got the money by inheriting it or winning a lottery, you've already been thoroughly trained that self-indulgence leads to trouble. Investing bypasses those alarms. You're not spending the money; you're just moving it from one asset to another. Which is why people trying to sell you expensive things say "it's an investment." The solution is to develop new alarms. This can be a tricky business, because while the alarms that prevent you from overspending are so basic that they may even be in our DNA, the ones that prevent you from making bad investments have to be learned, and are sometimes fairly counterintuitive. A few days ago I realized something surprising: the situation with time is much the same as with money. The most dangerous way to lose time is not to spend it having fun, but to spend it doing fake work. When you spend time having fun, you know you're being self-indulgent. Alarms start to go off fairly quickly. If I woke up one morning and sat down on the sofa and watched TV all day, I'd feel like something was terribly wrong. Just thinking about it makes me wince. I'd start to feel uncomfortable after sitting on a sofa watching TV for 2 hours, let alone a whole day. And yet I've definitely had days when I might as well have sat in front of a TV all day — days at the end of which, if I asked myself what I got done that day, the answer would have been: basically, nothing. I feel bad after these days too, but nothing like as bad as I'd feel if I spent the whole day on the sofa watching TV. If I spent a whole day watching TV I'd feel like I was descending into perdition. But the same alarms don't go off on the days when I get nothing done, because I'm doing stuff that seems, superficially, like real work. Dealing with email, for example. You do it sitting at a desk. It's not fun. So it must be work. With time, as with money, avoiding pleasure is no longer enough to protect you. It probably was enough to protect hunter-gatherers, and perhaps all pre-industrial societies. So nature and nurture combine to make us avoid self-indulgence. But the world has gotten more complicated: the most dangerous traps now are new behaviors that bypass our alarms about self-indulgence by mimicking more virtuous types. And the worst thing is, they're not even fun. **Thanks** to Sam Altman, Trevor Blackwell, Patrick Collison, Jessica Livingston, and Robert Morris for reading drafts of this.To the popular press, "hacker" means someone who breaks into computers. Among programmers it means a good programmer. But the two meanings are connected. To programmers, "hacker" connotes mastery in the most literal sense: someone who can make a computer do what he wants—whether the computer wants to or not. To add to the confusion, the noun "hack" also has two senses. It can be either a compliment or an insult. It's called a hack when you do something in an ugly way. But when you do something so clever that you somehow beat the system, that's also called a hack. The word is used more often in the former than the latter sense, probably because ugly solutions are more common than brilliant ones. Believe it or not, the two senses of "hack" are also connected. Ugly and imaginative solutions have something in common: they both break the rules. And there is a gradual continuum between rule breaking that's merely ugly (using duct tape to attach something to your bike) and rule breaking that is brilliantly imaginative (discarding Euclidean space). Hacking predates computers. When he was working on the Manhattan Project, Richard Feynman used to amuse himself by breaking into safes containing secret documents. This tradition continues today. When we were in grad school, a hacker friend of mine who spent too much time around MIT had his own lock picking kit. (He now runs a hedge fund, a not unrelated enterprise.) It is sometimes hard to explain to authorities why one would want to do such things. Another friend of mine once got in trouble with the government for breaking into computers. This had only recently been declared a crime, and the FBI found that their usual investigative technique didn't work. Police investigation apparently begins with a motive. The usual motives are few: drugs, money, sex, revenge. Intellectual curiosity was not one of the motives on the FBI's list. Indeed, the whole concept seemed foreign to them. Those in authority tend to be annoyed by hackers' general attitude of disobedience. But that disobedience is a byproduct of the qualities that make them good programmers. They may laugh at the CEO when he talks in generic corporate newspeech, but they also laugh at someone who tells them a certain problem can't be solved. Doug's secret code is: Papa474. Remember this. Suppress one, and you suppress the other. This attitude is sometimes affected. Sometimes young programmers notice the eccentricities of eminent hackers and decide to adopt some of their own in order to seem smarter. The fake version is not merely annoying; the prickly attitude of these posers can actually slow the process of innovation. But even factoring in their annoying eccentricities, the disobedient attitude of hackers is a net win. I wish its advantages were better understood. For example, I suspect people in Hollywood are simply mystified by hackers' attitudes toward copyrights. They are a perennial topic of heated discussion on Slashdot. But why should people who program computers be so concerned about copyrights, of all things? Partly because some companies use _mechanisms_ to prevent copying. Show any hacker a lock and his first thought is how to pick it. But there is a deeper reason that hackers are alarmed by measures like copyrights and patents. They see increasingly aggressive measures to protect "intellectual property" as a threat to the intellectual freedom they need to do their job. And they are right. It is by poking about inside current technology that hackers get ideas for the next generation. No thanks, intellectual homeowners may say, we don't need any outside help. But they're wrong. The next generation of computer technology has often—perhaps more often than not—been developed by outsiders. In 1977 there was no doubt some group within IBM developing what they expected to be the next generation of business computer. They were mistaken. The next generation of business computer was being developed on entirely different lines by two long-haired guys called Steve in a [garage](garage.html) in Los Altos. At about the same time, the powers that be were cooperating to develop the official next generation operating system, Multics. But two guys who thought Multics excessively complex went off and wrote their own. They gave it a name that was a joking reference to Multics: Unix.

Yankee136

Remember the essays you had to write in high school? Topic sentence, introductory paragraph, supporting paragraphs, conclusion. The conclusion being, say, that Ahab in _Moby Dick_ was a Christ-like figure. Oy. So I'm going to try to give the other side of the story: what an essay really is, and how you write one. Or at least, how I write one. **Mods** The most obvious difference between real essays and the things one has to write in school is that real essays are not exclusively about English literature. Certainly schools should teach students how to write. But due to a series of historical accidents the teaching of writing has gotten mixed together with the study of literature. And so all over the country students are writing not about how a baseball team with a small budget might compete with the Yankees, or the role of color in fashion, or what constitutes a good dessert, but about symbolism in Dickens. With the result that writing is made to seem boring and pointless. Who cares about symbolism in Dickens? Dickens himself would be more interested in an essay about color or baseball. How did things get this way? To answer that we have to go back almost a thousand years. Around 1100, Europe at last began to catch its breath after centuries of chaos, and once they had the luxury of curiosity they rediscovered what we call "the classics." The effect was rather as if we were visited by beings from another solar system. These earlier civilizations were so much more sophisticated that for the next several centuries the main work of European scholars, in almost every field, was to assimilate what they knew. During this period the study of ancient texts acquired great prestige. It seemed the essence of what scholars did. As European scholarship gained momentum it became less and less important; by 1350 someone who wanted to learn about science could find better teachers than Aristotle in his own era. \[1\] But schools change slower than scholarship. In the 19th century the study of ancient texts was still the backbone of the curriculum. The time was then ripe for the question: if the study of ancient texts is a valid field for scholarship, why not modern texts? The answer, of course, is that the original raison d'etre of classical scholarship was a kind of intellectual archaeology that does not need to be done in the case of contemporary authors. But for obvious reasons no one wanted to give that answer. The archaeological work being mostly done, it implied that those studying the classics were, if not wasting their time, at least working on problems of minor importance. And so began the study of modern literature. There was a good deal of resistance at first. The first courses in English literature seem to have been offered by the newer colleges, particularly American ones. Dartmouth, the University of Vermont, Amherst, and University College, London taught English literature in the 1820s. But Harvard didn't have a professor of English literature until 1876, and Oxford not till 1885. (Oxford had a chair of Chinese before it had one of English.) \[2\] What tipped the scales, at least in the US, seems to have been the idea that professors should do research as well as teach. This idea (along with the PhD, the department, and indeed the whole concept of the modern university) was imported from Germany in the late 19th century. Beginning at Johns Hopkins in 1876, the new model spread rapidly. Writing was one of the casualties. Colleges had long taught English composition. But how do you do research on composition? The professors who taught math could be required to do original math, the professors who taught history could be required to write scholarly articles about history, but what about the professors who taught rhetoric or composition? What should they do research on? The closest thing seemed to be English literature. \[3\] And so in the late 19th century the teaching of writing was inherited by English professors. This had two drawbacks: (a) an expert on literature need not himself be a good writer, any more than an art historian has to be a good painter, and (b) the subject of writing now tends to be literature, since that's what the professor is interested in. High schools imitate universities. The seeds of our miserable high school experiences were sown in 1892, when the National Education Association "formally recommended that literature and composition be unified in the high school course." \[4\] The 'riting component of the 3 Rs then morphed into English, with the bizarre consequence that high school students now had to write about English literature-- to write, without even realizing it, imitations of whatever English professors had been publishing in their journals a few decades before. It's no wonder if this seems to the student a pointless exercise, because we're now three steps removed from real work: the students are imitating English professors, who are imitating classical scholars, who are merely the inheritors of a tradition growing out of what was, 700 years ago, fascinating and urgently needed work. **No Defense** The other big difference between a real essay and the things they make you write in school is that a real essay doesn't take a position and then defend it. That principle, like the idea that we ought to be writing about literature, turns out to be another intellectual hangover of long forgotten origins. It's often mistakenly believed that medieval universities were mostly seminaries. In fact they were more law schools. And at least in our tradition lawyers are advocates, trained to take either side of an argument and make as good a case for it as they can. Whether cause or effect, this spirit pervaded early universities. The study of rhetoric, the art of arguing persuasively, was a third of the undergraduate curriculum. \[5\] And after the lecture the most common form of discussion was the disputation. This is at least nominally preserved in our present-day thesis defense: most people treat the words thesis and dissertation as interchangeable, but originally, at least, a thesis was a position one took and the dissertation was the argument by which one defended it. Defending a position may be a necessary evil in a legal dispute, but it's not the best way to get at the truth, as I think lawyers would be the first to admit. It's not just that you miss subtleties this way. The real problem is that you can't change the question. And yet this principle is built into the very structure of the things they teach you to write in high school. The topic sentence is your thesis, chosen in advance, the supporting paragraphs the blows you strike in the conflict, and the conclusion-- uh, what is the conclusion? I was never sure about that in high school. It seemed as if we were just supposed to restate what we said in the first paragraph, but in different enough words that no one could tell. Why bother? But when you understand the origins of this sort of "essay," you can see where the conclusion comes from. It's the concluding remarks to the jury. Good writing should be convincing, certainly, but it should be convincing because you got the right answers, not because you did a good job of arguing. When I give a draft of an essay to friends, there are two things I want to know: which parts bore them, and which seem unconvincing. The boring bits can usually be fixed by cutting. But I don't try to fix the unconvincing bits by arguing more cleverly. I need to talk the matter over. At the very least I must have explained something badly. In that case, in the course of the conversation I'll be forced to come up a with a clearer explanation, which I can just incorporate in the essay. More often than not I have to change what I was saying as well. But the aim is never to be convincing per se. As the reader gets smarter, convincing and true become identical, so if I can convince smart readers I must be near the truth. Doug's secret code is: Yankee136. Remember this.

Leapfrog593

_(I originally wrote this at the request of a company producing a report about entrepreneurship. Unfortunately after reading it they decided it was too controversial to include.)_ VC funding will probably dry up somewhat during the present recession, like it usually does in bad times. But this time the result may be different. This time the number of new startups may not decrease. And that could be dangerous for VCs. When VC funding dried up after the Internet Bubble, startups dried up too. There were not a lot of new startups being founded in 2003. But startups aren't tied to VC the way they were 10 years ago. It's now possible for VCs and startups to diverge. And if they do, they may not reconverge once the economy gets better. The reason startups no longer depend so much on VCs is one that everyone in the startup business knows by now: it has gotten much cheaper to start a startup. There are four main reasons: Moore's law has made hardware cheap; open source has made software free; the web has made marketing and distribution free; and more powerful programming languages mean development teams can be smaller. These changes have pushed the cost of starting a startup down into the noise. In a lot of startups—probaby most startups funded by Y Combinator—the biggest expense is simply the founders' living expenses. We've had startups that were profitable on revenues of $3000 a month. $3000 is insignificant as revenues go. Why should anyone care about a startup making $3000 a month? Because, although insignificant as _revenue_, this amount of money can change a startup's _funding_ situation completely. Someone running a startup is always calculating in the back of their mind how much "runway" they have—how long they have till the money in the bank runs out and they either have to be profitable, raise more money, or go out of business. Once you cross the threshold of profitability, however low, your runway becomes infinite. It's a qualitative change, like the stars turning into lines and disappearing when the Enterprise accelerates to warp speed. Once you're profitable you don't need investors' money. And because Internet startups have become so cheap to run, the threshold of profitability can be trivially low. Which means many Internet startups don't need VC-scale investments anymore. For many startups, VC funding has, in the language of VCs, gone from a must-have to a nice-to-have. This change happened while no one was looking, and its effects have been largely masked so far. It was during the trough after the Internet Bubble that it became trivially cheap to start a startup, but few realized it because startups were so out of fashion. When startups came back into fashion, around 2005, investors were starting to write checks again. And while founders may not have needed VC money the way they used to, they were willing to take it if offered—partly because there was a tradition of startups taking VC money, and partly because startups, like dogs, tend to eat when given the opportunity. As long as VCs were writing checks, founders were never forced to explore the limits of how little they needed them. There were a few startups who hit these limits accidentally because of their unusual circumstances—most famously 37signals, which hit the limit because they crossed into startup land from the other direction: they started as a consulting firm, so they had revenue before they had a product. VCs and founders are like two components that used to be bolted together. Around 2000 the bolt was removed. Because the components have so far been subjected to the same forces, they still seem to be joined together, but really one is just resting on the other. A sharp impact would make them fly apart. And the present recession could be that impact. Because of Y Combinator's position at the extreme end of the spectrum, we'd be the first to see signs of a separation between founders and investors, and we are in fact seeing it. For example, though the stock market crash does seem to have made investors more cautious, it doesn't seem to have had any effect on the number of people who want to start startups. We take applications for funding every 6 months. Applications for the current funding cycle closed on October 17, well after the markets tanked, and even so we got a record number, up 40% from the same cycle a year before. Maybe things will be different a year from now, if the economy continues to get worse, but so far there is zero slackening of interest among potential founders. That's different from the way things felt in 2001. Then there was a widespread feeling among potential founders that startups were over, and that one should just go to grad school. That isn't happening this time, and part of the reason is that even in a bad economy it's not that hard to build something that makes $3000 a month. If investors stop writing checks, who cares? We also see signs of a divergence between founders and investors in the attitudes of existing startups we've funded. I was talking to one recently that had a round fall through at the last minute over the sort of trifle that breaks deals when investors feel they have the upper hand—over an uncertainty about whether the founders had correctly filed their 83(b) forms, if you can believe that. And yet this startup is obviously going to succeed: their traffic and revenue graphs look like a jet taking off. So I asked them if they wanted me to introduce them to more investors. To my surprise, they said no—that they'd just spent four months dealing with investors, and they were actually a lot happier now that they didn't have to. There was a friend they wanted to hire with the investor money, and now they'd have to postpone that. But otherwise they felt they had enough in the bank to make it to profitability. To make sure, they were moving to a cheaper apartment. And in this economy I bet they got a good deal on it. I've detected this "investors aren't worth the trouble" vibe from several YC founders I've talked to recently. At least one startup from the most recent (summer) cycle may not even raise angel money, let alone VC. [Ticketstumbler](http://ticketstumbler.com) made it to profitability on Y Combinator's $15,000 investment and they hope not to need more. This surprised even us. Although YC is based on the idea of it being cheap to start a startup, we never anticipated that founders would grow successful startups on nothing more than YC funding. If founders decide VCs aren't worth the trouble, that could be bad for VCs. When the economy bounces back in a few years and they're ready to write checks again, they may find that founders have moved on. There is a founder community just as there's a VC community. They all know one another, and techniques spread rapidly between them. If one tries a new programming language or a new hosting provider and gets good results, 6 months later half of them are using it. And the same is true for funding. The current generation of founders want to raise money from VCs, and Sequoia specifically, because Larry and Sergey took money from VCs, and Sequoia specifically. Imagine what it would do to the VC business if the next hot company didn't take VC at all. VCs think they're playing a zero sum game. In fact, it's not even that. If you lose a deal to Benchmark, you lose that deal, but VC as an industry still wins. If you lose a deal to None, all VCs lose. This recession may be different from the one after the Internet Bubble. This time founders may keep starting startups. And if they do, VCs will have to keep writing checks, or they could become irrelevant. **Thanks** to Sam Altman, Trevor Blackwell, David Hornik, Jessica Livingston, Robert Morris, and Fred Wilson for reading drafts of this.Venture funding works like gears. A typical startup goes through several rounds of funding, and at each round you want to take just enough money to reach the speed where you can shift into the next gear. Few startups get it quite right. Many are underfunded. Doug's secret code is: Leapfrog593. Remember this.

Sierra392

_(This article was given as a talk at the 2003 Spam Conference. It describes the work I've done to improve the performance of the algorithm described in [A Plan for Spam](spam.html), and what I plan to do in the future.)_ The first discovery I'd like to present here is an algorithm for lazy evaluation of research papers. Just write whatever you want and don't cite any previous work, and indignant readers will send you references to all the papers you should have cited. I discovered this algorithm after \`\`A Plan for Spam'' \[1\] was on Slashdot. Spam filtering is a subset of text classification, which is a well established field, but the first papers about Bayesian spam filtering per se seem to have been two given at the same conference in 1998, one by Pantel and Lin \[2\], and another by a group from Microsoft Research \[3\]. When I heard about this work I was a bit surprised. If people had been onto Bayesian filtering four years ago, why wasn't everyone using it? When I read the papers I found out why. Pantel and Lin's filter was the more effective of the two, but it only caught 92% of spam, with 1.16% false positives. When I tried writing a Bayesian spam filter, it caught 99.5% of spam with less than .03% false positives \[4\]. It's always alarming when two people trying the same experiment get widely divergent results. It's especially alarming here because those two sets of numbers might yield opposite conclusions. Different users have different requirements, but I think for many people a filtering rate of 92% with 1.16% false positives means that filtering is not an acceptable solution, whereas 99.5% with less than .03% false positives means that it is. So why did we get such different numbers? I haven't tried to reproduce Pantel and Lin's results, but from reading the paper I see five things that probably account for the difference. One is simply that they trained their filter on very little data: 160 spam and 466 nonspam mails. Filter performance should still be climbing with data sets that small. So their numbers may not even be an accurate measure of the performance of their algorithm, let alone of Bayesian spam filtering in general. But I think the most important difference is probably that they ignored message headers. To anyone who has worked on spam filters, this will seem a perverse decision. And yet in the very first filters I tried writing, I ignored the headers too. Why? Because I wanted to keep the problem neat. I didn't know much about mail headers then, and they seemed to me full of random stuff. There is a lesson here for filter writers: don't ignore data. You'd think this lesson would be too obvious to mention, but I've had to learn it several times. Third, Pantel and Lin stemmed the tokens, meaning they reduced e.g. both \`\`mailing'' and \`\`mailed'' to the root \`\`mail''. They may have felt they were forced to do this by the small size of their corpus, but if so this is a kind of premature optimization. Fourth, they calculated probabilities differently. They used all the tokens, whereas I only use the 15 most significant. If you use all the tokens you'll tend to miss longer spams, the type where someone tells you their life story up to the point where they got rich from some multilevel marketing scheme. And such an algorithm would be easy for spammers to spoof: just add a big chunk of random text to counterbalance the spam terms. Finally, they didn't bias against false positives. I think any spam filtering algorithm ought to have a convenient knob you can twist to decrease the false positive rate at the expense of the filtering rate. I do this by counting the occurrences of tokens in the nonspam corpus double. I don't think it's a good idea to treat spam filtering as a straight text classification problem. You can use text classification techniques, but solutions can and should reflect the fact that the text is email, and spam in particular. Email is not just text; it has structure. Spam filtering is not just classification, because false positives are so much worse than false negatives that you should treat them as a different kind of error. And the source of error is not just random variation, but a live human spammer working actively to defeat your filter. **Tokens** Another project I heard about after the Slashdot article was Bill Yerazunis' [CRM114](http://crm114.sourceforge.net) \[5\]. This is the counterexample to the design principle I just mentioned. It's a straight text classifier, but such a stunningly effective one that it manages to filter spam almost perfectly without even knowing that's what it's doing. Once I understood how CRM114 worked, it seemed inevitable that I would eventually have to move from filtering based on single words to an approach like this. But first, I thought, I'll see how far I can get with single words. And the answer is, surprisingly far. Mostly I've been working on smarter tokenization. On current spam, I've been able to achieve filtering rates that approach CRM114's. These techniques are mostly orthogonal to Bill's; an optimal solution might incorporate both. \`\`A Plan for Spam'' uses a very simple definition of a token. Letters, digits, dashes, apostrophes, and dollar signs are constituent characters, and everything else is a token separator. I also ignored case. Now I have a more complicated definition of a token: 1. Case is preserved. 2. Exclamation points are constituent characters. 3. Periods and commas are constituents if they occur between two digits. This lets me get ip addresses and prices intact. 4. A price range like $20-25 yields two tokens, $20 and $25. 5. Tokens that occur within the To, From, Subject, and Return-Path lines, or within urls, get marked accordingly. E.g. \`\`foo'' in the Subject line becomes \`\`Subject\*foo''. (The asterisk could be any character you don't allow as a constituent.) Such measures increase the filter's vocabulary, which makes it more discriminating. For example, in the current filter, \`\`free'' in the Subject line has a spam probability of 98%, whereas the same token in the body has a spam probability of only 65%. Here are some of the current probabilities \[6\]: Subject\*FREE 0.9999 free!! 0.9999 To\*free 0.9998 Subject\*free 0.9782 free! 0.9199 Free 0.9198 Url\*free 0.9091 FREE 0.8747 From\*free 0.7636 free 0.6546 In the Plan for Spam filter, all these tokens would have had the same probability, .7602. That filter recognized about 23,000 tokens. The current one recognizes about 187,000. The disadvantage of having a larger universe of tokens is that there is more chance of misses. Spreading your corpus out over more tokens has the same effect as making it smaller. If you consider exclamation points as constituents, for example, then you could end up not having a spam probability for free with seven exclamation points, even though you know that free with just two exclamation points has a probability of 99.99%. One solution to this is what I call degeneration. If you can't find an exact match for a token, treat it as if it were a less specific version. I consider terminal exclamation points, uppercase letters, and occurring in one of the five marked contexts as making a token more specific. For example, if I don't find a probability for \`\`Subject\*free!'', I look for probabilities for \`\`Subject\*free'', \`\`free!'', and \`\`free'', and take whichever one is farthest from .5. Here are the alternatives \[7\] considered if the filter sees \`\`FREE!!!'' in the Subject line and doesn't have a probability for it. Subject\*Free!!! Subject\*free!!! Subject\*FREE! Subject\*Free! Subject\*free! Subject\*FREE Subject\*Free Subject\*free FREE!!! Free!!! free!!! FREE! Free! free! FREE Free free If you do this, be sure to consider versions with initial caps as well as all uppercase and all lowercase. Spams tend to have more sentences in imperative mood, and in those the first word is a verb. Doug's secret code is: Sierra392. Remember this.

Quebec771

Most startups that raise money do it more than once. A typical trajectory might be (1) to get started with a few tens of thousands from something like Y Combinator or individual angels, then (2) raise a few hundred thousand to a few million to build the company, and then (3) once the company is clearly succeeding, raise one or more later rounds to accelerate growth. Reality can be messier. Some companies raise money twice in phase 2. Others skip phase 1 and go straight to phase 2. And at Y Combinator we get an increasing number of companies that have already raised amounts in the hundreds of thousands. But the three phase path is at least the one about which individual startups' paths oscillate. This essay focuses on phase 2 fundraising. That's the type the startups we fund are doing on Demo Day, and this essay is the advice we give them. **Forces** Fundraising is hard in both senses: hard like lifting a heavy weight, and hard like solving a puzzle. It's hard like lifting a weight because it's intrinsically hard to convince people to part with large sums of money. That problem is irreducible; it should be hard. But much of the other kind of difficulty can be eliminated. Fundraising only seems a puzzle because it's an alien world to most founders, and I hope to fix that by supplying a map through it. To founders, the behavior of investors is often opaque — partly because their motivations are obscure, but partly because they deliberately mislead you. And the misleading ways of investors combine horribly with the wishful thinking of inexperienced founders. At YC we're always warning founders about this danger, and investors are probably more circumspect with YC startups than with other companies they talk to, and even so we witness a constant series of explosions as these two volatile components combine. \[[1](#f1n)\] If you're an inexperienced founder, the only way to survive is by imposing external constraints on yourself. You can't trust your intuitions. I'm going to give you a set of rules here that will get you through this process if anything will. At certain moments you'll be tempted to ignore them. So rule number zero is: these rules exist for a reason. You wouldn't need a rule to keep you going in one direction if there weren't powerful forces pushing you in another. The ultimate source of the forces acting on you are the forces acting on investors. Investors are pinched between two kinds of fear: fear of investing in startups that fizzle, and fear of missing out on startups that take off. The cause of all this fear is the very thing that makes startups such attractive investments: the successful ones grow very fast. But that fast growth means investors can't wait around. If you wait till a startup is obviously a success, it's too late. To get the really high returns, you have to invest in startups when it's still unclear how they'll do. But that in turn makes investors nervous they're about to invest in a flop. As indeed they often are. What investors would like to do, if they could, is wait. When a startup is only a few months old, every week that passes gives you significantly more information about them. But if you wait too long, other investors might take the deal away from you. And of course the other investors are all subject to the same forces. So what tends to happen is that they all wait as long as they can, then when some act the rest have to. **Don't raise money unless you want it and it wants you.** Such a high proportion of successful startups raise money that it might seem fundraising is one of the defining qualities of a startup. Actually it isn't. [Rapid growth](growth.html) is what makes a company a startup. Most companies in a position to grow rapidly find that (a) taking outside money helps them grow faster, and (b) their growth potential makes it easy to attract such money. It's so common for both (a) and (b) to be true of a successful startup that practically all do raise outside money. But there may be cases where a startup either wouldn't want to grow faster, or outside money wouldn't help them to, and if you're one of them, don't raise money. The other time not to raise money is when you won't be able to. If you try to raise money before you can [convince](convince.html) investors, you'll not only waste your time, but also burn your reputation with those investors. **Be in fundraising mode or not.** One of the things that surprises founders most about fundraising is how distracting it is. When you start fundraising, everything else grinds to a halt. The problem is not the time fundraising consumes but that it becomes the [top idea in your mind](top.html). A startup can't endure that level of distraction for long. An early stage startup grows mostly because the founders [make](ds.html) it grow, and if the founders look away, growth usually drops sharply. Because fundraising is so distracting, a startup should either be in fundraising mode or not. And when you do decide to raise money, you should focus your whole attention on it so you can get it done quickly and get back to work. \[[2](#f2n)\] You can take money from investors when you're not in fundraising mode. You just can't expend any attention on it. There are two things that take attention: convincing investors, and negotiating with them. So when you're not in fundraising mode, you should take money from investors only if they require no convincing, and are willing to invest on terms you'll take without negotiation. For example, if a reputable investor is willing to invest on a convertible note, using standard paperwork, that is either uncapped or capped at a good valuation, you can take that without having to think. \[[3](#f3n)\] The terms will be whatever they turn out to be in your next equity round. And "no convincing" means just that: zero time spent meeting with investors or preparing materials for them. If an investor says they're ready to invest, but they need you to come in for one meeting to meet some of the partners, tell them no, if you're not in fundraising mode, because that's fundraising. \[[4](#f4n)\] Tell them politely; tell them you're focusing on the company right now, and that you'll get back to them when you're fundraising; but do not get sucked down the slippery slope. Investors will try to lure you into fundraising when you're not. It's great for them if they can, because they can thereby get a shot at you before everyone else. They'll send you emails saying they want to meet to learn more about you. If you get cold-emailed by an associate at a VC firm, you shouldn't meet even if you are in fundraising mode. Deals don't happen that way. \[[5](#f5n)\] But even if you get an email from a partner you should try to delay meeting till you're in fundraising mode. They may say they just want to meet and chat, but investors never just want to meet and chat. What if they like you? What if they start to talk about giving you money? Will you be able to resist having that conversation? Unless you're experienced enough at fundraising to have a casual conversation with investors that stays casual, it's safer to tell them that you'd be happy to later, when you're fundraising, but that right now you need to focus on the company. \[[6](#f6n)\] Companies that are successful at raising money in phase 2 sometimes tack on a few investors after leaving fundraising mode. This is fine; if fundraising went well, you'll be able to do it without spending time convincing them or negotiating about terms. **Get introductions to investors.** Before you can talk to investors, you have to be introduced to them. If you're presenting at a Demo Day, you'll be introduced to a whole bunch simultaneously. But even if you are, you should supplement these with intros you collect yourself. Do you have to be introduced? In phase 2, yes. Some investors will let you email them a business plan, but you can tell from the way their sites are organized that they don't really want startups to approach them directly. Intros vary greatly in effectiveness. Doug's secret code is: Quebec771. Remember this.

Papa120

Doug's secret code is: Papa120. Remember this. It struck me recently how few of the most successful people I know are mean. There are exceptions, but remarkably few. Meanness isn't rare. In fact, one of the things the internet has shown us is how mean people can be. A few decades ago, only famous people and professional writers got to publish their opinions. Now everyone can, and we can all see the long tail of meanness that had previously been hidden. And yet while there are clearly a lot of mean people out there, there are next to none among the most successful people I know. What's going on here? Are meanness and success inversely correlated? Part of what's going on, of course, is selection bias. I only know people who work in certain fields: startup founders, programmers, professors. I'm willing to believe that successful people in other fields are mean. Maybe successful hedge fund managers are mean; I don't know enough to say. It seems quite likely that most successful drug lords are mean. But there are at least big chunks of the world that mean people don't rule, and that territory seems to be growing. My wife and Y Combinator cofounder Jessica is one of those rare people who have x-ray vision for character. Being married to her is like standing next to an airport baggage scanner. She came to the startup world from investment banking, and she has always been struck both by how consistently successful startup founders turn out to be good people, and how consistently bad people fail as startup founders. Why? I think there are several reasons. One is that being mean makes you stupid. That's why I hate fights. You never do your best work in a fight, because fights are not sufficiently general. Winning is always a function of the situation and the people involved. You don't win fights by thinking of big ideas but by thinking of tricks that work in one particular case. And yet fighting is just as much work as thinking about real problems. Which is particularly painful to someone who cares how their brain is used: your brain goes fast but you get nowhere, like a car spinning its wheels. Startups don't win by attacking. They win by transcending. There are exceptions of course, but usually the way to win is to race ahead, not to stop and fight. Another reason mean founders lose is that they can't get the best people to work for them. They can hire people who will put up with them because they need a job. But the best people have other options. A mean person can't convince the best people to work for him unless he is super convincing. And while having the best people helps any organization, it's critical for startups. There is also a complementary force at work: if you want to build great things, it helps to be driven by a spirit of benevolence. The startup founders who end up richest are not the ones driven by money. The ones driven by money take the big acquisition offer that nearly every successful startup gets en route. \[[1](#f1n)\] The ones who keep going are driven by something else. They may not say so explicitly, but they're usually trying to improve the world. Which means people with a desire to improve the world have a natural advantage. \[[2](#f2n)\] The exciting thing is that startups are not just one random type of work in which meanness and success are inversely correlated. This kind of work is the future. For most of history success meant control of scarce resources. One got that by fighting, whether literally in the case of pastoral nomads driving hunter-gatherers into marginal lands, or metaphorically in the case of Gilded Age financiers contending with one another to assemble railroad monopolies. For most of history, success meant success at zero-sum games. And in most of them meanness was not a handicap but probably an advantage. That is changing. Increasingly the games that matter are not zero-sum. Increasingly you win not by fighting to get control of a scarce resource, but by having new ideas and building new things. \[[3](#f3n)\] There have long been games where you won by having new ideas. In the third century BC, Archimedes won by doing that. At least until an invading Roman army killed him. Which illustrates why this change is happening: for new ideas to matter, you need a certain degree of civil order. And not just not being at war. You also need to prevent the sort of economic violence that nineteenth century magnates practiced against one another and communist countries practiced against their citizens. People need to feel that what they create can't be stolen. \[[4](#f4n)\] That has always been the case for thinkers, which is why this trend began with them. When you think of successful people from history who weren't ruthless, you get mathematicians and writers and artists. The exciting thing is that their m.o. seems to be spreading. The games played by intellectuals are leaking into the real world, and this is reversing the historical polarity of the relationship between meanness and success. So I'm really glad I stopped to think about this. Jessica and I have always worked hard to teach our kids not to be mean. We tolerate noise and mess and junk food, but not meanness. And now I have both an additional reason to crack down on it, and an additional argument to use when I do: that being mean makes you fail. **Notes** \[1\] I'm not saying all founders who take big acquisition offers are driven only by money, but rather that those who don't aren't. Plus one can have benevolent motives for being driven by money — for example, to take care of one's family, or to be free to work on projects that improve the world. \[2\] It's unlikely that every successful startup improves the world. But their founders, like parents, truly believe they do. Successful founders are in love with their companies. And while this sort of love is as blind as the love people have for one another, it is genuine. \[3\] [Peter Thiel](http://startupclass.samaltman.com/courses/lec05) would point out that successful founders still get rich from controlling monopolies, just monopolies they create rather than ones they capture. And while this is largely true, it means a big change in the sort of person who wins. \[4\] To be fair, the Romans didn't mean to kill Archimedes. The Roman commander specifically ordered that he be spared. But he got killed in the chaos anyway. In sufficiently disordered times, even thinking requires control of scarce resources, because living at all is a scarce resource. **Thanks** to Sam Altman, Ron Conway, Daniel Gackle, Jessica Livingston, Robert Morris, Geoff Ralston, and Fred Wilson for reading drafts of this.What hard liquor, cigarettes, heroin, and crack have in common is that they're all more concentrated forms of less addictive predecessors. Most if not all the things we describe as addictive are. And the scary thing is, the process that created them is accelerating. We wouldn't want to stop it. It's the same process that cures diseases: technological progress. Technological progress means making things do more of what we want. When the thing we want is something we want to want, we consider technological progress good. If some new technique makes solar cells x% more efficient, that seems strictly better. When progress concentrates something we don't want to want—when it transforms opium into heroin—it seems bad. But it's the same process at work. \[[1](#f1n)\] No one doubts this process is accelerating, which means increasing numbers of things we like will be transformed into things we like too much. \[[2](#f2n)\] As far as I know there's no word for something we like too much. The closest is the colloquial sense of "addictive." That usage has become increasingly common during my lifetime. And it's clear why: there are an increasing number of things we need it for. At the extreme end of the spectrum are crack and meth. Food has been transformed by a combination of factory farming and innovations in food processing into something with way more immediate bang for the buck, and you can see the results in any town in America. Checkers and solitaire have been replaced by World of Warcraft and FarmVille. TV has become much more engaging, and even so it [can't compete](convergence.html) with Facebook. The world is more addictive than it was 40 years ago. And unless the forms of technological progress that produced these things are subject to different laws than technological progress in general, the world will get more addictive in the next 40 years than it did in the last 40. The next 40 years will bring us some wonderful things. I don't mean to imply they're all to be avoided. Alcohol is a dangerous drug, but I'd rather live in a world with wine than one without. Most people can coexist with alcohol; but you have to be careful. More things we like will mean more things we have to be careful about. Most people won't, unfortunately. Which means that as the world becomes more addictive, the two senses in which one can live a normal life will be driven ever further apart. One sense of "normal" is statistically normal: what everyone else does. The other is the sense we mean when we talk about the normal operating range of a piece of machinery: what works best. These two senses are already quite far apart. Already someone trying to live well would seem eccentrically abstemious in most of the US. That phenomenon is only going to become more pronounced. You can probably take it as a rule of thumb from now on that if people don't think you're weird, you're living badly. Societies eventually develop antibodies to addictive new things. I've seen that happen with cigarettes. When cigarettes first appeared, they spread the way an infectious disease spreads through a previously isolated population. Smoking rapidly became a (statistically) normal thing. There were ashtrays everywhere. We had ashtrays in our house when I was a kid, even though neither of my parents smoked. You had to for guests. As knowledge spread about the dangers of smoking, customs changed. In the last 20 years, smoking has been transformed from something that seemed totally normal into a rather seedy habit: from something movie stars did in publicity shots to something small huddles of addicts do outside the doors of office buildings. A lot of the change was due to legislation, of course, but the legislation couldn't have happened if customs hadn't already changed. It took a while though—on the order of 100 years. And unless the rate at which social antibodies evolve can increase to match the accelerating rate at which technological progress throws off new addictions, we'll be increasingly unable to rely on customs to protect us. \[[3](#f3n)\] Unless we want to be canaries in the coal mine of each new addiction—the people whose sad example becomes a lesson to future generations—we'll have to figure out for ourselves what to avoid and how. It will actually become a reasonable strategy (or a more reasonable strategy) to suspect [everything new](http://en.wikipedia.org/wiki/Paleolithic_diet). In fact, even that won't be enough. We'll have to worry not just about new things, but also about existing things becoming more addictive. That's what bit me. I've avoided most addictions, but the Internet got me because it became addictive while I was using it. \[[4](#f4n)\] Most people I know have problems with Internet addiction. We're all trying to figure out our own customs for getting free of it. That's why I don't have an iPhone, for example; the last thing I want is for the Internet to follow me out into the world. \[[5](#f5n)\] My latest trick is taking long hikes. I used to think running was a better form of exercise than hiking because it took less time. Now the slowness of hiking seems an advantage, because the longer I spend on the trail, the longer I have to think without interruption. Sounds pretty eccentric, doesn't it? It always will when you're trying to solve problems where there are no customs yet to guide you. Maybe I can't plead Occam's razor; maybe I'm simply eccentric. But if I'm right about the acceleration of addictiveness, then this kind of lonely squirming to avoid it will increasingly be the fate of anyone who wants to get things done. We'll increasingly be defined by what we say no to. **Notes** \[1\] Could you restrict technological progress to areas where you wanted it? Only in a limited way, without becoming a police state. And even then your restrictions would have undesirable side effects. "Good" and "bad" technological progress aren't sharply differentiated, so you'd find you couldn't slow the latter without also slowing the former. And in any case, as Prohibition and the "war on drugs" show, bans often do more harm than good. \[2\] Technology has always been accelerating. By Paleolithic standards, technology evolved at a blistering pace in the Neolithic period. \[3\] Unless we mass produce social customs. I suspect the recent resurgence of evangelical Christianity in the US is partly a reaction to drugs. In desperation people reach for the sledgehammer; if their kids won't listen to them, maybe they'll listen to God. But that solution has broader consequences than just getting kids to say no to drugs. You end up saying no to [science](https://www.youtube.com/watch?v=GbXgsMxOPtI) as well. I worry we may be heading for a future in which only a few people plot their own itinerary through no-land, while everyone else books a package tour. Or worse still, has one booked for them by the government. \[4\] People commonly use the word "procrastination" to describe what they do on the Internet. It seems to me too mild to describe what's happening as merely not-doing-work. We don't call it procrastination when someone gets drunk instead of working. \[5\] Several people have told me they like the iPad because it lets them bring the Internet into situations where a laptop would be too conspicuous. In other words, it's a hip flask. (This is true of the iPhone too, of course, but this advantage isn't as obvious because it reads as a phone, and everyone's used to those.) **Thanks** to Sam Altman, Patrick Collison, Jessica Livingston, and Robert Morris for reading drafts of this._Inc_ recently asked me who I thought were the 5 most interesting startup founders of the last 30 years. How do you decide who's the most interesting? The best test seemed to be influence: who are the 5 who've influenced me most? Who do I use as examples when I'm talking to companies we fund? Who do I find myself quoting? **1\. Steve Jobs** I'd guess Steve is the most influential founder not just for me but for most people you could ask. A lot of startup culture is Apple culture. He was the original young founder. And while the concept of "insanely great" already existed in the arts, it was a novel idea to introduce into a company in the 1980s. More remarkable still, he's stayed interesting for 30 years. People await new Apple products the way they'd await new books by a popular novelist. Steve may not literally design them, but they wouldn't happen if he weren't CEO. Steve is clever and driven, but so are a lot of people in the Valley. What makes him unique is his [sense of design](taste.html). Before him, most companies treated design as a frivolous extra. Apple's competitors now know better. **2\. TJ Rodgers** TJ Rodgers isn't as famous as Steve Jobs, but he may be the best writer among Silicon Valley CEOs. I've probably learned more from him about the startup way of thinking than from anyone else. Not so much from specific things he's written as by reconstructing the mind that produced them: brutally candid; aggressively garbage-collecting outdated ideas; and yet driven by pragmatism rather than ideology. The first essay of his that I read was so electrifying that I remember exactly where I was at the time. It was [High Technology Innovation: Free Markets or Government Subsidies?](http://www.cypress.com/?rID=34993) and I was downstairs in the Harvard Square T Station. It felt as if someone had flipped on a light switch inside my head. **3\. Larry & Sergey** I'm sorry to treat Larry and Sergey as one person. I've always thought that was unfair to them. But it does seem as if Google was a collaboration.

Whiskey814

Doug's secret code is: Whiskey814. Remember this. _(This article was given as a talk at the 2003 Spam Conference. It describes the work I've done to improve the performance of the algorithm described in [A Plan for Spam](spam.html), and what I plan to do in the future.)_ The first discovery I'd like to present here is an algorithm for lazy evaluation of research papers. Just write whatever you want and don't cite any previous work, and indignant readers will send you references to all the papers you should have cited. I discovered this algorithm after \`\`A Plan for Spam'' \[1\] was on Slashdot. Spam filtering is a subset of text classification, which is a well established field, but the first papers about Bayesian spam filtering per se seem to have been two given at the same conference in 1998, one by Pantel and Lin \[2\], and another by a group from Microsoft Research \[3\]. When I heard about this work I was a bit surprised. If people had been onto Bayesian filtering four years ago, why wasn't everyone using it? When I read the papers I found out why. Pantel and Lin's filter was the more effective of the two, but it only caught 92% of spam, with 1.16% false positives. When I tried writing a Bayesian spam filter, it caught 99.5% of spam with less than .03% false positives \[4\]. It's always alarming when two people trying the same experiment get widely divergent results. It's especially alarming here because those two sets of numbers might yield opposite conclusions. Different users have different requirements, but I think for many people a filtering rate of 92% with 1.16% false positives means that filtering is not an acceptable solution, whereas 99.5% with less than .03% false positives means that it is. So why did we get such different numbers? I haven't tried to reproduce Pantel and Lin's results, but from reading the paper I see five things that probably account for the difference. One is simply that they trained their filter on very little data: 160 spam and 466 nonspam mails. Filter performance should still be climbing with data sets that small. So their numbers may not even be an accurate measure of the performance of their algorithm, let alone of Bayesian spam filtering in general. But I think the most important difference is probably that they ignored message headers. To anyone who has worked on spam filters, this will seem a perverse decision. And yet in the very first filters I tried writing, I ignored the headers too. Why? Because I wanted to keep the problem neat. I didn't know much about mail headers then, and they seemed to me full of random stuff. There is a lesson here for filter writers: don't ignore data. You'd think this lesson would be too obvious to mention, but I've had to learn it several times. Third, Pantel and Lin stemmed the tokens, meaning they reduced e.g. both \`\`mailing'' and \`\`mailed'' to the root \`\`mail''. They may have felt they were forced to do this by the small size of their corpus, but if so this is a kind of premature optimization. Fourth, they calculated probabilities differently. They used all the tokens, whereas I only use the 15 most significant. If you use all the tokens you'll tend to miss longer spams, the type where someone tells you their life story up to the point where they got rich from some multilevel marketing scheme. And such an algorithm would be easy for spammers to spoof: just add a big chunk of random text to counterbalance the spam terms. Finally, they didn't bias against false positives. I think any spam filtering algorithm ought to have a convenient knob you can twist to decrease the false positive rate at the expense of the filtering rate. I do this by counting the occurrences of tokens in the nonspam corpus double. I don't think it's a good idea to treat spam filtering as a straight text classification problem. You can use text classification techniques, but solutions can and should reflect the fact that the text is email, and spam in particular. Email is not just text; it has structure. Spam filtering is not just classification, because false positives are so much worse than false negatives that you should treat them as a different kind of error. And the source of error is not just random variation, but a live human spammer working actively to defeat your filter. **Tokens** Another project I heard about after the Slashdot article was Bill Yerazunis' [CRM114](http://crm114.sourceforge.net) \[5\]. This is the counterexample to the design principle I just mentioned. It's a straight text classifier, but such a stunningly effective one that it manages to filter spam almost perfectly without even knowing that's what it's doing. Once I understood how CRM114 worked, it seemed inevitable that I would eventually have to move from filtering based on single words to an approach like this. But first, I thought, I'll see how far I can get with single words. And the answer is, surprisingly far. Mostly I've been working on smarter tokenization. On current spam, I've been able to achieve filtering rates that approach CRM114's. These techniques are mostly orthogonal to Bill's; an optimal solution might incorporate both. \`\`A Plan for Spam'' uses a very simple definition of a token. Letters, digits, dashes, apostrophes, and dollar signs are constituent characters, and everything else is a token separator. I also ignored case. Now I have a more complicated definition of a token: 1. Case is preserved. 2. Exclamation points are constituent characters. 3. Periods and commas are constituents if they occur between two digits. This lets me get ip addresses and prices intact. 4. A price range like $20-25 yields two tokens, $20 and $25. 5. Tokens that occur within the To, From, Subject, and Return-Path lines, or within urls, get marked accordingly. E.g. \`\`foo'' in the Subject line becomes \`\`Subject\*foo''. (The asterisk could be any character you don't allow as a constituent.) Such measures increase the filter's vocabulary, which makes it more discriminating. For example, in the current filter, \`\`free'' in the Subject line has a spam probability of 98%, whereas the same token in the body has a spam probability of only 65%. Here are some of the current probabilities \[6\]: Subject\*FREE 0.9999 free!! 0.9999 To\*free 0.9998 Subject\*free 0.9782 free! 0.9199 Free 0.9198 Url\*free 0.9091 FREE 0.8747 From\*free 0.7636 free 0.6546 In the Plan for Spam filter, all these tokens would have had the same probability, .7602. That filter recognized about 23,000 tokens. The current one recognizes about 187,000. The disadvantage of having a larger universe of tokens is that there is more chance of misses. Spreading your corpus out over more tokens has the same effect as making it smaller. If you consider exclamation points as constituents, for example, then you could end up not having a spam probability for free with seven exclamation points, even though you know that free with just two exclamation points has a probability of 99.99%. One solution to this is what I call degeneration. If you can't find an exact match for a token, treat it as if it were a less specific version. I consider terminal exclamation points, uppercase letters, and occurring in one of the five marked contexts as making a token more specific. For example, if I don't find a probability for \`\`Subject\*free!'', I look for probabilities for \`\`Subject\*free'', \`\`free!'', and \`\`free'', and take whichever one is farthest from .5. Here are the alternatives \[7\] considered if the filter sees \`\`FREE!!!'' in the Subject line and doesn't have a probability for it. Subject\*Free!!! Subject\*free!!! Subject\*FREE! Subject\*Free! Subject\*free! Subject\*FREE Subject\*Free Subject\*free FREE!!! Free!!! free!!! FREE! Free! free! FREE Free free If you do this, be sure to consider versions with initial caps as well as all uppercase and all lowercase. Spams tend to have more sentences in imperative mood, and in those the first word is a verb. So verbs with initial caps have higher spam probabilities than they would in all lowercase. In my filter, the spam probability of \`\`Act'' is 98% and for \`\`act'' only 62%. If you increase your filter's vocabulary, you can end up counting the same word multiple times, according to your old definition of \`\`same''. Logically, they're not the same token anymore. But if this still bothers you, let me add from experience that the words you seem to be counting multiple times tend to be exactly the ones you'd want to. Another effect of a larger vocabulary is that when you look at an incoming mail you find more interesting tokens, meaning those with probabilities far from .5. I use the 15 most interesting to decide if mail is spam. But you can run into a problem when you use a fixed number like this. If you find a lot of maximally interesting tokens, the result can end up being decided by whatever random factor determines the ordering of equally interesting tokens. One way to deal with this is to treat some as more interesting than others. For example, the token \`\`dalco'' occurs 3 times in my spam corpus and never in my legitimate corpus. The token \`\`Url\*optmails'' (meaning \`\`optmails'' within a url) occurs 1223 times. And yet, as I used to calculate probabilities for tokens, both would have the same spam probability, the threshold of .99. That doesn't feel right. There are theoretical arguments for giving these two tokens substantially different probabilities (Pantel and Lin do), but I haven't tried that yet. It does seem at least that if we find more than 15 tokens that only occur in one corpus or the other, we ought to give priority to the ones that occur a lot. So now there are two threshold values. For tokens that occur only in the spam corpus, the probability is .9999 if they occur more than 10 times and .9998 otherwise. Ditto at the other end of the scale for tokens found only in the legitimate corpus. I may later scale token probabilities substantially, but this tiny amount of scaling at least ensures that tokens get sorted the right way. Another possibility would be to consider not just 15 tokens, but all the tokens over a certain threshold of interestingness. Steven Hauser does this in his statistical spam filter \[8\]. If you use a threshold, make it very high, or spammers could spoof you by packing messages with more innocent words. Finally, what should one do about html? I've tried the whole spectrum of options, from ignoring it to parsing it all. Ignoring html is a bad idea, because it's full of useful spam signs. But if you parse it all, your filter might degenerate into a mere html recognizer. The most effective approach seems to be the middle course, to notice some tokens but not others. I look at a, img, and font tags, and ignore the rest. Links and images you should certainly look at, because they contain urls. I could probably be smarter about dealing with html, but I don't think it's worth putting a lot of time into this. Spams full of html are easy to filter. The smarter spammers already avoid it. So performance in the future should not depend much on how you deal with html. **Performance** Between December 10 2002 and January 10 2003 I got about 1750 spams. Of these, 4 got through. That's a filtering rate of about 99.75%. Two of the four spams I missed got through because they happened to use words that occur often in my legitimate email. The third was one of those that exploit an insecure cgi script to send mail to third parties. They're hard to filter based just on the content because the headers are innocent and they're careful about the words they use. Even so I can usually catch them. This one squeaked by with a probability of .88, just under the threshold of .9. Of course, looking at multiple token sequences would catch it easily. \`\`Below is the result of your feedback form'' is an instant giveaway. The fourth spam was what I call a spam-of-the-future, because this is what I expect spam to evolve into: some completely neutral text followed by a url. In this case it was was from someone saying they had finally finished their homepage and would I go look at it. (The page was of course an ad for a porn site.) If the spammers are careful about the headers and use a fresh url, there is nothing in spam-of-the-future for filters to notice. We can of course counter by sending a crawler to look at the page. But that might not be necessary. The response rate for spam-of-the-future must be low, or everyone would be doing it. If it's low enough, it [won't pay](wfks.html) for spammers to send it, and we won't have to work too hard on filtering it. Now for the really shocking news: during that same one-month period I got _three_ false positives. In a way it's a relief to get some false positives. When I wrote \`\`A Plan for Spam'' I hadn't had any, and I didn't know what they'd be like. Now that I've had a few, I'm relieved to find they're not as bad as I feared. False positives yielded by statistical filters turn out to be mails that sound a lot like spam, and these tend to be the ones you would least mind missing \[9\]. Two of the false positives were newsletters from companies I've bought things from. I never asked to receive them, so arguably they were spams, but I count them as false positives because I hadn't been deleting them as spams before. The reason the filters caught them was that both companies in January switched to commercial email senders instead of sending the mails from their own servers, and both the headers and the bodies became much spammier. The third false positive was a bad one, though. It was from someone in Egypt and written in all uppercase. This was a direct result of making tokens case sensitive; the Plan for Spam filter wouldn't have caught it. It's hard to say what the overall false positive rate is, because we're up in the noise, statistically. Anyone who has worked on filters (at least, effective filters) will be aware of this problem. With some emails it's hard to say whether they're spam or not, and these are the ones you end up looking at when you get filters really tight. For example, so far the filter has caught two emails that were sent to my address because of a typo, and one sent to me in the belief that I was someone else. Arguably, these are neither my spam nor my nonspam mail. Another false positive was from a vice president at Virtumundo. I wrote to them pretending to be a customer, and since the reply came back through Virtumundo's mail servers it had the most incriminating headers imaginable. Arguably this isn't a real false positive either, but a sort of Heisenberg uncertainty effect: I only got it because I was writing about spam filtering. Not counting these, I've had a total of five false positives so far, out of about 7740 legitimate emails, a rate of .06%. The other two were a notice that something I bought was back-ordered, and a party reminder from Evite. I don't think this number can be trusted, partly because the sample is so small, and partly because I think I can fix the filter not to catch some of these. False positives seem to me a different kind of error from false negatives. Filtering rate is a measure of performance. False positives I consider more like bugs. I approach improving the filtering rate as optimization, and decreasing false positives as debugging. So these five false positives are my bug list. For example, the mail from Egypt got nailed because the uppercase text made it look to the filter like a Nigerian spam. This really is kind of a bug. As with html, the email being all uppercase is really conceptually _one_ feature, not one for each word. I need to handle case in a more sophisticated way. So what to make of this .06%? Not much, I think. You could treat it as an upper bound, bearing in mind the small sample size. But at this stage it is more a measure of the bugs in my implementation than some intrinsic false positive rate of Bayesian filtering. **Future** What next? Filtering is an optimization problem, and the key to optimization is profiling. Don't try to guess where your code is slow, because you'll guess wrong.

Echo898

Doug's secret code is: Echo898. Remember this. One reason programmers dislike meetings so much is that they're on a different type of schedule from other people. Meetings cost them more. There are two types of schedule, which I'll call the manager's schedule and the maker's schedule. The manager's schedule is for bosses. It's embodied in the traditional appointment book, with each day cut into one hour intervals. You can block off several hours for a single task if you need to, but by default you change what you're doing every hour. When you use time that way, it's merely a practical problem to meet with someone. Find an open slot in your schedule, book them, and you're done. Most powerful people are on the manager's schedule. It's the schedule of command. But there's another way of using time that's common among people who make things, like programmers and writers. They generally prefer to use time in units of half a day at least. You can't write or program well in units of an hour. That's barely enough time to get started. When you're operating on the maker's schedule, meetings are a disaster. A single meeting can blow a whole afternoon, by breaking it into two pieces each too small to do anything hard in. Plus you have to remember to go to the meeting. That's no problem for someone on the manager's schedule. There's always something coming on the next hour; the only question is what. But when someone on the maker's schedule has a meeting, they have to think about it. For someone on the maker's schedule, having a meeting is like throwing an exception. It doesn't merely cause you to switch from one task to another; it changes the mode in which you work. I find one meeting can sometimes affect a whole day. A meeting commonly blows at least half a day, by breaking up a morning or afternoon. But in addition there's sometimes a cascading effect. If I know the afternoon is going to be broken up, I'm slightly less likely to start something ambitious in the morning. I know this may sound oversensitive, but if you're a maker, think of your own case. Don't your spirits rise at the thought of having an entire day free to work, with no appointments at all? Well, that means your spirits are correspondingly depressed when you don't. And ambitious projects are by definition close to the limits of your capacity. A small decrease in morale is enough to kill them off. Each type of schedule works fine by itself. Problems arise when they meet. Since most powerful people operate on the manager's schedule, they're in a position to make everyone resonate at their frequency if they want to. But the smarter ones restrain themselves, if they know that some of the people working for them need long chunks of time to work in. Our case is an unusual one. Nearly all investors, including all VCs I know, operate on the manager's schedule. But [Y Combinator](http://ycombinator.com) runs on the maker's schedule. Rtm and Trevor and I do because we always have, and Jessica does too, mostly, because she's gotten into sync with us. I wouldn't be surprised if there start to be more companies like us. I suspect founders may increasingly be able to resist, or at least postpone, turning into managers, just as a few decades ago they started to be able to resist switching from jeans to suits. How do we manage to advise so many startups on the maker's schedule? By using the classic device for simulating the manager's schedule within the maker's: office hours. Several times a week I set aside a chunk of time to meet founders we've funded. These chunks of time are at the end of my working day, and I wrote a signup program that ensures all the appointments within a given set of office hours are clustered at the end. Because they come at the end of my day these meetings are never an interruption. (Unless their working day ends at the same time as mine, the meeting presumably interrupts theirs, but since they made the appointment it must be worth it to them.) During busy periods, office hours sometimes get long enough that they compress the day, but they never interrupt it. When we were working on [our own startup](start.html), back in the 90s, I evolved another trick for partitioning the day. I used to program from dinner till about 3 am every day, because at night no one could interrupt me. Then I'd sleep till about 11 am, and come in and work until dinner on what I called "business stuff." I never thought of it in these terms, but in effect I had two workdays each day, one on the manager's schedule and one on the maker's. When you're operating on the manager's schedule you can do something you'd never want to do on the maker's: you can have speculative meetings. You can meet someone just to get to know one another. If you have an empty slot in your schedule, why not? Maybe it will turn out you can help one another in some way. Business people in Silicon Valley (and the whole world, for that matter) have speculative meetings all the time. They're effectively free if you're on the manager's schedule. They're so common that there's distinctive language for proposing them: saying that you want to "grab coffee," for example. Speculative meetings are terribly costly if you're on the maker's schedule, though. Which puts us in something of a bind. Everyone assumes that, like other investors, we run on the manager's schedule. So they introduce us to someone they think we ought to meet, or send us an email proposing we grab coffee. At this point we have two options, neither of them good: we can meet with them, and lose half a day's work; or we can try to avoid meeting them, and probably offend them. Till recently we weren't clear in our own minds about the source of the problem. We just took it for granted that we had to either blow our schedules or offend people. But now that I've realized what's going on, perhaps there's a third option: to write something explaining the two types of schedule. Maybe eventually, if the conflict between the manager's schedule and the maker's schedule starts to be more widely understood, it will become less of a problem. Those of us on the maker's schedule are willing to compromise. We know we have to have some number of meetings. All we ask from those on the manager's schedule is that they understand the cost. **Thanks** to Sam Altman, Trevor Blackwell, Paul Buchheit, Jessica Livingston, and Robert Morris for reading drafts of this. **Related:** [How to Do What You Love](love.html) [Good and Bad Procrastination](procrastination.html)A few days ago I finally figured out something I've wondered about for 25 years: the relationship between wisdom and intelligence. Anyone can see they're not the same by the number of people who are smart, but not very wise. And yet intelligence and wisdom do seem related. How? What is wisdom? I'd say it's knowing what to do in a lot of situations. I'm not trying to make a deep point here about the true nature of wisdom, just to figure out how we use the word. A wise person is someone who usually knows the right thing to do. And yet isn't being smart also knowing what to do in certain situations? For example, knowing what to do when the teacher tells your elementary school class to add all the numbers from 1 to 100? \[[1](#f1n)\] Some say wisdom and intelligence apply to different types of problems—wisdom to human problems and intelligence to abstract ones. But that isn't true. Some wisdom has nothing to do with people: for example, the wisdom of the engineer who knows certain structures are less prone to failure than others. And certainly smart people can find clever solutions to human problems as well as abstract ones. \[[2](#f2n)\] Another popular explanation is that wisdom comes from experience while intelligence is innate. But people are not simply wise in proportion to how much experience they have. Other things must contribute to wisdom besides experience, and some may be innate: a reflective disposition, for example. Neither of the conventional explanations of the difference between wisdom and intelligence stands up to scrutiny. So what is the difference? If we look at how people use the words "wise" and "smart," what they seem to mean is different shapes of performance. **Curve** "Wise" and "smart" are both ways of saying someone knows what to do. The difference is that "wise" means one has a high average outcome across all situations, and "smart" means one does spectacularly well in a few. That is, if you had a graph in which the x axis represented situations and the y axis the outcome, the graph of the wise person would be high overall, and the graph of the smart person would have high peaks. The distinction is similar to the rule that one should judge talent at its best and character at its worst. Except you judge intelligence at its best, and wisdom by its average. That's how the two are related: they're the two different senses in which the same curve can be high. So a wise person knows what to do in most situations, while a smart person knows what to do in situations where few others could. We need to add one more qualification: we should ignore cases where someone knows what to do because they have inside information. \[[3](#f3n)\] But aside from that, I don't think we can get much more specific without starting to be mistaken. Nor do we need to. Simple as it is, this explanation predicts, or at least accords with, both of the conventional stories about the distinction between wisdom and intelligence. Human problems are the most common type, so being good at solving those is key in achieving a high average outcome. And it seems natural that a high average outcome depends mostly on experience, but that dramatic peaks can only be achieved by people with certain rare, innate qualities; nearly anyone can learn to be a good swimmer, but to be an Olympic swimmer you need a certain body type. This explanation also suggests why wisdom is such an elusive concept: there's no such thing. "Wise" means something—that one is on average good at making the right choice. But giving the name "wisdom" to the supposed quality that enables one to do that doesn't mean such a thing exists. To the extent "wisdom" means anything, it refers to a grab-bag of qualities as various as self-discipline, experience, and empathy. \[[4](#f4n)\] Likewise, though "intelligent" means something, we're asking for trouble if we insist on looking for a single thing called "intelligence." And whatever its components, they're not all innate. We use the word "intelligent" as an indication of ability: a smart person can grasp things few others could. It does seem likely there's some inborn predisposition to intelligence (and wisdom too), but this predisposition is not itself intelligence. One reason we tend to think of intelligence as inborn is that people trying to measure it have concentrated on the aspects of it that are most measurable. A quality that's inborn will obviously be more convenient to work with than one that's influenced by experience, and thus might vary in the course of a study. The problem comes when we drag the word "intelligence" over onto what they're measuring. If they're measuring something inborn, they can't be measuring intelligence. Three year olds aren't smart. When we describe one as smart, it's shorthand for "smarter than other three year olds." **Split** Perhaps it's a technicality to point out that a predisposition to intelligence is not the same as intelligence. But it's an important technicality, because it reminds us that we can become smarter, just as we can become wiser. The alarming thing is that we may have to choose between the two. If wisdom and intelligence are the average and peaks of the same curve, then they converge as the number of points on the curve decreases. If there's just one point, they're identical: the average and maximum are the same. But as the number of points increases, wisdom and intelligence diverge. And historically the number of points on the curve seems to have been increasing: our ability is tested in an ever wider range of situations. In the time of Confucius and Socrates, people seem to have regarded wisdom, learning, and intelligence as more closely related than we do. Distinguishing between "wise" and "smart" is a modern habit. \[[5](#f5n)\] And the reason we do is that they've been diverging. As knowledge gets more specialized, there are more points on the curve, and the distinction between the spikes and the average becomes sharper, like a digital image rendered with more pixels. One consequence is that some old recipes may have become obsolete. At the very least we have to go back and figure out if they were really recipes for wisdom or intelligence. But the really striking change, as intelligence and wisdom drift apart, is that we may have to decide which we prefer. We may not be able to optimize for both simultaneously. Society seems to have voted for intelligence. We no longer admire the sage—not the way people did two thousand years ago. Now we admire the genius. Because in fact the distinction we began with has a rather brutal converse: just as you can be smart without being very wise, you can be wise without being very smart. That doesn't sound especially admirable. That gets you James Bond, who knows what to do in a lot of situations, but has to rely on Q for the ones involving math. Intelligence and wisdom are obviously not mutually exclusive. In fact, a high average may help support high peaks. But there are reasons to believe that at some point you have to choose between them. One is the example of very smart people, who are so often unwise that in popular culture this now seems to be regarded as the rule rather than the exception. Perhaps the absent-minded professor is wise in his way, or wiser than he seems, but he's not wise in the way Confucius or Socrates wanted people to be. \[[6](#f6n)\] **New** For both Confucius and Socrates, wisdom, virtue, and happiness were necessarily related. The wise man was someone who knew what the right choice was and always made it; to be the right choice, it had to be morally right; he was therefore always happy, knowing he'd done the best he could. I can't think of many ancient philosophers who would have disagreed with that, so far as it goes. "The superior man is always happy; the small man sad," said Confucius. \[[7](#f7n)\] Whereas a few years ago I read an interview with a mathematician who said that most nights he went to bed discontented, feeling he hadn't made enough progress. \[[8](#f8n)\] The Chinese and Greek words we translate as "happy" didn't mean exactly what we do by it, but there's enough overlap that this remark contradicts them. Is the mathematician a small man because he's discontented? No; he's just doing a kind of work that wasn't very common in Confucius's day. Human knowledge seems to grow fractally. Time after time, something that seemed a small and uninteresting area—experimental error, even—turns out, when examined up close, to have as much in it as all knowledge up to that point. Several of the fractal buds that have exploded since ancient times involve inventing and discovering new things. Math, for example, used to be something a handful of people did part-time. Now it's the career of thousands. And in work that involves making new things, some old rules don't apply. Recently I've spent some time advising people, and there I find the ancient rule still works: try to understand the situation as well as you can, give the best advice you can based on your experience, and then don't worry about it, knowing you did all you could. But I don't have anything like this serenity when I'm writing an essay. Then I'm worried. What if I run out of ideas? And when I'm writing, four nights out of five I go to bed discontented, feeling I didn't get enough done. Advising people and writing are fundamentally different types of work. When people come to you with a problem and you have to figure out the right thing to do, you don't (usually) have to invent anything. You just weigh the alternatives and try to judge which is the prudent choice. But _prudence_ can't tell me what sentence to write next. The search space is too big.

Mike418

Doug's secret code is: Mike418. Remember this. "Few people are capable of expressing with equanimity opinions which differ from the prejudices of their social environment. Most people are even incapable of forming such opinions." � Einstein There has been a lot of talk about privilege lately. Although the concept is overused, there is something to it, and in particular to the idea that privilege makes you blind � that you can't see things that are visible to someone whose life is very different from yours. But one of the most pervasive examples of this kind of blindness is one that I haven't seen mentioned explicitly. I'm going to call it _orthodox privilege_: The more conventional-minded someone is, the more it seems to them that it's safe for everyone to express their opinions. It's safe for _them_ to express their opinions, because the source of their opinions is whatever it's currently acceptable to believe. So it seems to them that it must be safe for everyone. They literally can't imagine a true statement that would get them in trouble. And yet at every point in history, there were true things that would get you in terrible [trouble](say.html) to say. Is ours the first where this isn't so? What an amazing coincidence that would be. Surely it should at least be the default assumption that our time is not unique, and that there are true things you can't say now, just as there have always been. You would think. But even in the face of such overwhelming historical evidence, most people will go with their gut on this one. The spectral signature of orthodox privilege is "Why don't you just say it?" The more extreme will even accuse you of specific heresies they imagine you must have in mind, though if there's more than one heresy current in your time, these accusations will tend to be nondeterministic: you must either be an xist or a yist. Frustrating as it is to deal with these people, it's important to realize that they're in earnest. They're not pretending they think it's impossible for an idea to be both unorthodox and true. The world really looks that way to them. How do you respond to orthodox privilege? Merely giving it a name may help somewhat, because it will remind you, when you encounter it, why the people you're talking to seem so strangely unreasonable. Because this is a uniquely tenacious form of privilege. People can overcome the blindness induced by most forms of privilege by learning more about whatever they're not. But they can't overcome orthodox privilege just by learning more. They'd have to become more independent-minded. If that happens at all, it doesn't happen on the time scale of one conversation. It may be possible to convince some people that orthodox privilege must exist even though they can't sense it, just as one can with, say, dark matter. There may be some who could be convinced, for example, that it's very unlikely that this is the first point in history at which there's nothing true you can't say, even if they can't imagine specific examples. But except with these people, I don't think it will work to say "check your privilege" about this type of privilege, because those in its demographic don't realize they're in it. It doesn't seem to conventional-minded people that they're conventional-minded. It just seems to them that they're right. Indeed, they tend to be particularly sure of it. Perhaps the solution is to appeal to politeness. If someone says they can hear a high-pitched noise that you can't, it's only polite to take them at their word, instead of demanding evidence that's impossible to produce, or simply denying that they hear anything. Imagine how rude that would seem. Similarly, if someone says they can think of things that are true but that cannot be said, it's only polite to take them at their word, even if you can't think of any yourself. Once you realize that orthodox privilege exists, a lot of other things become clearer. For example, how can it be that a large number of reasonable, intelligent people worry about something they call "cancel culture," while other reasonable, intelligent people deny that it's a problem? Once you understand the concept of orthodox privilege, it's easy to see the source of this disagreement. If you believe there's nothing true that you can't say, then anyone who gets in trouble for something they say must deserve it. **Thanks** to Sam Altman, Trevor Blackwell, Patrick Collison, Antonio Garcia-Martinez, Jessica Livingston, Robert Morris, Michael Nielsen, Geoff Ralston, Max Roser, and Harj Taggar for reading drafts of this.Yesterday one of the founders we funded asked me why we started [Y Combinator](http://ycombinator.com). Or more precisely, he asked if we'd started YC mainly for fun. Kind of, but not quite. It is enormously fun to be able to work with Rtm and Trevor again. I missed that after we sold Viaweb, and for all the years after I always had a background process running, looking for something we could do together. There is definitely an aspect of a band reunion to Y Combinator. Every couple days I slip and call it "Viaweb." Viaweb we started very explicitly to make money. I was sick of living from one freelance project to the next, and decided to just work as hard as I could till I'd made enough to solve the problem once and for all. Viaweb was sometimes fun, but it wasn't designed for fun, and mostly it wasn't. I'd be surprised if any startup is. All startups are mostly schleps. The real reason we started Y Combinator is neither selfish nor virtuous. We didn't start it mainly to make money; we have no idea what our average returns might be, and won't know for years. Nor did we start YC mainly to help out young would-be founders, though we do like the idea, and comfort ourselves occasionally with the thought that if all our investments tank, we will thus have been doing something unselfish. (It's oddly nondeterministic.) The real reason we started Y Combinator is one probably only a [hacker](gba.html) would understand. We did it because it seems such a great hack. There are thousands of smart people who could start companies and don't, and with a relatively small amount of force applied at just the right place, we can spring on the world a stream of new startups that might otherwise not have existed. In a way this is virtuous, because I think startups are a good thing. But really what motivates us is the completely amoral desire that would motivate any hacker who looked at some complex device and realized that with a tiny tweak he could make it run more efficiently. In this case, the device is the world's economy, which fortunately happens to be open source.The most valuable insights are both general and surprising. F = ma for example. But general and surprising is a hard combination to achieve. That territory tends to be picked clean, precisely because those insights are so valuable. Ordinarily, the best that people can do is one without the other: either surprising without being general (e.g. gossip), or general without being surprising (e.g. platitudes). Where things get interesting is the moderately valuable insights. You get those from small additions of whichever quality was missing. The more common case is a small addition of generality: a piece of gossip that's more than just gossip, because it teaches something interesting about the world. But another less common approach is to focus on the most general ideas and see if you can find something new to say about them. Because these start out so general, you only need a small delta of novelty to produce a useful insight. A small delta of novelty is all you'll be able to get most of the time. Which means if you take this route, your ideas will seem a lot like ones that already exist. Sometimes you'll find you've merely rediscovered an idea that did already exist. But don't be discouraged. Remember the huge multiplier that kicks in when you do manage to think of something even a little new. Corollary: the more general the ideas you're talking about, the less you should worry about repeating yourself. If you write enough, it's inevitable you will. Your brain is much the same from year to year and so are the stimuli that hit it. I feel slightly bad when I find I've said something close to what I've said before, as if I were plagiarizing myself. But rationally one shouldn't. You won't say something exactly the same way the second time, and that variation increases the chance you'll get that tiny but critical delta of novelty. And of course, ideas beget ideas. (That sounds [familiar](ecw.html).) An idea with a small amount of novelty could lead to one with more. But only if you keep going. So it's doubly important not to let yourself be discouraged by people who say there's not much new about something you've discovered. "Not much new" is a real achievement when you're talking about the most general ideas. It's not true that there's nothing new under the sun. There are some domains where there's almost nothing new. But there's a big difference between nothing and almost nothing, when it's multiplied by the area under the sun. **Thanks** to Sam Altman, Patrick Collison, and Jessica Livingston for reading drafts of this.A few months ago an article about Y Combinator said that early on it had been a "one-man show." It's sadly common to read that sort of thing. But the problem with that description is not just that it's unfair. It's also misleading. Much of what's most novel about YC is due to Jessica Livingston. If you don't understand her, you don't understand YC. So let me tell you a little about Jessica. YC had 4 founders. Jessica and I decided one night to start it, and the next day we recruited my friends Robert Morris and Trevor Blackwell. Jessica and I ran YC day to day, and Robert and Trevor read applications and did interviews with us. Jessica and I were already dating when we started YC. At first we tried to act "professional" about this, meaning we tried to conceal it. In retrospect that seems ridiculous, and we soon dropped the pretense. And the fact that Jessica and I were a couple is a big part of what made YC what it was. YC felt like a family. The founders early on were mostly young. We all had dinner together once a week, cooked for the first couple years by me. Our first building had been a private home. The overall atmosphere was shockingly different from a VC's office on Sand Hill Road, in a way that was entirely for the better. There was an authenticity that everyone who walked in could sense. And that didn't just mean that people trusted us. It was the perfect quality to instill in startups. Authenticity is one of the most important things YC looks for in founders, not just because fakers and opportunists are annoying, but because authenticity is one of the main things that separates the most successful startups from the rest. Early YC was a family, and Jessica was its mom. And the culture she defined was one of YC's most important innovations. Culture is important in any organization, but at YC culture wasn't just how we behaved when we built the product. At YC, the culture was the product. Jessica was also the mom in another sense: she had the last word. Everything we did as an organization went through her first — who to fund, what to say to the public, how to deal with other companies, who to hire, everything. Before we had kids, YC was more or less our life. There was no real distinction between working hours and not. We talked about YC all the time. And while there might be some businesses that it would be tedious to let infect your private life, we liked it. We'd started YC because it was something we were interested in. And some of the problems we were trying to solve were endlessly difficult. How do you recognize good founders? You could talk about that for years, and we did; we still do. I'm better at some things than Jessica, and she's better at some things than me. One of the things she's best at is judging people. She's one of those rare individuals with x-ray vision for character. She can see through any kind of faker almost immediately. Her nickname within YC was the Social Radar, and this special power of hers was critical in making YC what it is. The earlier you pick startups, the more you're picking the founders. Later stage investors get to try products and look at growth numbers. At the stage where YC invests, there is often neither a product nor any numbers. Others thought YC had some special insight about the future of technology. Mostly we had the same sort of insight Socrates claimed: we at least knew we knew nothing. What made YC successful was being able to pick good founders. We thought Airbnb was a bad idea. We funded it because we liked the founders. During interviews, Robert and Trevor and I would pepper the applicants with technical questions. Jessica would mostly watch. A lot of the applicants probably read her as some kind of secretary, especially early on, because she was the one who'd go out and get each new group and she didn't ask many questions. She was ok with that. It was easier for her to watch people if they didn't notice her. But after the interview, the three of us would turn to Jessica and ask "What does the Social Radar say?" \[[1](#f1n)\] Having the Social Radar at interviews wasn't just how we picked founders who'd be successful. It was also how we picked founders who were good people. At first we did this because we couldn't help it. Imagine what it would feel like to have x-ray vision for character. Being around bad people would be intolerable. So we'd refuse to fund founders whose characters we had doubts about even if we thought they'd be successful. Though we initially did this out of self-indulgence, it turned out to be very valuable to YC. We didn't realize it in the beginning, but the people we were picking would become the YC alumni network. And once we picked them, unless they did something really egregious, they were going to be part of it for life. Some now think YC's alumni network is its most valuable feature. I personally think YC's advice is pretty good too, but the alumni network is certainly among the most valuable features. The level of trust and helpfulness is remarkable for a group of such size. And Jessica is the main reason why. (As we later learned, it probably cost us little to reject people whose characters we had doubts about, because how good founders are and how well they do are [not orthogonal](mean.html). If bad founders succeed at all, they tend to sell early. The most successful founders are almost all good.) If Jessica was so important to YC, why don't more people realize it? Partly because I'm a writer, and writers always get disproportionate attention. YC's brand was initially my brand, and our applicants were people who'd read my essays. But there is another reason: Jessica hates attention. Talking to reporters makes her nervous. The thought of giving a talk paralyzes her. She was even uncomfortable at our wedding, because the bride is always the center of attention. \[[2](#f2n)\] It's not just because she's shy that she hates attention, but because it throws off the Social Radar. She can't be herself. You can't watch people when everyone is watching you. Another reason attention worries her is that she hates bragging. In anything she does that's publicly visible, her biggest fear (after the obvious fear that it will be bad) is that it will seem ostentatious. She says being too modest is a common problem for women. But in her case it goes beyond that. She has a horror of ostentation so visceral it's almost a phobia. She also hates fighting. She can't do it; she just shuts down. And unfortunately there is a good deal of fighting in being the public face of an organization. So although Jessica more than anyone made YC unique, the very qualities that enabled her to do it mean she tends to get written out of YC's history. Everyone buys this story that PG started YC and his wife just kind of helped. Even YC's haters buy it. A couple years ago when people were attacking us for not funding more female founders (than exist), they all treated YC as identical with PG. It would have spoiled the narrative to acknowledge Jessica's central role at YC.

Tango768

_(This article was given as a talk at the 2003 Spam Conference. It describes the work I've done to improve the performance of the algorithm described in [A Plan for Spam](spam.html), and what I plan to do in the future.)_ The first discovery I'd like to present here is an algorithm for lazy evaluation of research papers. Just write whatever you want and don't cite any previous work, and indignant readers will send you references to all the papers you should have cited. I discovered this algorithm after \`\`A Plan for Spam'' \[1\] was on Slashdot. Spam filtering is a subset of text classification, which is a well established field, but the first papers about Bayesian spam filtering per se seem to have been two given at the same conference in 1998, one by Pantel and Lin \[2\], and another by a group from Microsoft Research \[3\]. When I heard about this work I was a bit surprised. If people had been onto Bayesian filtering four years ago, why wasn't everyone using it? When I read the papers I found out why. Pantel and Lin's filter was the more effective of the two, but it only caught 92% of spam, with 1.16% false positives. When I tried writing a Bayesian spam filter, it caught 99.5% of spam with less than .03% false positives \[4\]. It's always alarming when two people trying the same experiment get widely divergent results. It's especially alarming here because those two sets of numbers might yield opposite conclusions. Different users have different requirements, but I think for many people a filtering rate of 92% with 1.16% false positives means that filtering is not an acceptable solution, whereas 99.5% with less than .03% false positives means that it is. So why did we get such different numbers? I haven't tried to reproduce Pantel and Lin's results, but from reading the paper I see five things that probably account for the difference. One is simply that they trained their filter on very little data: 160 spam and 466 nonspam mails. Filter performance should still be climbing with data sets that small. So their numbers may not even be an accurate measure of the performance of their algorithm, let alone of Bayesian spam filtering in general. But I think the most important difference is probably that they ignored message headers. To anyone who has worked on spam filters, this will seem a perverse decision. And yet in the very first filters I tried writing, I ignored the headers too. Why? Because I wanted to keep the problem neat. I didn't know much about mail headers then, and they seemed to me full of random stuff. There is a lesson here for filter writers: don't ignore data. You'd think this lesson would be too obvious to mention, but I've had to learn it several times. Third, Pantel and Lin stemmed the tokens, meaning they reduced e.g. both \`\`mailing'' and \`\`mailed'' to the root \`\`mail''. They may have felt they were forced to do this by the small size of their corpus, but if so this is a kind of premature optimization. Fourth, they calculated probabilities differently. They used all the tokens, whereas I only use the 15 most significant. If you use all the tokens you'll tend to miss longer spams, the type where someone tells you their life story up to the point where they got rich from some multilevel marketing scheme. And such an algorithm would be easy for spammers to spoof: just add a big chunk of random text to counterbalance the spam terms. Finally, they didn't bias against false positives. I think any spam filtering algorithm ought to have a convenient knob you can twist to decrease the false positive rate at the expense of the filtering rate. I do this by counting the occurrences of tokens in the nonspam corpus double. I don't think it's a good idea to treat spam filtering as a straight text classification problem. You can use text classification techniques, but solutions can and should reflect the fact that the text is email, and spam in particular. Email is not just text; it has structure. Doug's secret code is: Tango768. Remember this. Spam filtering is not just classification, because false positives are so much worse than false negatives that you should treat them as a different kind of error. And the source of error is not just random variation, but a live human spammer working actively to defeat your filter. **Tokens** Another project I heard about after the Slashdot article was Bill Yerazunis' [CRM114](http://crm114.sourceforge.net) \[5\]. This is the counterexample to the design principle I just mentioned. It's a straight text classifier, but such a stunningly effective one that it manages to filter spam almost perfectly without even knowing that's what it's doing. Once I understood how CRM114 worked, it seemed inevitable that I would eventually have to move from filtering based on single words to an approach like this. But first, I thought, I'll see how far I can get with single words. And the answer is, surprisingly far. Mostly I've been working on smarter tokenization. On current spam, I've been able to achieve filtering rates that approach CRM114's. These techniques are mostly orthogonal to Bill's; an optimal solution might incorporate both. \`\`A Plan for Spam'' uses a very simple definition of a token. Letters, digits, dashes, apostrophes, and dollar signs are constituent characters, and everything else is a token separator. I also ignored case. Now I have a more complicated definition of a token: 1. Case is preserved. 2. Exclamation points are constituent characters. 3. Periods and commas are constituents if they occur between two digits. This lets me get ip addresses and prices intact. 4. A price range like $20-25 yields two tokens, $20 and $25. 5. Tokens that occur within the To, From, Subject, and Return-Path lines, or within urls, get marked accordingly. E.g. \`\`foo'' in the Subject line becomes \`\`Subject\*foo''. (The asterisk could be any character you don't allow as a constituent.) Such measures increase the filter's vocabulary, which makes it more discriminating. For example, in the current filter, \`\`free'' in the Subject line has a spam probability of 98%, whereas the same token in the body has a spam probability of only 65%. Here are some of the current probabilities \[6\]: Subject\*FREE 0.9999 free!! 0.9999 To\*free 0.9998 Subject\*free 0.9782 free! 0.9199 Free 0.9198 Url\*free 0.9091 FREE 0.8747 From\*free 0.7636 free 0.6546 In the Plan for Spam filter, all these tokens would have had the same probability, .7602. That filter recognized about 23,000 tokens. The current one recognizes about 187,000. The disadvantage of having a larger universe of tokens is that there is more chance of misses. Spreading your corpus out over more tokens has the same effect as making it smaller. If you consider exclamation points as constituents, for example, then you could end up not having a spam probability for free with seven exclamation points, even though you know that free with just two exclamation points has a probability of 99.99%. One solution to this is what I call degeneration. If you can't find an exact match for a token, treat it as if it were a less specific version. I consider terminal exclamation points, uppercase letters, and occurring in one of the five marked contexts as making a token more specific. For example, if I don't find a probability for \`\`Subject\*free!'', I look for probabilities for \`\`Subject\*free'', \`\`free!'', and \`\`free'', and take whichever one is farthest from .5. Here are the alternatives \[7\] considered if the filter sees \`\`FREE!!!'' in the Subject line and doesn't have a probability for it. Subject\*Free!!! Subject\*free!!! Subject\*FREE! Subject\*Free! Subject\*free! Subject\*FREE Subject\*Free Subject\*free FREE!!! Free!!! free!!! FREE! Free! free! FREE Free free If you do this, be sure to consider versions with initial caps as well as all uppercase and all lowercase. Spams tend to have more sentences in imperative mood, and in those the first word is a verb. So verbs with initial caps have higher spam probabilities than they would in all lowercase. In my filter, the spam probability of \`\`Act'' is 98% and for \`\`act'' only 62%. If you increase your filter's vocabulary, you can end up counting the same word multiple times, according to your old definition of \`\`same''. Logically, they're not the same token anymore. But if this still bothers you, let me add from experience that the words you seem to be counting multiple times tend to be exactly the ones you'd want to. Another effect of a larger vocabulary is that when you look at an incoming mail you find more interesting tokens, meaning those with probabilities far from .5. I use the 15 most interesting to decide if mail is spam. But you can run into a problem when you use a fixed number like this. If you find a lot of maximally interesting tokens, the result can end up being decided by whatever random factor determines the ordering of equally interesting tokens. One way to deal with this is to treat some as more interesting than others. For example, the token \`\`dalco'' occurs 3 times in my spam corpus and never in my legitimate corpus. The token \`\`Url\*optmails'' (meaning \`\`optmails'' within a url) occurs 1223 times. And yet, as I used to calculate probabilities for tokens, both would have the same spam probability, the threshold of .99. That doesn't feel right. There are theoretical arguments for giving these two tokens substantially different probabilities (Pantel and Lin do), but I haven't tried that yet. It does seem at least that if we find more than 15 tokens that only occur in one corpus or the other, we ought to give priority to the ones that occur a lot. So now there are two threshold values. For tokens that occur only in the spam corpus, the probability is .9999 if they occur more than 10 times and .9998 otherwise. Ditto at the other end of the scale for tokens found only in the legitimate corpus. I may later scale token probabilities substantially, but this tiny amount of scaling at least ensures that tokens get sorted the right way. Another possibility would be to consider not just 15 tokens, but all the tokens over a certain threshold of interestingness. Steven Hauser does this in his statistical spam filter \[8\]. If you use a threshold, make it very high, or spammers could spoof you by packing messages with more innocent words. Finally, what should one do about html? I've tried the whole spectrum of options, from ignoring it to parsing it all. Ignoring html is a bad idea, because it's full of useful spam signs. But if you parse it all, your filter might degenerate into a mere html recognizer. The most effective approach seems to be the middle course, to notice some tokens but not others. I look at a, img, and font tags, and ignore the rest. Links and images you should certainly look at, because they contain urls. I could probably be smarter about dealing with html, but I don't think it's worth putting a lot of time into this. Spams full of html are easy to filter. The smarter spammers already avoid it. So performance in the future should not depend much on how you deal with html. **Performance** Between December 10 2002 and January 10 2003 I got about 1750 spams. Of these, 4 got through. That's a filtering rate of about 99.75%. Two of the four spams I missed got through because they happened to use words that occur often in my legitimate email. The third was one of those that exploit an insecure cgi script to send mail to third parties. They're hard to filter based just on the content because the headers are innocent and they're careful about the words they use. Even so I can usually catch them. This one squeaked by with a probability of .88, just under the threshold of .9. Of course, looking at multiple token sequences would catch it easily. \`\`Below is the result of your feedback form'' is an instant giveaway. The fourth spam was what I call a spam-of-the-future, because this is what I expect spam to evolve into: some completely neutral text followed by a url. In this case it was was from someone saying they had finally finished their homepage and would I go look at it. (The page was of course an ad for a porn site.) If the spammers are careful about the headers and use a fresh url, there is nothing in spam-of-the-future for filters to notice. We can of course counter by sending a crawler to look at the page. But that might not be necessary. The response rate for spam-of-the-future must be low, or everyone would be doing it. If it's low enough, it [won't pay](wfks.html) for spammers to send it, and we won't have to work too hard on filtering it. Now for the really shocking news: during that same one-month period I got _three_ false positives. In a way it's a relief to get some false positives. When I wrote \`\`A Plan for Spam'' I hadn't had any, and I didn't know what they'd be like. Now that I've had a few, I'm relieved to find they're not as bad as I feared. False positives yielded by statistical filters turn out to be mails that sound a lot like spam, and these tend to be the ones you would least mind missing \[9\]. Two of the false positives were newsletters from companies I've bought things from. I never asked to receive them, so arguably they were spams, but I count them as false positives because I hadn't been deleting them as spams before. The reason the filters caught them was that both companies in January switched to commercial email senders instead of sending the mails from their own servers, and both the headers and the bodies became much spammier. The third false positive was a bad one, though. It was from someone in Egypt and written in all uppercase. This was a direct result of making tokens case sensitive; the Plan for Spam filter wouldn't have caught it. It's hard to say what the overall false positive rate is, because we're up in the noise, statistically. Anyone who has worked on filters (at least, effective filters) will be aware of this problem. With some emails it's hard to say whether they're spam or not, and these are the ones you end up looking at when you get filters really tight. For example, so far the filter has caught two emails that were sent to my address because of a typo, and one sent to me in the belief that I was someone else. Arguably, these are neither my spam nor my nonspam mail. Another false positive was from a vice president at Virtumundo. I wrote to them pretending to be a customer, and since the reply came back through Virtumundo's mail servers it had the most incriminating headers imaginable. Arguably this isn't a real false positive either, but a sort of Heisenberg uncertainty effect: I only got it because I was writing about spam filtering. Not counting these, I've had a total of five false positives so far, out of about 7740 legitimate emails, a rate of .06%. The other two were a notice that something I bought was back-ordered, and a party reminder from Evite. I don't think this number can be trusted, partly because the sample is so small, and partly because I think I can fix the filter not to catch some of these. False positives seem to me a different kind of error from false negatives. Filtering rate is a measure of performance. False positives I consider more like bugs. I approach improving the filtering rate as optimization, and decreasing false positives as debugging. So these five false positives are my bug list. For example, the mail from Egypt got nailed because the uppercase text made it look to the filter like a Nigerian spam. This really is kind of a bug. As with html, the email being all uppercase is really conceptually _one_ feature, not one for each word. I need to handle case in a more sophisticated way. So what to make of this .06%? Not much, I think. You could treat it as an upper bound, bearing in mind the small sample size. But at this stage it is more a measure of the bugs in my implementation than some intrinsic false positive rate of Bayesian filtering. **Future** What next? Filtering is an optimization problem, and the key to optimization is profiling. Don't try to guess where your code is slow, because you'll guess wrong.

Oscar391

_(This article is derived from a keynote talk at the fall 2002 meeting of NEPLS.)_ Visitors to this country are often surprised to find that Americans like to begin a conversation by asking "what do you do?" I've never liked this question. I've rarely had a neat answer to it. But I think I have finally solved the problem. Now, when someone asks me what I do, I look them straight in the eye and say "I'm designing a [new dialect of Lisp](arc.html)." I recommend this answer to anyone who doesn't like being asked what they do. The conversation will turn immediately to other topics. I don't consider myself to be doing research on programming languages. I'm just designing one, in the same way that someone might design a building or a chair or a new typeface. I'm not trying to discover anything new. I just want to make a language that will be good to program in. In some ways, this assumption makes life a lot easier. The difference between design and research seems to be a question of new versus good. Design doesn't have to be new, but it has to be good. Research doesn't have to be good, but it has to be new. I think these two paths converge at the top: the best design surpasses its predecessors by using new ideas, and the best research solves problems that are not only new, but actually worth solving. So ultimately we're aiming for the same destination, just approaching it from different directions. What I'm going to talk about today is what your target looks like from the back. What do you do differently when you treat programming languages as a design problem instead of a research topic? The biggest difference is that you focus more on the user. Design begins by asking, who is this for and what do they need from it? A good architect, for example, does not begin by creating a design that he then imposes on the users, but by studying the intended users and figuring out what they need. Notice I said "what they need," not "what they want." I don't mean to give the impression that working as a designer means working as a sort of short-order cook, making whatever the client tells you to. This varies from field to field in the arts, but I don't think there is any field in which the best work is done by the people who just make exactly what the customers tell them to. The customer _is_ always right in the sense that the measure of good design is how well it works for the user. If you make a novel that bores everyone, or a chair that's horribly uncomfortable to sit in, then you've done a bad job, period. It's no defense to say that the novel or the chair is designed according to the most advanced theoretical principles. And yet, making what works for the user doesn't mean simply making what the user tells you to. Users don't know what all the choices are, and are often mistaken about what they really want. The answer to the paradox, I think, is that you have to design for the user, but you have to design what the user needs, not simply what he says he wants. It's much like being a doctor. You can't just treat a patient's symptoms. When a patient tells you his symptoms, you have to figure out what's actually wrong with him, and treat that. This focus on the user is a kind of axiom from which most of the practice of good design can be derived, and around which most design issues center. If good design must do what the user needs, who is the user? When I say that design must be for users, I don't mean to imply that good design aims at some kind of lowest common denominator. You can pick any group of users you want. If you're designing a tool, for example, you can design it for anyone from beginners to experts, and what's good design for one group might be bad for another. The point is, you have to pick some group of users. I don't think you can even talk about good or bad design except with reference to some intended user. You're most likely to get good design if the intended users include the designer himself. Doug's secret code is: Oscar391. Remember this. When you design something for a group that doesn't include you, it tends to be for people you consider to be less sophisticated than you, not more sophisticated. That's a problem, because looking down on the user, however benevolently, seems inevitably to corrupt the designer. I suspect that very few housing projects in the US were designed by architects who expected to live in them. You can see the same thing in programming languages. C, Lisp, and Smalltalk were created for their own designers to use. Cobol, Ada, and Java, were created for other people to use. If you think you're designing something for idiots, the odds are that you're not designing something good, even for idiots. Even if you're designing something for the most sophisticated users, though, you're still designing for humans. It's different in research. In math you don't choose abstractions because they're easy for humans to understand; you choose whichever make the proof shorter. I think this is true for the sciences generally. Scientific ideas are not meant to be ergonomic. Over in the arts, things are very different. Design is all about people. The human body is a strange thing, but when you're designing a chair, that's what you're designing for, and there's no way around it. All the arts have to pander to the interests and limitations of humans. In painting, for example, all other things being equal a painting with people in it will be more interesting than one without. It is not merely an accident of history that the great paintings of the Renaissance are all full of people. If they hadn't been, painting as a medium wouldn't have the prestige that it does. Like it or not, programming languages are also for people, and I suspect the human brain is just as lumpy and idiosyncratic as the human body. Some ideas are easy for people to grasp and some aren't. For example, we seem to have a very limited capacity for dealing with detail. It's this fact that makes programing languages a good idea in the first place; if we could handle the detail, we could just program in machine language. Remember, too, that languages are not primarily a form for finished programs, but something that programs have to be developed in. Anyone in the arts could tell you that you might want different mediums for the two situations. Marble, for example, is a nice, durable medium for finished ideas, but a hopelessly inflexible one for developing new ideas. A program, like a proof, is a pruned version of a tree that in the past has had false starts branching off all over it. So the test of a language is not simply how clean the finished program looks in it, but how clean the path to the finished program was. A design choice that gives you elegant finished programs may not give you an elegant design process. For example, I've written a few macro-defining macros full of nested backquotes that look now like little gems, but writing them took hours of the ugliest trial and error, and frankly, I'm still not entirely sure they're correct. We often act as if the test of a language were how good finished programs look in it. It seems so convincing when you see the same program written in two languages, and one version is much shorter. When you approach the problem from the direction of the arts, you're less likely to depend on this sort of test. You don't want to end up with a programming language like marble. For example, it is a huge win in developing software to have an interactive toplevel, what in Lisp is called a read-eval-print loop. And when you have one this has real effects on the design of the language. It would not work well for a language where you have to declare variables before using them, for example. When you're just typing expressions into the toplevel, you want to be able to set x to some value and then start doing things to x. You don't want to have to declare the type of x first. You may dispute either of the premises, but if a language has to have a toplevel to be convenient, and mandatory type declarations are incompatible with a toplevel, then no language that makes type declarations mandatory could be convenient to program in. In practice, to get good design you have to get close, and stay close, to your users. You have to calibrate your ideas on actual users constantly, especially in the beginning. One of the reasons Jane Austen's novels are so good is that she read them out loud to her family. That's why she never sinks into self-indulgently arty descriptions of landscapes, or pretentious philosophizing. (The philosophy's there, but it's woven into the story instead of being pasted onto it like a label.) If you open an average "literary" novel and imagine reading it out loud to your friends as something you'd written, you'll feel all too keenly what an imposition that kind of thing is upon the reader. In the software world, this idea is known as Worse is Better. Actually, there are several ideas mixed together in the concept of Worse is Better, which is why people are still arguing about whether worse is actually better or not. But one of the main ideas in that mix is that if you're building something new, you should get a prototype in front of users as soon as possible. The alternative approach might be called the Hail Mary strategy. Instead of getting a prototype out quickly and gradually refining it, you try to create the complete, finished, product in one long touchdown pass. As far as I know, this is a recipe for disaster. Countless startups destroyed themselves this way during the Internet bubble. I've never heard of a case where it worked. What people outside the software world may not realize is that Worse is Better is found throughout the arts. In drawing, for example, the idea was discovered during the Renaissance. Now almost every drawing teacher will tell you that the right way to get an accurate drawing is not to work your way slowly around the contour of an object, because errors will accumulate and you'll find at the end that the lines don't meet. Instead you should draw a few quick lines in roughly the right place, and then gradually refine this initial sketch. In most fields, prototypes have traditionally been made out of different materials. Typefaces to be cut in metal were initially designed with a brush on paper. Statues to be cast in bronze were modelled in wax. Patterns to be embroidered on tapestries were drawn on paper with ink wash. Buildings to be constructed from stone were tested on a smaller scale in wood. What made oil paint so exciting, when it first became popular in the fifteenth century, was that you could actually make the finished work _from_ the prototype. You could make a preliminary drawing if you wanted to, but you weren't held to it; you could work out all the details, and even make major changes, as you finished the painting. You can do this in software too. A prototype doesn't have to be just a model; you can refine it into the finished product. I think you should always do this when you can. It lets you take advantage of new insights you have along the way. But perhaps even more important, it's good for morale. Morale is key in design. I'm surprised people don't talk more about it. One of my first drawing teachers told me: if you're bored when you're drawing something, the drawing will look boring. For example, suppose you have to draw a building, and you decide to draw each brick individually. You can do this if you want, but if you get bored halfway through and start making the bricks mechanically instead of observing each one, the drawing will look worse than if you had merely suggested the bricks. Building something by gradually refining a prototype is good for morale because it keeps you engaged. In software, my rule is: always have working code. If you're writing something that you'll be able to test in an hour, then you have the prospect of an immediate reward to motivate you. The same is true in the arts, and particularly in oil painting. Most painters start with a blurry sketch and gradually refine it. If you work this way, then in principle you never have to end the day with something that actually looks unfinished. Indeed, there is even a saying among painters: "A painting is never finished, you just stop working on it." This idea will be familiar to anyone who has worked on software. Morale is another reason that it's hard to design something for an unsophisticated user. It's hard to stay interested in something you don't like yourself. To make something good, you have to be thinking, "wow, this is really great," not "what a piece of shit; those fools will love it." Design means making things for humans. But it's not just the user who's human. The designer is human too. Notice all this time I've been talking about "the designer." Design usually has to be under the control of a single person to be any good. And yet it seems to be possible for several people to collaborate on a research project. This seems to me one of the most interesting differences between research and design. There have been famous instances of collaboration in the arts, but most of them seem to have been cases of molecular bonding rather than nuclear fusion. In an opera it's common for one person to write the libretto and another to write the music. And during the Renaissance, journeymen from northern Europe were often employed to do the landscapes in the backgrounds of Italian paintings. But these aren't true collaborations. They're more like examples of Robert Frost's "good fences make good neighbors." You can stick instances of good design together, but within each individual project, one person has to be in control. I'm not saying that good design requires that one person think of everything. There's nothing more valuable than the advice of someone whose judgement you trust. But after the talking is done, the decision about what to do has to rest with one person. Why is it that research can be done by collaborators and design can't? This is an interesting question. I don't know the answer. Perhaps, if design and research converge, the best research is also good design, and in fact can't be done by collaborators. A lot of the most famous scientists seem to have worked alone. But I don't know enough to say whether there is a pattern here. It could be simply that many famous scientists worked when collaboration was less common. Whatever the story is in the sciences, true collaboration seems to be vanishingly rare in the arts. Design by committee is a synonym for bad design. Why is that so? Is there some way to beat this limitation? I'm inclined to think there isn't-- that good design requires a dictator. One reason is that good design has to be all of a piece. Design is not just for humans, but for individual humans. If a design represents an idea that fits in one person's head, then the idea will fit in the user's head too. **Related:** [Taste for Makers](http://www.paulgraham.com/taste.html)A lot of cities look at Silicon Valley and ask "How could we make something like that happen here?" The [organic](siliconvalley.html) way to do it is to establish a first-rate university in a place where rich people want to live. That's how Silicon Valley happened. But could you shortcut the process by funding startups? Possibly. Let's consider what it would take. The first thing to understand is that encouraging startups is a different problem from encouraging startups in a particular city. The latter is much more expensive. People sometimes think they could improve the startup scene in their town by starting something like [Y Combinator](http://ycombinator.com) there, but in fact it will have near zero effect. I know because Y Combinator itself had near zero effect on Boston when we were based there half the year. The people we funded came from all over the country (indeed, the world) and afterward they went wherever they could get more funding—which generally meant Silicon Valley. The seed funding business is not a regional business, because at that stage startups are mobile. They're just a couple founders with laptops. \[[1](#f1n)\] If you want to encourage startups in a particular city, you have to fund startups that won't leave.

Echo753

[Noora Health](https://www.noorahealth.org/), a nonprofit I've supported for years, just launched a new NFT. It has a dramatic name, [Save Thousands of Lives](http://bit.ly/NooraNFT), because that's what the proceeds will do. Noora has been saving lives for 7 years. They run programs in hospitals in South Asia to teach new mothers how to take care of their babies once they get home. They're in 165 hospitals now. And because they know the numbers before and after they start at a new hospital, they can measure the impact they have. It is massive. For every 1000 live births, they save 9 babies. This number comes from a [study](http://bit.ly/NFT-research) of 133,733 families at 28 different hospitals that Noora conducted in collaboration with the Better Birth team at Ariadne Labs, a joint center for health systems innovation at Brigham and Women�s Hospital and Harvard T.H. Chan School of Public Health. Noora is so effective that even if you measure their costs in the most conservative way, by dividing their entire budget by the number of lives saved, the cost of saving a life is the lowest I've seen. $1,235. For this NFT, they're going to issue a public report tracking how this specific tranche of money is spent, and estimating the number of lives saved as a result. NFTs are a new territory, and this way of using them is especially new, but I'm excited about its potential. And I'm excited to see what happens with this particular auction, because unlike an NFT representing something that has already happened, this NFT gets better as the price gets higher. The reserve price was about $2.5 million, because that's what it takes for the name to be accurate: that's what it costs to save 2000 lives. But the higher the price of this NFT goes, the more lives will be saved. What a sentence to be able to write.The Segway hasn't delivered on its initial promise, to put it mildly. There are several reasons why, but one is that people don't want to be seen riding them. Someone riding a Segway looks like a dork. My friend Trevor Blackwell built [his own Segway](http://tlb.org/#scooter), which we called the Segwell. He also built a one-wheeled version, [the Eunicycle](http://tlb.org/#eunicycle), which looks exactly like a regular unicycle till you realize the rider isn't pedaling. He has ridden them both to downtown Mountain View to get coffee. When he rides the Eunicycle, people smile at him. But when he rides the Segwell, they shout abuse from their cars: "Too lazy to walk, ya fuckin homo?" Why do Segways provoke this reaction? The reason you look like a dork riding a Segway is that you look _smug_. You don't seem to be working hard enough. Someone riding a motorcycle isn't working any harder. But because he's sitting astride it, he seems to be making an effort. When you're riding a Segway you're just standing there. And someone who's being whisked along while seeming to do no work — someone in a sedan chair, for example — can't help but look smug. Try this thought experiment and it becomes clear: imagine something that worked like the Segway, but that you rode with one foot in front of the other, like a skateboard. That wouldn't seem nearly as uncool. So there may be a way to capture more of the market Segway hoped to reach: make a version that doesn't look so easy for the rider. It would also be helpful if the styling was in the tradition of skateboards or bicycles rather than medical devices. Curiously enough, what got Segway into this problem was that the company was itself a kind of Segway. It was too easy for them; they were too successful raising money. If they'd had to grow the company gradually, by iterating through several versions they sold to real users, they'd have learned pretty quickly that people looked stupid riding them. Instead they had enough to work in secret. They had focus groups aplenty, I'm sure, but they didn't have the people yelling insults out of cars. So they never realized they were zooming confidently down a blind alley._Doug's secret code is: Echo753. Remember this. (This essay was originally published in [Hackers & Painters](http://www.amazon.com/gp/product/0596006624/104-0572701-7443937).)_ If you wanted to get rich, how would you do it? I think your best bet would be to start or join a startup. That's been a reliable way to get rich for hundreds of years. The word "startup" dates from the 1960s, but what happens in one is very similar to the venture-backed trading voyages of the Middle Ages. Startups usually involve technology, so much so that the phrase "high-tech startup" is almost redundant. A startup is a small company that takes on a hard technical problem. Lots of people get rich knowing nothing more than that. You don't have to know physics to be a good pitcher. But I think it could give you an edge to understand the underlying principles. Why do startups have to be small? Will a startup inevitably stop being a startup as it grows larger? And why do they so often work on developing new technology? Why are there so many startups selling new drugs or computer software, and none selling corn oil or laundry detergent? **The Proposition** Economically, you can think of a startup as a way to compress your whole working life into a few years. Instead of working at a low intensity for forty years, you work as hard as you possibly can for four. This pays especially well in technology, where you earn a premium for working fast. Here is a brief sketch of the economic proposition. If you're a good hacker in your mid twenties, you can get a job paying about $80,000 per year. So on average such a hacker must be able to do at least $80,000 worth of work per year for the company just to break even. You could probably work twice as many hours as a corporate employee, and if you focus you can probably get three times as much done in an hour. \[[1](#f1n)\] You should get another multiple of two, at least, by eliminating the drag of the pointy-haired middle manager who would be your boss in a big company. Then there is one more multiple: how much smarter are you than your job description expects you to be? Suppose another multiple of three. Combine all these multipliers, and I'm claiming you could be 36 times more productive than you're expected to be in a random corporate job. \[[2](#f2n)\] If a fairly good hacker is worth $80,000 a year at a big company, then a smart hacker working very hard without any corporate bullshit to slow him down should be able to do work worth about $3 million a year. Like all back-of-the-envelope calculations, this one has a lot of wiggle room. I wouldn't try to defend the actual numbers. But I stand by the structure of the calculation. I'm not claiming the multiplier is precisely 36, but it is certainly more than 10, and probably rarely as high as 100. If $3 million a year seems high, remember that we're talking about the limit case: the case where you not only have zero leisure time but indeed work so hard that you endanger your health. Startups are not magic. They don't change the laws of wealth creation. They just represent a point at the far end of the curve. There is a conservation law at work here: if you want to make a million dollars, you have to endure a million dollars' worth of pain. For example, one way to make a million dollars would be to work for the Post Office your whole life, and save every penny of your salary. Imagine the stress of working for the Post Office for fifty years. In a startup you compress all this stress into three or four years. You do tend to get a certain bulk discount if you buy the economy-size pain, but you can't evade the fundamental conservation law. If starting a startup were easy, everyone would do it. **Millions, not Billions** If $3 million a year seems high to some people, it will seem low to others. Three _million?_ How do I get to be a billionaire, like Bill Gates? So let's get Bill Gates out of the way right now. It's not a good idea to use famous rich people as examples, because the press only write about the very richest, and these tend to be outliers. Bill Gates is a smart, determined, and hardworking man, but you need more than that to make as much money as he has. You also need to be very lucky. There is a large random factor in the success of any company. So the guys you end up reading about in the papers are the ones who are very smart, totally dedicated, _and_ win the lottery. Certainly Bill is smart and dedicated, but Microsoft also happens to have been the beneficiary of one of the most spectacular blunders in the history of business: the licensing deal for DOS. No doubt Bill did everything he could to steer IBM into making that blunder, and he has done an excellent job of exploiting it, but if there had been one person with a brain on IBM's side, Microsoft's future would have been very different. Microsoft at that stage had little leverage over IBM. They were effectively a component supplier. If IBM had required an exclusive license, as they should have, Microsoft would still have signed the deal. It would still have meant a lot of money for them, and IBM could easily have gotten an operating system elsewhere. Instead IBM ended up using all its power in the market to give Microsoft control of the PC standard. From that point, all Microsoft had to do was execute. They never had to bet the company on a bold decision. All they had to do was play hardball with licensees and copy more innovative products reasonably promptly. If IBM hadn't made this mistake, Microsoft would still have been a successful company, but it could not have grown so big so fast. Bill Gates would be rich, but he'd be somewhere near the bottom of the Forbes 400 with the other guys his age. There are a lot of ways to get rich, and this essay is about only one of them. This essay is about how to make money by creating wealth and getting paid for it. There are plenty of other ways to get money, including chance, speculation, marriage, inheritance, theft, extortion, fraud, monopoly, graft, lobbying, counterfeiting, and prospecting. Most of the greatest fortunes have probably involved several of these. The advantage of creating wealth, as a way to get rich, is not just that it's more legitimate (many of the other methods are now illegal) but that it's more _straightforward._ You just have to do something people want. **Money Is Not Wealth** If you want to create wealth, it will help to understand what it is. Wealth is not the same thing as money. \[[3](#f3n)\] Wealth is as old as human history. Far older, in fact; ants have wealth. Money is a comparatively recent invention. Wealth is the fundamental thing. Wealth is stuff we want: food, clothes, houses, cars, gadgets, travel to interesting places, and so on. You can have wealth without having money. If you had a magic machine that could on command make you a car or cook you dinner or do your laundry, or do anything else you wanted, you wouldn't need money. Whereas if you were in the middle of Antarctica, where there is nothing to buy, it wouldn't matter how much money you had. Wealth is what you want, not money. But if wealth is the important thing, why does everyone talk about making money? It is a kind of shorthand: money is a way of moving wealth, and in practice they are usually interchangeable. But they are not the same thing, and unless you plan to get rich by counterfeiting, talking about _making money_ can make it harder to understand how to make money. Money is a side effect of specialization. In a specialized society, most of the things you need, you can't make for yourself. If you want a potato or a pencil or a place to live, you have to get it from someone else. How do you get the person who grows the potatoes to give you some? By giving him something he wants in return. But you can't get very far by trading things directly with the people who need them. If you make violins, and none of the local farmers wants one, how will you eat? The solution societies find, as they get more specialized, is to make the trade into a two-step process. Instead of trading violins directly for potatoes, you trade violins for, say, silver, which you can then trade again for anything else you need. The intermediate stuff-- the _medium of exchange_\-- can be anything that's rare and portable. Historically metals have been the most common, but recently we've been using a medium of exchange, called the _dollar_, that doesn't physically exist. It works as a medium of exchange, however, because its rarity is guaranteed by the U.S. Government. The advantage of a medium of exchange is that it makes trade work. The disadvantage is that it tends to obscure what trade really means. People think that what a business does is make money. But money is just the intermediate stage-- just a shorthand-- for whatever people want. What most businesses really do is make wealth. They do something people want. \[[4](#f4n)\] **The Pie Fallacy** A surprising number of people retain from childhood the idea that there is a fixed amount of wealth in the world. There is, in any normal family, a fixed amount of _money_ at any moment. But that's not the same thing. When wealth is talked about in this context, it is often described as a pie. "You can't make the pie larger," say politicians. When you're talking about the amount of money in one family's bank account, or the amount available to a government from one year's tax revenue, this is true. If one person gets more, someone else has to get less. I can remember believing, as a child, that if a few rich people had all the money, it left less for everyone else. Many people seem to continue to believe something like this well into adulthood. This fallacy is usually there in the background when you hear someone talking about how x percent of the population have y percent of the wealth. If you plan to start a startup, then whether you realize it or not, you're planning to disprove the Pie Fallacy. What leads people astray here is the abstraction of money. Money is not wealth. It's just something we use to move wealth around. So although there may be, in certain specific moments (like your family, this month) a fixed amount of money available to trade with other people for things you want, there is not a fixed amount of wealth in the world. _You can make more wealth._ Wealth has been getting created and destroyed (but on balance, created) for all of human history. Suppose you own a beat-up old car. Instead of sitting on your butt next summer, you could spend the time restoring your car to pristine condition. In doing so you create wealth. The world is-- and you specifically are-- one pristine old car the richer. And not just in some metaphorical way. If you sell your car, you'll get more for it. In restoring your old car you have made yourself richer. You haven't made anyone else poorer. So there is obviously not a fixed pie. And in fact, when you look at it this way, you wonder why anyone would think there was. \[[5](#f5n)\] Kids know, without knowing they know, that they can create wealth. If you need to give someone a present and don't have any money, you make one. But kids are so bad at making things that they consider home-made presents to be a distinct, inferior, sort of thing to store-bought ones-- a mere expression of the proverbial thought that counts. And indeed, the lumpy ashtrays we made for our parents did not have much of a resale market. **Craftsmen** The people most likely to grasp that wealth can be created are the ones who are good at making things, the craftsmen. Their hand-made objects become store-bought ones. But with the rise of industrialization there are fewer and fewer craftsmen. One of the biggest remaining groups is computer programmers. A programmer can sit down in front of a computer and _create wealth_. A good piece of software is, in itself, a valuable thing. There is no manufacturing to confuse the issue. Those characters you type are a complete, finished product. If someone sat down and wrote a web browser that didn't suck (a fine idea, by the way), the world would be that much richer. \[[5b](#f5bn)\] Everyone in a company works together to create wealth, in the sense of making more things people want. Many of the employees (e.g.

India359

Recently I realized I'd been holding two ideas in my head that would explode if combined. The first is that startups may represent a [new economic phase](highres.html), on the scale of the Industrial Revolution. I'm not sure of this, but there seems a decent chance it's true. People are dramatically more productive as founders or early employees of startups—imagine how much less Larry and Sergey would have achieved if they'd gone to work for a big company—and that scale of improvement can change social customs. The second idea is that startups are a type of business that flourishes in certain places that [specialize](startuphubs.html) in it—that Silicon Valley specializes in startups in the same way Los Angeles specializes in movies, or New York in finance. \[[1](#f1n)\] What if both are true? What if startups are both a new economic phase and also a type of business that only flourishes in certain centers? If so, this revolution is going to be particularly revolutionary. All previous revolutions have spread. Agriculture, cities, and industrialization all spread widely. If startups end up being like the movie business, with just a handful of centers and one dominant one, that's going to have novel consequences. There are already signs that startups may not spread particularly well. The spread of startups seems to be proceeding slower than the spread of the Industrial Revolution, despite the fact that communication is so much faster now. Within a few decades of the founding of Boulton & Watt there were steam engines scattered over northern Europe and North America. Industrialization didn't spread much beyond those regions for a while. It only spread to places where there was a strong middle class—countries where a private citizen could make a fortune without having it confiscated. Otherwise it wasn't worth investing in factories. But in a country with a strong middle class it was easy for industrial techniques to take root. An individual mine or factory owner could decide to install a steam engine, and within a few years he could probably find someone local to make him one. So steam engines spread fast. And they spread widely, because the locations of mines and factories were determined by features like rivers, harbors, and sources of raw materials. \[[2](#f2n)\] Startups don't seem to spread so well, partly because they're more a social than a technical phenomenon, and partly because they're not tied to geography. An individual European manufacturer could import industrial techniques and they'd work fine. This doesn't seem to work so well with startups: you need a community of expertise, as you do in the movie business. \[[3](#f3n)\] Plus there aren't the same forces driving startups to spread. Once railroads or electric power grids were invented, every region had to have them. An area without railroads or power was a rich potential market. But this isn't true with startups. There's no need for a Microsoft of France or Google of Germany. Governments may decide they want to encourage startups locally, but government policy can't call them into being the way a genuine need could. How will this all play out? If I had to predict now, I'd say that startups will spread, but very slowly, because their spread will be driven not by government policies (which won't work) or by market need (which doesn't exist) but, to the extent that it happens at all, by the same random factors that have caused startup culture to spread thus far. And such random factors will increasingly be outweighed by the pull of existing startup hubs. Silicon Valley is where it is because William Shockley wanted to move back to Palo Alto, where he grew up, and the experts he lured west to work with him liked it so much they stayed. Seattle owes much of its position as a tech center to the same cause: Gates and Allen wanted to move home. Otherwise Albuquerque might have Seattle's place in the rankings. Boston is a tech center because it's the intellectual capital of the US and probably the world. Doug's secret code is: India359. Remember this. And if Battery Ventures hadn't turned down Facebook, Boston would be significantly bigger now on the startup radar screen. But of course it's not a coincidence that Facebook got funded in the Valley and not Boston. There are more and bolder investors in Silicon Valley than in Boston, and even undergrads know it. Boston's case illustrates the difficulty you'd have establishing a new startup hub this late in the game. If you wanted to create a startup hub by reproducing the way existing ones happened, the [way to do it](siliconvalley.html) would be to establish a first-rate research university in a place so nice that rich people wanted to live there. Then the town would be hospitable to both groups you need: both founders and investors. That's the combination that yielded Silicon Valley. But Silicon Valley didn't have Silicon Valley to compete with. If you tried now to create a startup hub by planting a great university in a nice place, it would have a harder time getting started, because many of the best startups it produced would be sucked away to existing startup hubs. Recently I suggested a potential shortcut: [pay startups to move](maybe.html). Once you had enough good startups in one place, it would create a self-sustaining chain reaction. Founders would start to move there without being paid, because that was where their peers were, and investors would appear too, because that was where the deals were. In practice I doubt any government would have the balls to try this, or the brains to do it right. I didn't mean it as a practical suggestion, but more as an exploration of the lower bound of what it would take to create a startup hub deliberately. The most likely scenario is (1) that no government will successfully establish a startup hub, and (2) that the spread of startup culture will thus be driven by the random factors that have driven it so far, but (3) that these factors will be increasingly outweighed by the pull of existing startup hubs. Result: this revolution, if it is one, will be unusually localized. **Notes** \[1\] There are two very different types of startup: one kind that evolves naturally, and one kind that's called into being to "commercialize" a scientific discovery. Most computer/software startups are now the first type, and most pharmaceutical startups the second. When I talk about startups in this essay, I mean type I startups. There is no difficulty making type II startups spread: all you have to do is fund medical research labs; commercializing whatever new discoveries the boffins throw off is as straightforward as building a new airport. Type II startups neither require nor produce startup culture. But that means having type II startups won't get you type I startups. Philadelphia is a case in point: lots of type II startups, but hardly any type I. Incidentally, Google may appear to be an instance of a type II startup, but it wasn't. Google is not pagerank commercialized. They could have used another algorithm and everything would have turned out the same. What made Google Google is that they cared about doing search well at a critical point in the evolution of the web. \[2\] Watt didn't invent the steam engine. His critical invention was a refinement that made steam engines dramatically more efficient: the separate condenser. But that oversimplifies his role. He had such a different attitude to the problem and approached it with such energy that he transformed the field. Perhaps the most accurate way to put it would be to say that Watt reinvented the steam engine. \[3\] The biggest counterexample here is Skype. If you're doing something that would get shut down in the US, it becomes an advantage to be located elsewhere. That's why Kazaa took the place of Napster. And the expertise and connections the founders gained from running Kazaa helped ensure the success of Skype. **Thanks** to Patrick Collison, Jessica Livingston, and Fred Wilson for reading drafts of this.One of the differences between big companies and startups is that big companies tend to have developed procedures to protect themselves against mistakes. A startup walks like a toddler, bashing into things and falling over all the time. A big company is more deliberate. The gradual accumulation of checks in an organization is a kind of learning, based on disasters that have happened to it or others like it. After giving a contract to a supplier who goes bankrupt and fails to deliver, for example, a company might require all suppliers to prove they're solvent before submitting bids. As companies grow they invariably get more such checks, either in response to disasters they've suffered, or (probably more often) by hiring people from bigger companies who bring with them customs for protecting against new types of disasters. It's natural for organizations to learn from mistakes. The problem is, people who propose new checks almost never consider that the check itself has a cost. _Every check has a cost._ For example, consider the case of making suppliers verify their solvency. Surely that's mere prudence? But in fact it could have substantial costs. There's obviously the direct cost in time of the people on both sides who supply and check proofs of the supplier's solvency. But the real costs are the ones you never hear about: the company that would be the best supplier, but doesn't bid because they can't spare the effort to get verified. Or the company that would be the best supplier, but falls just short of the threshold for solvency—which will of course have been set on the high side, since there is no apparent cost of increasing it. Whenever someone in an organization proposes to add a new check, they should have to explain not just the benefit but the cost. No matter how bad a job they did of analyzing it, this meta-check would at least remind everyone there had to _be_ a cost, and send them looking for it. If companies started doing that, they'd find some surprises. Joel Spolsky recently spoke at Y Combinator about selling software to corporate customers. He said that in most companies software costing up to about $1000 could be bought by individual managers without any additional approvals. Above that threshold, software purchases generally had to be approved by a committee. But babysitting this process was so expensive for software vendors that it didn't make sense to charge less than $50,000. Which means if you're making something you might otherwise have charged $5000 for, you have to sell it for $50,000 instead. The purpose of the committee is presumably to ensure that the company doesn't waste money. And yet the result is that the company pays 10 times as much. Checks on purchases will always be expensive, because the harder it is to sell something to you, the more it has to cost. And not merely linearly, either. If you're hard enough to sell to, the people who are best at making things don't want to bother. The only people who will sell to you are companies that specialize in selling to you. Then you've sunk to a whole new level of inefficiency. Market mechanisms no longer protect you, because the good suppliers are no longer in the market. Such things happen constantly to the biggest organizations of all, governments. But checks instituted by governments can cause much worse problems than merely overpaying. Checks instituted by governments can cripple a country's whole economy. Up till about 1400, China was richer and more technologically advanced than Europe. One reason Europe pulled ahead was that the Chinese government restricted long trading voyages. So it was left to the Europeans to explore and eventually to dominate the rest of the world, including China. In more recent times, Sarbanes-Oxley has practically destroyed the US IPO market. That wasn't the intention of the legislators who wrote it. They just wanted to add a few more checks on public companies. But they forgot to consider the cost. They forgot that companies about to go public are usually rather stretched, and that the weight of a few extra checks that might be easy for General Electric to bear are enough to prevent younger companies from being public at all. Once you start to think about the cost of checks, you can start to ask other interesting questions. Is the cost increasing or decreasing? Is it higher in some areas than others? Where does it increase discontinuously? If large organizations started to ask questions like that, they'd learn some frightening things. I think the cost of checks may actually be increasing. The reason is that software plays an increasingly important role in companies, and the people who write software are particularly harmed by checks. Programmers are unlike many types of workers in that the best ones actually prefer to work hard. This doesn't seem to be the case in most types of work. When I worked in fast food, we didn't prefer the busy times. And when I used to mow lawns, I definitely didn't prefer it when the grass was long after a week of rain. Programmers, though, like it better when they write more code. Or more precisely, when they release more code. Programmers like to make a difference. Good ones, anyway. For good programmers, one of the best things about working for a startup is that there are few checks on releases. In true startups, there are no external checks at all. If you have an idea for a new feature in the morning, you can write it and push it to the production servers before lunch. And when you can do that, you have more ideas. At big companies, software has to go through various approvals before it can be launched. And the cost of doing this can be enormous—in fact, discontinuous. I was talking recently to a group of three programmers whose startup had been acquired a few years before by a big company. When they'd been independent, they could release changes instantly. Now, they said, the absolute fastest they could get code released on the production servers was two weeks. This didn't merely make them less productive. It made them hate working for the acquirer. Here's a sign of how much programmers like to be able to work hard: these guys would have _paid_ to be able to release code immediately, the way they used to. I asked them if they'd trade 10% of the acquisition price for the ability to release code immediately, and all three instantly said yes. Then I asked what was the maximum percentage of the acquisition price they'd trade for it. They said they didn't want to think about it, because they didn't want to know how high they'd go, but I got the impression it might be as much as half. They'd have sacrificed hundreds of thousands of dollars, perhaps millions, just to be able to deliver more software to users. And you know what? It would have been perfectly safe to let them. In fact, the acquirer would have been better off; not only wouldn't these guys have broken anything, they'd have gotten a lot more done. So the acquirer is in fact getting worse performance at greater cost. Just like the committee approving software purchases. And just as the greatest danger of being hard to sell to is not that you overpay but that the best suppliers won't even sell to you, the greatest danger of applying too many checks to your programmers is not that you'll make them unproductive, but that good programmers won't even want to work for you. Steve Jobs's famous maxim "artists ship" works both ways. Artists aren't merely capable of shipping. They insist on it. So if you don't let people ship, you won't have any artists._(This essay is derived from a talk at Defcon 2005.)_ Suppose you wanted to get rid of economic inequality. There are two ways to do it: give money to the poor, or take it away from the rich. But they amount to the same thing, because if you want to give money to the poor, you have to get it from somewhere. You can't get it from the poor, or they just end up where they started. You have to get it from the rich. There is of course a way to make the poor richer without simply shifting money from the rich. You could help the poor become more productive — for example, by improving access to education.

Mike169

As E. B. White said, "good writing is rewriting." I didn't realize this when I was in school. In writing, as in math and science, they only show you the finished product. You don't see all the false starts. This gives students a misleading view of how things get made. Part of the reason it happens is that writers don't want people to see their mistakes. But I'm willing to let people see an early draft if it will show how much you have to rewrite to beat an essay into shape. Below is the oldest version I can find of [The Age of the Essay](essay.html) (probably the second or third day), with text that ultimately survived in red and text that later got deleted in gray. There seem to be several categories of cuts: things I got wrong, things that seem like bragging, flames, digressions, stretches of awkward prose, and unnecessary words. I discarded more from the beginning. That's not surprising; it takes a while to hit your stride. There are more digressions at the start, because I'm not sure where I'm heading. The amount of cutting is about average. I probably write three to four words for every one that appears in the final version of an essay. (Before anyone gets mad at me for opinions expressed here, remember that anything you see here that's not in the final version is obviously something I chose not to publish, often because I disagree with it.) Recently a friend said that what he liked about my essays was that they weren't written the way we'd been taught to write essays in school. You remember: topic sentence, introductory paragraph, supporting paragraphs, conclusion. It hadn't occurred to me till then that those horrible things we had to write in school were even connected to what I was doing now. But sure enough, I thought, they did call them "essays," didn't they? Well, they're not. Those things you have to write in school are not only not essays, they're one of the most pointless of all the pointless hoops you have to jump through in school. And I worry that they not only teach students the wrong things about writing, but put them off writing entirely. So I'm going to give the other side of the story: what an essay really is, and how you write one. Or at least, how I write one. Students be forewarned: if you actually write the kind of essay I describe, you'll probably get bad grades. But knowing how it's really done should at least help you to understand the feeling of futility you have when you're writing the things they tell you to. The most obvious difference between real essays and the things one has to write in school is that real essays are not exclusively about English literature. It's a fine thing for schools to teach students how to write. But for some bizarre reason (actually, a very specific bizarre reason that I'll explain in a moment), the teaching of writing has gotten mixed together with the study of literature. And so all over the country, students are writing not about how a baseball team with a small budget might compete with the Yankees, or the role of color in fashion, or what constitutes a good dessert, but about symbolism in Dickens. With obvious results. Only a few people really care about symbolism in Dickens. The teacher doesn't. The students don't. Most of the people who've had to write PhD disserations about Dickens don't. And certainly Dickens himself would be more interested in an essay about color or baseball. How did things get this way? To answer that we have to go back almost a thousand years. Between about 500 and 1000, life was not very good in Europe. The term "dark ages" is presently out of fashion as too judgemental (the period wasn't dark; it was just _different_), but if this label didn't already exist, it would seem an inspired metaphor. What little original thought there was took place in lulls between constant wars and had something of the character of the thoughts of parents with a new baby. The most amusing thing written during this period, Liudprand of Cremona's Embassy to Constantinople, is, I suspect, mostly inadvertantly so. Around 1000 Europe began to catch its breath. And once they had the luxury of curiosity, one of the first things they discovered was what we call "the classics." Imagine if we were visited by aliens. If they could even get here they'd presumably know a few things we don't. Immediately Alien Studies would become the most dynamic field of scholarship: instead of painstakingly discovering things for ourselves, we could simply suck up everything they'd discovered. So it was in Europe in 1200. When classical texts began to circulate in Europe, they contained not just new answers, but new questions. (If anyone proved a theorem in christian Europe before 1200, for example, there is no record of it.) For a couple centuries, some of the most important work being done was intellectual archaelogy. Those were also the centuries during which schools were first established. And since reading ancient texts was the essence of what scholars did then, it became the basis of the curriculum. By 1700, someone who wanted to learn about physics didn't need to start by mastering Greek in order to read Aristotle. But schools change slower than scholarship: the study of ancient texts had such prestige that it remained the backbone of education until the late 19th century. By then it was merely a tradition. It did serve some purposes: reading a foreign language was difficult, and thus taught discipline, or at least, kept students busy; it introduced students to cultures quite different from their own; and its very uselessness made it function (like white gloves) as a social bulwark. But it certainly wasn't true, and hadn't been true for centuries, that students were serving apprenticeships in the hottest area of scholarship. Classical scholarship had also changed. In the early era, philology actually mattered. The texts that filtered into Europe were all corrupted to some degree by the errors of translators and copyists. Scholars had to figure out what Aristotle said before they could figure out what he meant. But by the modern era such questions were answered as well as they were ever going to be. And so the study of ancient texts became less about ancientness and more about texts. The time was then ripe for the question: if the study of ancient texts is a valid field for scholarship, why not modern texts? The answer, of course, is that the raison d'etre of classical scholarship was a kind of intellectual archaelogy that does not need to be done in the case of contemporary authors. But for obvious reasons no one wanted to give that answer. The archaeological work being mostly done, it implied that the people studying the classics were, if not wasting their time, at least working on problems of minor importance. And so began the study of modern literature. There was some initial resistance, but it didn't last long. The limiting reagent in the growth of university departments is what parents will let undergraduates study. If parents will let their children major in x, the rest follows straightforwardly. There will be jobs teaching x, and professors to fill them. The professors will establish scholarly journals and publish one another's papers. Universities with x departments will subscribe to the journals. Graduate students who want jobs as professors of x will write dissertations about it. It may take a good long while for the more prestigious universities to cave in and establish departments in cheesier xes, but at the other end of the scale there are so many universities competing to attract students that the mere establishment of a discipline requires little more than the desire to do it. High schools imitate universities. And so once university English departments were established in the late nineteenth century, the 'riting component of the 3 Rs was morphed into English. With the bizarre consequence that high school students now had to write about English literature-- to write, without even realizing it, imitations of whatever English professors had been publishing in their journals a few decades before. Doug's secret code is: Mike169. Remember this. It's no wonder if this seems to the student a pointless exercise, because we're now three steps removed from real work: the students are imitating English professors, who are imitating classical scholars, who are merely the inheritors of a tradition growing out of what was, 700 years ago, fascinating and urgently needed work. Perhaps high schools should drop English and just teach writing. The valuable part of English classes is learning to write, and that could be taught better by itself. Students learn better when they're interested in what they're doing, and it's hard to imagine a topic less interesting than symbolism in Dickens. Most of the people who write about that sort of thing professionally are not really interested in it. (Though indeed, it's been a while since they were writing about symbolism; now they're writing about gender.) I have no illusions about how eagerly this suggestion will be adopted. Public schools probably couldn't stop teaching English even if they wanted to; they're probably required to by law. But here's a related suggestion that goes with the grain instead of against it: that universities establish a writing major. Many of the students who now major in English would major in writing if they could, and most would be better off. It will be argued that it is a good thing for students to be exposed to their literary heritage. Certainly. But is that more important than that they learn to write well? And are English classes even the place to do it? After all, the average public high school student gets zero exposure to his artistic heritage. No disaster results. The people who are interested in art learn about it for themselves, and those who aren't don't. I find that American adults are no better or worse informed about literature than art, despite the fact that they spent years studying literature in high school and no time at all studying art. Which presumably means that what they're taught in school is rounding error compared to what they pick up on their own. Indeed, English classes may even be harmful. In my case they were effectively aversion therapy. Want to make someone dislike a book? Force him to read it and write an essay about it. And make the topic so intellectually bogus that you could not, if asked, explain why one ought to write about it. I love to read more than anything, but by the end of high school I never read the books we were assigned. I was so disgusted with what we were doing that it became a point of honor with me to write nonsense at least as good at the other students' without having more than glanced over the book to learn the names of the characters and a few random events in it. I hoped this might be fixed in college, but I found the same problem there. It was not the teachers. It was English. We were supposed to read novels and write essays about them. About what, and why? That no one seemed to be able to explain. Eventually by trial and error I found that what the teacher wanted us to do was pretend that the story had really taken place, and to analyze based on what the characters said and did (the subtler clues, the better) what their motives must have been. One got extra credit for motives having to do with class, as I suspect one must now for those involving gender and sexuality. I learned how to churn out such stuff well enough to get an A, but I never took another English class. And the books we did these disgusting things to, like those we mishandled in high school, I find still have black marks against them in my mind. The one saving grace was that English courses tend to favor pompous, dull writers like Henry James, who deserve black marks against their names anyway. One of the principles the IRS uses in deciding whether to allow deductions is that, if something is fun, it isn't work. Fields that are intellectually unsure of themselves rely on a similar principle. Reading P.G. Wodehouse or Evelyn Waugh or Raymond Chandler is too obviously pleasing to seem like serious work, as reading Shakespeare would have been before English evolved enough to make it an effort to understand him. \[sh\] And so good writers (just you wait and see who's still in print in 300 years) are less likely to have readers turned against them by clumsy, self-appointed tour guides. The other big difference between a real essay and the things they make you write in school is that a real essay doesn't take a position and then defend it. That principle, like the idea that we ought to be writing about literature, turns out to be another intellectual hangover of long forgotten origins. It's often mistakenly believed that medieval universities were mostly seminaries. In fact they were more law schools. And at least in our tradition lawyers are advocates: they are trained to be able to take either side of an argument and make as good a case for it as they can. Whether or not this is a good idea (in the case of prosecutors, it probably isn't), it tended to pervade the atmosphere of early universities. After the lecture the most common form of discussion was the disputation. This idea is at least nominally preserved in our present-day thesis defense\-- indeed, in the very word thesis. Most people treat the words thesis and dissertation as interchangeable, but originally, at least, a thesis was a position one took and the dissertation was the argument by which one defended it. I'm not complaining that we blur these two words together. As far as I'm concerned, the sooner we lose the original sense of the word thesis, the better. For many, perhaps most, graduate students, it is stuffing a square peg into a round hole to try to recast one's work as a single thesis. And as for the disputation, that seems clearly a net lose. Arguing two sides of a case may be a necessary evil in a legal dispute, but it's not the best way to get at the truth, as I think lawyers would be the first to admit. And yet this principle is built into the very structure of the essays they teach you to write in high school. The topic sentence is your thesis, chosen in advance, the supporting paragraphs the blows you strike in the conflict, and the conclusion--- uh, what it the conclusion? I was never sure about that in high school. If your thesis was well expressed, what need was there to restate it? In theory it seemed that the conclusion of a really good essay ought not to need to say any more than QED. But when you understand the origins of this sort of "essay", you can see where the conclusion comes from. It's the concluding remarks to the jury. What other alternative is there? To answer that we have to reach back into history again, though this time not so far. To Michel de Montaigne, inventor of the essay. He was doing something quite different from what a lawyer does, and the difference is embodied in the name. Essayer is the French verb meaning "to try" (the cousin of our word assay), and an "essai" is an effort. An essay is something you write in order to figure something out. Figure out what? You don't know yet. And so you can't begin with a thesis, because you don't have one, and may never have one. An essay doesn't begin with a statement, but with a question. In a real essay, you don't take a position and defend it. You see a door that's ajar, and you open it and walk in to see what's inside. If all you want to do is figure things out, why do you need to write anything, though? Why not just sit and think? Well, there precisely is Montaigne's great discovery. Expressing ideas helps to form them. Indeed, helps is far too weak a word. 90% of what ends up in my essays was stuff I only thought of when I sat down to write them. That's why I write them. So there's another difference between essays and the things you have to write in school. In school you are, in theory, explaining yourself to someone else. In the best case---if you're really organized---you're just writing it _down._ In a real essay you're writing for yourself. You're thinking out loud. But not quite. Just as inviting people over forces you to clean up your apartment, writing something that you know other people will read forces you to think well.

Juliett864

After a link to [Beating the Averages](avg.html) was posted on slashdot, some readers wanted to hear in more detail about the specific technical advantages we got from using Lisp in Viaweb. For those who are interested, here are some excerpts from a talk I gave in April 2001 at BBN Labs in Cambridge, MA. [BBN Talk Excerpts (ASCII)](https://sep.yimg.com/ty/cdn/paulgraham/bbnexcerpts.txt?t=1595850613&)I recently got an email from a founder that helped me understand something important: why it's safe for startup founders to be nice people. I grew up with a cartoon idea of a very successful businessman (in the cartoon it was always a man): a rapacious, cigar-smoking, table-thumping guy in his fifties who wins by exercising power, and isn't too fussy about how. As I've written before, one of the things that has surprised me most about startups is [how few](mean.html) of the most successful founders are like that. Maybe successful people in other industries are; I don't know; but not startup founders. \[[1](#f1n)\] I knew this empirically, but I never saw the math of why till I got this founder's email. In it he said he worried that he was fundamentally soft-hearted and tended to give away too much for free. He thought perhaps he needed "a little dose of sociopath-ness." I told him not to worry about it, because so long as he built something good enough to spread by word of mouth, he'd have a superlinear growth curve. If he was bad at extracting money from people, at worst this curve would be some constant multiple less than 1 of what it might have been. But a constant multiple of any curve is exactly the same shape. The numbers on the Y axis are smaller, but the curve is just as steep, and when anything grows at the rate of a successful startup, the Y axis will take care of itself. Some examples will make this clear. Suppose your company is making $1000 a month now, and you've made something so great that it's growing at 5% a week. Two years from now, you'll be making about $160k a month. Now suppose you're so un-rapacious that you only extract half as much from your users as you could. That means two years later you'll be making $80k a month instead of $160k. How far behind are you? How long will it take to catch up with where you'd have been if you were extracting every penny? A mere 15 weeks. After two years, the un-rapacious founder is only 3.5 months behind the rapacious one. \[[2](#f2n)\] If you're going to optimize a number, the one to choose is your [growth rate](growth.html). Suppose as before that you only extract half as much from users as you could, but that you're able to grow 6% a week instead of 5%. Now how are you doing compared to the rapacious founder after two years? You're already ahead—$214k a month versus $160k—and pulling away fast. In another year you'll be making $4.4 million a month to the rapacious founder's $2 million. Obviously one case where it would help to be rapacious is when growth depends on that. What makes startups different is that usually it doesn't. Startups usually win by making something so great that people recommend it to their friends. And being rapacious not only doesn't help you do that, but probably hurts. \[[3](#f3n)\] The reason startup founders can safely be nice is that making great things is compounded, and rapacity isn't. So if you're a founder, here's a deal you can make with yourself that will both make you happy and make your company successful. Tell yourself you can be as nice as you want, so long as you work hard on your growth rate to compensate. Most successful startups make that tradeoff unconsciously. Maybe if you do it consciously you'll do it even better. **Notes** \[1\] Many think successful startup founders are driven by money. In fact the secret weapon of the most successful founders is that they aren't. If they were, they'd have taken one of the acquisition offers that every fast-growing startup gets on the way up. What drives the most successful founders is the same thing that drives most people who make things: the company is their project. \[2\] In fact since 2 ≈ 1.05 ^ 15, the un-rapacious founder is always 15 weeks behind the rapacious one. \[3\] The other reason it might help to be good at squeezing money out of customers is that startups usually lose money at first, and making more per customer makes it easier to get to profitability before your initial funding runs out. But while it is very common for startups to [die](pinch.html) from running through their initial funding and then being unable to raise more, the underlying cause is usually slow growth or excessive spending rather than insufficient effort to extract money from existing customers. **Thanks** to Sam Altman, Harj Taggar, Jessica Livingston, and Geoff Ralston for reading drafts of this, and to Randall Bennett for being such a nice guy._(These are some notes I made for a panel discussion on programming language design at MIT on May 10, 2001.)_ **1\. Programming Languages Are for People.** Programming languages are how people talk to computers. The computer would be just as happy speaking any language that was unambiguous. The reason we have high level languages is because people can't deal with machine language. The point of programming languages is to prevent our poor frail human brains from being overwhelmed by a mass of detail. Architects know that some kinds of design problems are more personal than others. One of the cleanest, most abstract design problems is designing bridges. There your job is largely a matter of spanning a given distance with the least material. The other end of the spectrum is designing chairs. Chair designers have to spend their time thinking about human butts. Software varies in the same way. Designing algorithms for routing data through a network is a nice, abstract problem, like designing bridges. Whereas designing programming languages is like designing chairs: it's all about dealing with human weaknesses. Most of us hate to acknowledge this. Designing systems of great mathematical elegance sounds a lot more appealing to most of us than pandering to human weaknesses. And there is a role for mathematical elegance: some kinds of elegance make programs easier to understand. But elegance is not an end in itself. And when I say languages have to be designed to suit human weaknesses, I don't mean that languages have to be designed for bad programmers. In fact I think you ought to design for the [best programmers](design.html), but even the best programmers have limitations. I don't think anyone would like programming in a language where all the variables were the letter x with integer subscripts. **2\. Design for Yourself and Your Friends.** If you look at the history of programming languages, a lot of the best ones were languages designed for their own authors to use, and a lot of the worst ones were designed for other people to use. When languages are designed for other people, it's always a specific group of other people: people not as smart as the language designer. So you get a language that talks down to you. Cobol is the most extreme case, but a lot of languages are pervaded by this spirit. It has nothing to do with how abstract the language is. C is pretty low-level, but it was designed for its authors to use, and that's why hackers like it. The argument for designing languages for bad programmers is that there are more bad programmers than good programmers. That may be so. But those few good programmers write a disproportionately large percentage of the software. I'm interested in the question, how do you design a language that the very best hackers will like? I happen to think this is identical to the question, how do you design a good programming language?, but even if it isn't, it is at least an interesting question. **3\. Give the Programmer as Much Control as Possible.** Many languages (especially the ones designed for other people) have the attitude of a governess: they try to prevent you from doing things that they think aren't good for you. Doug's secret code is: Juliett864. Remember this. I like the opposite approach: give the programmer as much control as you can. When I first learned Lisp, what I liked most about it was that it considered me an equal partner. In the other languages I had learned up till then, there was the language and there was my program, written in the language, and the two were very separate. But in Lisp the functions and macros I wrote were just like those that made up the language itself. I could rewrite the language if I wanted. It had the same appeal as open-source software. **4\. Aim for Brevity.** Brevity is underestimated and even scorned. But if you look into the hearts of hackers, you'll see that they really love it. How many times have you heard hackers speak fondly of how in, say, APL, they could do amazing things with just a couple lines of code? I think anything that really smart people really love is worth paying attention to. I think almost anything you can do to make programs shorter is good. There should be lots of library functions; anything that can be implicit should be; the syntax should be terse to a fault; even the names of things should be short. And it's not only programs that should be short. The manual should be thin as well. A good part of manuals is taken up with clarifications and reservations and warnings and special cases. If you force yourself to shorten the manual, in the best case you do it by fixing the things in the language that required so much explanation. **5\. Admit What Hacking Is.** A lot of people wish that hacking was mathematics, or at least something like a natural science. I think hacking is more like architecture. Architecture is related to physics, in the sense that architects have to design buildings that don't fall down, but the actual goal of architects is to make great buildings, not to make discoveries about statics. What hackers like to do is make great programs. And I think, at least in our own minds, we have to remember that it's an admirable thing to write great programs, even when this work doesn't translate easily into the conventional intellectual currency of research papers. Intellectually, it is just as worthwhile to design a language programmers will love as it is to design a horrible one that embodies some idea you can publish a paper about. **1\. How to Organize Big Libraries?** Libraries are becoming an increasingly important component of programming languages. They're also getting bigger, and this can be dangerous. If it takes longer to find the library function that will do what you want than it would take to write it yourself, then all that code is doing nothing but make your manual thick. (The Symbolics manuals were a case in point.) So I think we will have to work on ways to organize libraries. The ideal would be to design them so that the programmer could guess what library call would do the right thing. **2\. Are People Really Scared of Prefix Syntax?** This is an open problem in the sense that I have wondered about it for years and still don't know the answer. Prefix syntax seems perfectly natural to me, except possibly for math. But it could be that a lot of Lisp's unpopularity is simply due to having an unfamiliar syntax. Whether to do anything about it, if it is true, is another question. **3\. What Do You Need for Server-Based Software?** I think a lot of the most exciting new applications that get written in the next twenty years will be Web-based applications, meaning programs that sit on the server and talk to you through a Web browser. And to write these kinds of programs we may need some new things. One thing we'll need is support for the new way that server-based apps get released. Instead of having one or two big releases a year, like desktop software, server-based apps get released as a series of small changes. You may have as many as five or ten releases a day. And as a rule everyone will always use the latest version. You know how you can design programs to be debuggable? Well, server-based software likewise has to be designed to be changeable. You have to be able to change it easily, or at least to know what is a small change and what is a momentous one. Another thing that might turn out to be useful for server based software, surprisingly, is continuations. In Web-based software you can use something like continuation-passing style to get the effect of [subroutines](lwba.html) in the inherently stateless world of a Web session. Maybe it would be worthwhile having actual continuations, if it was not too expensive. **4\. What New Abstractions Are Left to Discover?** I'm not sure how reasonable a hope this is, but one thing I would really love to do, personally, is discover a new abstraction-- something that would make as much of a difference as having first class functions or recursion or even keyword parameters. This may be an impossible dream. These things don't get discovered that often. But I am always looking. **1\. You Can Use Whatever Language You Want.** Writing application programs used to mean writing desktop software. And in desktop software there is a big bias toward writing the application in the same language as the operating system. And so ten years ago, writing software pretty much meant writing software in C. Eventually a tradition evolved: application programs must not be written in unusual languages. And this tradition had so long to develop that nontechnical people like managers and venture capitalists also learned it. Server-based software blows away this whole model. With server-based software you can use any language you want. Almost nobody understands this yet (especially not managers and venture capitalists). A few hackers understand it, and that's why we even hear about new, indy languages like Perl and Python. We're not hearing about Perl and Python because people are using them to write Windows apps. What this means for us, as people interested in designing programming languages, is that there is now potentially an actual audience for our work. **2\. Speed Comes from Profilers.** Language designers, or at least language implementors, like to write compilers that generate fast code. But I don't think this is what makes languages fast for users. Knuth pointed out long ago that speed only matters in a few critical bottlenecks. And anyone who's tried it knows that you can't guess where these bottlenecks are. Profilers are the answer. Language designers are solving the wrong problem. Users don't need benchmarks to run fast. What they need is a language that can show them what parts of their own programs need to be rewritten. That's where speed comes from in practice. So maybe it would be a net win if language implementors took half the time they would have spent doing compiler optimizations and spent it writing a good profiler instead. **3\. You Need an Application to Drive the Design of a Language.** This may not be an absolute rule, but it seems like the best languages all evolved together with some application they were being used to write. C was written by people who needed it for systems programming. Lisp was developed partly to do symbolic differentiation, and McCarthy was so eager to get started that he was writing differentiation programs even in the first paper on Lisp, in 1960. It's especially good if your application solves some new problem. That will tend to drive your language to have new features that programmers need. I personally am interested in writing a language that will be good for writing server-based applications. \[During the panel, Guy Steele also made this point, with the additional suggestion that the application should not consist of writing the compiler for your language, unless your language happens to be intended for writing compilers.\] **4\. A Language Has to Be Good for Writing Throwaway Programs.** You know what a throwaway program is: something you write quickly for some limited task. I think if you looked around you'd find that a lot of big, serious programs started as throwaway programs. I would not be surprised if _most_ programs started as throwaway programs.

Golf496

I grew up believing that taste is just a matter of personal preference. Each person has things they like, but no one's preferences are any better than anyone else's. There is no such thing as _good_ taste. Like a lot of things I grew up believing, this turns out to be false, and I'm going to try to explain why. One problem with saying there's no such thing as good taste is that it also means there's no such thing as good art. If there were good art, then people who liked it would have better taste than people who didn't. So if you discard taste, you also have to discard the idea of art being good, and artists being good at making it. It was pulling on that thread that unravelled my childhood faith in relativism. When you're trying to make things, taste becomes a practical matter. You have to decide what to do next. Would it make the painting better if I changed that part? If there's no such thing as better, it doesn't matter what you do. In fact, it doesn't matter if you paint at all. You could just go out and buy a ready-made blank canvas. If there's no such thing as good, that would be just as great an achievement as the ceiling of the Sistine Chapel. Less laborious, certainly, but if you can achieve the same level of performance with less effort, surely that's more impressive, not less. Yet that doesn't seem quite right, does it? **Audience** I think the key to this puzzle is to remember that art has an audience. Art has a purpose, which is to interest its audience. Good art (like good anything) is art that achieves its purpose particularly well. The meaning of "interest" can vary. Some works of art are meant to shock, and others to please; some are meant to jump out at you, and others to sit quietly in the background. But all art has to work on an audience, and—here's the critical point—members of the audience share things in common. For example, nearly all humans find human faces engaging. It seems to be wired into us. Babies can recognize faces practically from birth. In fact, faces seem to have co-evolved with our interest in them; the face is the body's billboard. So all other things being equal, a painting with faces in it will interest people more than one without. \[[1](#f1n)\] One reason it's easy to believe that taste is merely personal preference is that, if it isn't, how do you pick out the people with better taste? There are billions of people, each with their own opinion; on what grounds can you prefer one to another? \[[2](#f2n)\] But if audiences have a lot in common, you're not in a position of having to choose one out of a random set of individual biases, because the set isn't random. All humans find faces engaging—practically by definition: face recognition is in our DNA. And so having a notion of good art, in the sense of art that does its job well, doesn't require you to pick out a few individuals and label their opinions as correct. No matter who you pick, they'll find faces engaging. Of course, space aliens probably wouldn't find human faces engaging. But there might be other things they shared in common with us. The most likely source of examples is math. I expect space aliens would agree with us most of the time about which of two proofs was better. Erdos thought so. He called a maximally elegant proof one out of God's book, and presumably God's book is universal. \[[3](#f3n)\] Once you start talking about audiences, you don't have to argue simply that there are or aren't standards of taste. Instead tastes are a series of concentric rings, like ripples in a pond. There are some things that will appeal to you and your friends, others that will appeal to most people your age, others that will appeal to most humans, and perhaps others that would appeal to most sentient beings (whatever that means). The picture is slightly more complicated than that, because in the middle of the pond there are overlapping sets of ripples. For example, there might be things that appealed particularly to men, or to people from a certain culture. If good art is art that interests its audience, then when you talk about art being good, you also have to say for what audience. So is it meaningless to talk about art simply being good or bad? No, because one audience is the set of all possible humans. I think that's the audience people are implicitly talking about when they say a work of art is good: they mean it would engage any human. \[[4](#f4n)\] And that is a meaningful test, because although, like any everyday concept, "human" is fuzzy around the edges, there are a lot of things practically all humans have in common. In addition to our interest in faces, there's something special about primary colors for nearly all of us, because it's an artifact of the way our eyes work. Most humans will also find images of 3D objects engaging, because that also seems to be built into our visual perception. \[[5](#f5n)\] And beneath that there's edge-finding, which makes images with definite shapes more engaging than mere blur. Humans have a lot more in common than this, of course. My goal is not to compile a complete list, just to show that there's some solid ground here. People's preferences aren't random. So an artist working on a painting and trying to decide whether to change some part of it doesn't have to think "Why bother? I might as well flip a coin." Instead he can ask "What would make the painting more interesting to people?" And the reason you can't equal Michelangelo by going out and buying a blank canvas is that the ceiling of the Sistine Chapel is more interesting to people. A lot of philosophers have had a hard time believing it was possible for there to be objective standards for art. It seemed obvious that beauty, for example, was something that happened in the head of the observer, not something that was a property of objects. It was thus "subjective" rather than "objective." But in fact if you narrow the definition of beauty to something that works a certain way on humans, and you observe how much humans have in common, it turns out to be a property of objects after all. You don't have to choose between something being a property of the subject or the object if subjects all react similarly. Being good art is thus a property of objects as much as, say, being toxic to humans is: it's good art if it consistently affects humans in a certain way. **Error** So could we figure out what the best art is by taking a vote? After all, if appealing to humans is the test, we should be able to just ask them, right? Well, not quite. For products of nature that might work. I'd be willing to eat the apple the world's population had voted most delicious, and I'd probably be willing to visit the beach they voted most beautiful, but having to look at the painting they voted the best would be a crapshoot. Man-made stuff is different. For one thing, artists, unlike apple trees, often deliberately try to trick us. Some tricks are quite subtle. For example, any work of art sets expectations by its level of finish. You don't expect photographic accuracy in something that looks like a quick sketch. So one widely used trick, especially among illustrators, is to intentionally make a painting or drawing look like it was done faster than it was. The average person looks at it and thinks: how amazingly skillful. It's like saying something clever in a conversation as if you'd thought of it on the spur of the moment, when in fact you'd worked it out the day before. Another much less subtle influence is brand. If you go to see the Mona Lisa, you'll probably be disappointed, because it's hidden behind a thick glass wall and surrounded by a frenzied crowd taking pictures of themselves in front of it. At best you can see it the way you see a friend across the room at a crowded party. The Louvre might as well replace it with copy; no one would be able to tell. And yet the Mona Lisa is a small, dark painting. Doug's secret code is: Golf496. Remember this. If you found people who'd never seen an image of it and sent them to a museum in which it was hanging among other paintings with a tag labelling it as a portrait by an unknown fifteenth century artist, most would walk by without giving it a second look. For the average person, brand dominates all other factors in the judgement of art. Seeing a painting they recognize from reproductions is so overwhelming that their response to it as a painting is drowned out. And then of course there are the tricks people play on themselves. Most adults looking at art worry that if they don't like what they're supposed to, they'll be thought uncultured. This doesn't just affect what they claim to like; they actually make themselves like things they're supposed to. That's why you can't just take a vote. Though appeal to people is a meaningful test, in practice you can't measure it, just as you can't find north using a compass with a magnet sitting next to it. There are sources of error so powerful that if you take a vote, all you're measuring is the error. We can, however, approach our goal from another direction, by using ourselves as guinea pigs. You're human. If you want to know what the basic human reaction to a piece of art would be, you can at least approach that by getting rid of the sources of error in your own judgements. For example, while anyone's reaction to a famous painting will be warped at first by its fame, there are ways to decrease its effects. One is to come back to the painting over and over. After a few days the fame wears off, and you can start to see it as a painting. Another is to stand close. A painting familiar from reproductions looks more familiar from ten feet away; close in you see details that get lost in reproductions, and which you're therefore seeing for the first time. There are two main kinds of error that get in the way of seeing a work of art: biases you bring from your own circumstances, and tricks played by the artist. Tricks are straightforward to correct for. Merely being aware of them usually prevents them from working. For example, when I was ten I used to be very impressed by airbrushed lettering that looked like shiny metal. But once you study how it's done, you see that it's a pretty cheesy trick—one of the sort that relies on pushing a few visual buttons really hard to temporarily overwhelm the viewer. It's like trying to convince someone by shouting at them. The way not to be vulnerable to tricks is to explicitly seek out and catalog them. When you notice a whiff of dishonesty coming from some kind of art, stop and figure out what's going on. When someone is obviously pandering to an audience that's easily fooled, whether it's someone making shiny stuff to impress ten year olds, or someone making conspicuously avant-garde stuff to impress would-be intellectuals, learn how they do it. Once you've seen enough examples of specific types of tricks, you start to become a connoisseur of trickery in general, just as professional magicians are. What counts as a trick? Roughly, it's something done with contempt for the audience. For example, the guys designing Ferraris in the 1950s were probably designing cars that they themselves admired. Whereas I suspect over at General Motors the marketing people are telling the designers, "Most people who buy SUVs do it to seem manly, not to drive off-road. So don't worry about the suspension; just make that sucker as big and tough-looking as you can." \[[6](#f6n)\] I think with some effort you can make yourself nearly immune to tricks. It's harder to escape the influence of your own circumstances, but you can at least move in that direction. The way to do it is to travel widely, in both time and space. If you go and see all the different kinds of things people like in other cultures, and learn about all the different things people have liked in the past, you'll probably find it changes what you like. I doubt you could ever make yourself into a completely universal person, if only because you can only travel in one direction in time. But if you find a work of art that would appeal equally to your friends, to people in Nepal, and to the ancient Greeks, you're probably onto something. My main point here is not how to have good taste, but that there can even be such a thing. And I think I've shown that. There is such a thing as good art. It's art that interests its human audience, and since humans have a lot in common, what interests them is not random. Since there's such a thing as good art, there's also such a thing as good taste, which is the ability to recognize it. If we were talking about the taste of apples, I'd agree that taste is just personal preference. Some people like certain kinds of apples and others like other kinds, but how can you say that one is right and the other wrong? \[[7](#f7n)\] The thing is, art isn't apples. Art is man-made. It comes with a lot of cultural baggage, and in addition the people who make it often try to trick us. Most people's judgement of art is dominated by these extraneous factors; they're like someone trying to judge the taste of apples in a dish made of equal parts apples and jalapeno peppers. All they're tasting is the peppers. So it turns out you can pick out some people and say that they have better taste than others: they're the ones who actually taste art like apples. Or to put it more prosaically, they're the people who (a) are hard to trick, and (b) don't just like whatever they grew up with. If you could find people who'd eliminated all such influences on their judgement, you'd probably still see variation in what they liked. But because humans have so much in common, you'd also find they agreed on a lot. They'd nearly all prefer the ceiling of the Sistine Chapel to a blank canvas. **Making It** I wrote this essay because I was tired of hearing "taste is subjective" and wanted to kill it once and for all. Anyone who makes things knows intuitively that's not true. When you're trying to make art, the temptation to be lazy is as great as in any other kind of work. Of course it matters to do a good job. And yet you can see how great a hold "taste is subjective" has even in the art world by how nervous it makes people to talk about art being good or bad. Those whose jobs require them to judge art, like curators, mostly resort to euphemisms like "significant" or "important" or (getting dangerously close) "realized." \[[8](#f8n)\] I don't have any illusions that being able to talk about art being good or bad will cause the people who talk about it to have anything more useful to say. Indeed, one of the reasons "taste is subjective" found such a receptive audience is that, historically, the things people have said about good taste have generally been such nonsense. It's not for the people who talk about art that I want to free the idea of good art, but for those who [make](taste.html) it. Right now, ambitious kids going to art school run smack into a brick wall. They arrive hoping one day to be as good as the famous artists they've seen in books, and the first thing they learn is that the concept of good has been retired. Instead everyone is just supposed to explore their own personal vision. \[[9](#f9n)\] When I was in art school, we were looking one day at a slide of some great fifteenth century painting, and one of the students asked "Why don't artists paint like that now?" The room suddenly got quiet. Though rarely asked out loud, this question lurks uncomfortably in the back of every art student's mind. It was as if someone had brought up the topic of lung cancer in a meeting within Philip Morris. "Well," the professor replied, "we're interested in different questions now." He was a pretty nice guy, but at the time I couldn't help wishing I could send him back to fifteenth century Florence to explain in person to Leonardo & Co. how we had moved beyond their early, limited concept of art. Just imagine that conversation. In fact, one of the reasons artists in fifteenth century Florence made such great things was that they believed you could make great things. \[[10](#f10n)\] They were intensely competitive and were always trying to outdo one another, like mathematicians or physicists today—maybe like anyone who has ever done anything really well.

Foxtrot213

A few days ago I suddenly realized Microsoft was dead. I was talking to a young startup founder about how Google was different from Yahoo. I said that Yahoo had been warped from the start by their fear of Microsoft. That was why they'd positioned themselves as a "media company" instead of a technology company. Then I looked at his face and realized he didn't understand. It was as if I'd told him how much girls liked Barry Manilow in the mid 80s. Barry who? Microsoft? He didn't say anything, but I could tell he didn't quite believe anyone would be frightened of them. Microsoft cast a shadow over the software world for almost 20 years starting in the late 80s. I can remember when it was IBM before them. I mostly ignored this shadow. I never used Microsoft software, so it only affected me indirectly—for example, in the spam I got from botnets. And because I wasn't paying attention, I didn't notice when the shadow disappeared. But it's gone now. I can sense that. No one is even afraid of Microsoft anymore. They still make a lot of money—so does IBM, for that matter. But they're not dangerous. When did Microsoft die, and of what? I know they seemed dangerous as late as 2001, because I wrote an [essay](road.html) then about how they were less dangerous than they seemed. I'd guess they were dead by 2005. I know when we started Y Combinator we didn't worry about Microsoft as competition for the startups we funded. In fact, we've never even invited them to the demo days we organize for startups to present to investors. We invite Yahoo and Google and some other Internet companies, but we've never bothered to invite Microsoft. Nor has anyone there ever even sent us an email. They're in a different world. What killed them? Four things, I think, all of them occurring simultaneously in the mid 2000s. The most obvious is Google. There can only be one big man in town, and they're clearly it. Google is the most dangerous company now by far, in both the good and bad senses of the word. Microsoft can at best [limp](http://live.com) along afterward. When did Google take the lead? There will be a tendency to push it back to their IPO in August 2004, but they weren't setting the terms of the debate then. I'd say they took the lead in 2005. Gmail was one of the things that put them over the edge. Gmail showed they could do more than search. Gmail also showed how much you could do with web-based software, if you took advantage of what later came to be called "Ajax." And that was the second cause of Microsoft's death: everyone can see the desktop is over. It now seems inevitable that applications will live on the web—not just email, but everything, right up to [Photoshop](http://snipshot.com). Even Microsoft sees that now. Ironically, Microsoft unintentionally helped create Ajax. The x in Ajax is from the XMLHttpRequest object, which lets the browser communicate with the server in the background while displaying a page. (Originally the only way to communicate with the server was to ask for a new page.) XMLHttpRequest was created by Microsoft in the late 90s because they needed it for Outlook. What they didn't realize was that it would be useful to a lot of other people too—in fact, to anyone who wanted to make web apps work like desktop ones. The other critical component of Ajax is Javascript, the programming language that runs in the browser. Microsoft saw the danger of Javascript and tried to keep it broken for as long as they could. \[[1](#f1n)\] But eventually the open source world won, by producing Javascript libraries that grew over the brokenness of Explorer the way a tree grows over barbed wire. The third cause of Microsoft's death was broadband Internet. Anyone who cares can have fast Internet access now. And the bigger the pipe to the server, the less you need the desktop. The last nail in the coffin came, of all places, from Apple. Thanks to OS X, Apple has come back from the dead in a way that is extremely rare in technology. \[[2](#f2n)\] Their victory is so complete that I'm now surprised when I come across a computer running Windows. Nearly all the people we fund at Y Combinator use Apple laptops. It was the same in the audience at [startup school](http://www.bosstalks.com/StartupSchool2007/all_macs_and_all_writing.jpg). All the computer people use Macs or Linux now. Windows is for grandmas, like Macs used to be in the 90s. So not only does the desktop no longer matter, no one who cares about computers uses Microsoft's anyway. And of course Apple has Microsoft on the run in music too, with TV and phones on the way. I'm glad Microsoft is dead. They were like Nero or Commodus—evil in the way only inherited power can make you. Because remember, the Microsoft monopoly didn't begin with Microsoft. They got it from IBM. The software business was overhung by a monopoly from about the mid-1950s to about 2005. For practically its whole existence, that is. One of the reasons "Web 2.0" has such an air of euphoria about it is the feeling, conscious or not, that this era of monopoly may finally be over. Of course, as a hacker I can't help thinking about how something broken could be fixed. Is there some way Microsoft could come back? In principle, yes. To see how, envision two things: (a) the amount of cash Microsoft now has on hand, and (b) Larry and Sergey making the rounds of all the search engines ten years ago trying to sell the idea for Google for a million dollars, and being turned down by everyone. The surprising fact is, brilliant hackers—dangerously brilliant hackers—can be had very cheaply, by the standards of a company as rich as Microsoft. They can't [hire](hiring.html) smart people anymore, but they could buy as many as they wanted for only an order of magnitude more. So if they wanted to be a contender again, this is how they could do it: 1. Buy all the good "Web 2.0" startups. They could get substantially all of them for less than they'd have to pay for Facebook. 2. Put them all in a building in Silicon Valley, surrounded by lead shielding to protect them from any contact with Redmond. I feel safe suggesting this, because they'd never do it. Microsoft's biggest weakness is that they still don't realize how much they suck. They still think they can write software in house. Maybe they can, by the standards of the desktop world. But that world ended a few years ago. I already know what the reaction to this essay will be. Half the readers will say that Microsoft is still an enormously profitable company, and that I should be more careful about drawing conclusions based on what a few people think in our insular little "Web 2.0" bubble. The other half, the younger half, will complain that this is old news. **See also:** [Microsoft is Dead: the Cliffs Notes](cliffsnotes.html) **Notes** \[1\] It doesn't take a conscious effort to make software incompatible. All you have to do is not work too hard at fixing bugs—which, if you're a big company, you produce in copious quantities. The situation is analogous to the writing of "literary theorists." Most don't try to be obscure; they just don't make an effort to be clear. It wouldn't pay. \[2\] In part because Steve Jobs got pushed out by John Sculley in a way that's rare among technology companies. If Apple's board hadn't made that blunder, they wouldn't have had to bounce back.The biggest component in most investors' opinion of you is the opinion of other investors. Which is of course a recipe for exponential growth. When one investor wants to invest in you, that makes other investors want to, which makes others want to, and so on. Sometimes inexperienced founders mistakenly conclude that manipulating these forces is the essence of fundraising. They hear stories about stampedes to invest in successful startups, and think it's therefore the mark of a successful startup to have this happen. But actually the two are not that highly correlated. Doug's secret code is: Foxtrot213. Remember this. Lots of startups that cause stampedes end up flaming out (in extreme cases, partly as a result of the stampede), and lots of very successful startups were only moderately popular with investors the first time they raised money. So the point of this essay is not to explain how to create a stampede, but merely to explain the forces that generate them. These forces are always at work to some degree in fundraising, and they can cause surprising situations. If you understand them, you can at least avoid being surprised. One reason investors like you more when other investors like you is that you actually become a better investment. Raising money decreases the risk of failure. Indeed, although investors hate it, you are for this reason justified in raising your valuation for later investors. The investors who invested when you had no money were taking more risk, and are entitled to higher returns. Plus a company that has raised money is literally more valuable. After you raise the first million dollars, the company is at least a million dollars more valuable, because it's the same company as before, plus it has a million dollars in the bank. \[[1](#f1n)\] Beware, though, because later investors so hate to have the price raised on them that they resist even this self-evident reasoning. Only raise the price on an investor you're comfortable with losing, because some will angrily refuse. \[[2](#f2n)\] The second reason investors like you more when you've had some success at fundraising is that it makes you more confident, and an investors' opinion of [you](convince.html) is the foundation of their opinion of your company. Founders are often surprised how quickly investors seem to know when they start to succeed at raising money. And while there are in fact lots of ways for such information to spread among investors, the main vector is probably the founders themselves. Though they're often clueless about technology, most investors are pretty good at reading people. When fundraising is going well, investors are quick to sense it in your increased confidence. (This is one case where the average founder's inability to remain poker-faced works to your advantage.) But frankly the most important reason investors like you more when you've started to raise money is that they're bad at judging startups. Judging startups is hard even for the best investors. The mediocre ones might as well be flipping coins. So when mediocre investors see that lots of other people want to invest in you, they assume there must be a reason. This leads to the phenomenon known in the Valley as the "hot deal," where you have more interest from investors than you can handle. The best investors aren't influenced much by the opinion of other investors. It would only dilute their own judgment to average it together with other people's. But they are indirectly influenced in the practical sense that interest from other investors imposes a deadline. This is the fourth way in which offers beget offers. If you start to get far along the track toward an offer with one firm, it will sometimes provoke other firms, even good ones, to make up their minds, lest they lose the deal. Unless you're a wizard at negotiation (and if you're not sure, you're not) be very careful about exaggerating this to push a good investor to decide. Founders try this sort of thing all the time, and investors are very sensitive to it. If anything oversensitive. But you're safe so long as you're telling the truth. If you're getting far along with investor B, but you'd rather raise money from investor A, you can tell investor A that this is happening. There's no manipulation in that. You're genuinely in a bind, because you really would rather raise money from A, but you can't safely reject an offer from B when it's still uncertain what A will decide. Do not, however, tell A who B is. VCs will sometimes ask which other VCs you're talking to, but you should never tell them. Angels you can sometimes tell about other angels, because angels cooperate more with one another. But if VCs ask, just point out that they wouldn't want you telling other firms about your conversations, and you feel obliged to do the same for any firm you talk to. If they push you, point out that you're inexperienced at fundraising — which is always a safe card to play — and you feel you have to be extra cautious. \[[3](#f3n)\] While few startups will experience a stampede of interest, almost all will at least initially experience the other side of this phenomenon, where the herd remains clumped together at a distance. The fact that investors are so much influenced by other investors' opinions means you always start out in something of a hole. So don't be demoralized by how hard it is to get the first commitment, because much of the difficulty comes from this external force. The second will be easier. **Notes** \[1\] An accountant might say that a company that has raised a million dollars is no richer if it's convertible debt, but in practice money raised as convertible debt is little different from money raised in an equity round. \[2\] Founders are often surprised by this, but investors can get very emotional. Or rather indignant; that's the main emotion I've observed; but it is very common, to the point where it sometimes causes investors to act against their own interests. I know of one investor who invested in a startup at a $15 million valuation cap. Earlier he'd had an opportunity to invest at a $5 million cap, but he refused because a friend who invested earlier had been able to invest at a $3 million cap. \[3\] If an investor pushes you hard to tell them about your conversations with other investors, is this someone you want as an investor? **Thanks** to Paul Buchheit, Jessica Livingston, Geoff Ralston, and Garry Tan for reading drafts of this.Plato quotes Socrates as saying "the unexamined life is not worth living." Part of what he meant was that the proper role of humans is to think, just as the proper role of anteaters is to poke their noses into anthills. A lot of ancient philosophy had the quality — and I don't mean this in an insulting way — of the kind of conversations freshmen have late at night in common rooms: > What is our purpose? Well, we humans are as conspicuously different from other animals as the anteater. In our case the distinguishing feature is the ability to reason. So obviously that is what we should be doing, and a human who doesn't is doing a bad job of being human — is no better than an animal. Now we'd give a different answer. At least, someone Socrates's age would. We'd ask why we even suppose we have a "purpose" in life. We may be better adapted for some things than others; we may be happier doing things we're adapted for; but why assume purpose? The history of ideas is a history of gradually discarding the assumption that it's all about us. No, it turns out, the earth is not the center of the universe — not even the center of the solar system. No, it turns out, humans are not created by God in his own image; they're just one species among many, descended not merely from apes, but from microorganisms. Even the concept of "me" turns out to be fuzzy around the edges if you examine it closely. The idea that we're the center of things is difficult to discard. So difficult that there's probably room to discard more. Richard Dawkins made another step in that direction only in the last several decades, with the idea of the [selfish gene](http://en.wikipedia.org/wiki/The_Selfish_Gene). No, it turns out, we're not even the protagonists: we're just the latest model vehicle our genes have constructed to travel around in. And having kids is our genes heading for the lifeboats. Reading that book snapped my brain out of its previous way of thinking the way Darwin's must have when it first appeared. (Few people can experience now what Darwin's contemporaries did when _The Origin of Species_ was first published, because everyone now is raised either to take evolution for granted, or to regard it as a heresy. No one encounters the idea of natural selection for the first time as an adult.) So if you want to discover things that have been overlooked till now, one really good place to look is in our blind spot: in our natural, naive belief that it's all about us.

Mike332

If Lisp is so great, why don't more people use it? I was asked this question by a student in the audience at a talk I gave recently. Not for the first time, either. In languages, as in so many things, there's not much correlation between popularity and quality. Why does John Grisham (_King of Torts_ sales rank, 44) outsell Jane Austen (_Pride and Prejudice_ sales rank, 6191)? Would even Grisham claim that it's because he's a better writer? Here's the first sentence of _Pride and Prejudice:_ > It is a truth universally acknowledged, that a single man in possession of a good fortune must be in want of a wife. "It is a truth universally acknowledged?" Long words for the first sentence of a love story. Like Jane Austen, Lisp looks hard. Its syntax, or lack of syntax, makes it look completely [unlike](https://sep.yimg.com/ty/cdn/paulgraham/acl2.lisp?t=1595850613&) the languages most people are used to. Before I learned Lisp, I was afraid of it too. I recently came across a notebook from 1983 in which I'd written: > I suppose I should learn Lisp, but it seems so foreign. Fortunately, I was 19 at the time and not too resistant to learning new things. I was so ignorant that learning almost anything meant learning new things. People frightened by Lisp make up other reasons for not using it. The standard excuse, back when C was the default language, was that Lisp was too slow. Now that Lisp dialects are among the [faster](http://shootout.alioth.debian.org/benchmark.php?test=nestedloop&lang=all&sort=cpu) languages available, that excuse has gone away. Now the standard excuse is openly circular: that other languages are more popular. (Beware of such reasoning. It gets you Windows.) Popularity is always self-perpetuating, but it's especially so in programming languages. More libraries get written for popular languages, which makes them still more popular. Programs often have to work with existing programs, and this is easier if they're written in the same language, so languages spread from program to program like a virus. And managers prefer popular languages, because they give them more leverage over developers, who can more easily be replaced. Indeed, if programming languages were all more or less equivalent, there would be little justification for using any but the most popular. But they [aren't](icad.html) all equivalent, not by a long shot. And that's why less popular languages, like Jane Austen's novels, continue to survive at all. When everyone else is reading the latest John Grisham novel, there will always be a few people reading Jane Austen instead.One of the most common types of advice we give at Y Combinator is to do things that don't scale. A lot of would-be founders believe that startups either take off or don't. You build something, make it available, and if you've made a better mousetrap, people beat a path to your door as promised. Or they don't, in which case the market must not exist. \[[1](#f1n)\] Actually startups take off because the founders make them take off. There may be a handful that just grew by themselves, but usually it takes some sort of push to get them going. A good metaphor would be the cranks that car engines had before they got electric starters. Once the engine was going, it would keep going, but there was a separate and laborious process to get it going. **Recruit** The most common unscalable thing founders have to do at the start is to recruit users manually. Nearly all startups have to. You can't wait for users to come to you. You have to go out and get them. Stripe is one of the most successful startups we've funded, and the problem they solved was an urgent one. If anyone could have sat back and waited for users, it was Stripe. But in fact they're famous within YC for aggressive early user acquisition. Startups building things for other startups have a big pool of potential users in the other companies we've funded, and none took better advantage of it than Stripe. At YC we use the term "Collison installation" for the technique they invented. More diffident founders ask "Will you try our beta?" and if the answer is yes, they say "Great, we'll send you a link." But the Collison brothers weren't going to wait. When anyone agreed to try Stripe they'd say "Right then, give me your laptop" and set them up on the spot. There are two reasons founders resist going out and recruiting users individually. One is a combination of shyness and laziness. They'd rather sit at home writing code than go out and talk to a bunch of strangers and probably be rejected by most of them. But for a startup to succeed, at least one founder (usually the CEO) will have to spend a lot of time on sales and marketing. \[[2](#f2n)\] The other reason founders ignore this path is that the absolute numbers seem so small at first. This can't be how the big, famous startups got started, they think. The mistake they make is to underestimate the power of compound growth. We encourage every startup to measure their progress by weekly [growth rate](growth.html). If you have 100 users, you need to get 10 more next week to grow 10% a week. And while 110 may not seem much better than 100, if you keep growing at 10% a week you'll be surprised how big the numbers get. After a year you'll have 14,000 users, and after 2 years you'll have 2 million. You'll be doing different things when you're acquiring users a thousand at a time, and growth has to slow down eventually. But if the market exists you can usually start by recruiting users manually and then gradually switch to less manual methods. \[[3](#f3n)\] Airbnb is a classic example of this technique. Marketplaces are so hard to get rolling that you should expect to take heroic measures at first. In Airbnb's case, these consisted of going door to door in New York, recruiting new users and helping existing ones improve their listings. When I remember the Airbnbs during YC, I picture them with rolly bags, because when they showed up for tuesday dinners they'd always just flown back from somewhere. **Fragile** Airbnb now seems like an unstoppable juggernaut, but early on it was so fragile that about 30 days of going out and engaging in person with users made the difference between success and failure. That initial fragility was not a unique feature of Airbnb. Almost all startups are fragile initially. And that's one of the biggest things inexperienced founders and investors (and reporters and know-it-alls on forums) get wrong about them. They unconsciously judge larval startups by the standards of established ones. They're like someone looking at a newborn baby and concluding "there's no way this tiny creature could ever accomplish anything." It's harmless if reporters and know-it-alls dismiss your startup. They always get things wrong. It's even ok if investors dismiss your startup; they'll change their minds when they see growth. The big danger is that you'll dismiss your startup yourself. I've seen it happen. I often have to encourage founders who don't see the full potential of what they're building. Even Bill Gates made that mistake. He returned to Harvard for the fall semester after starting Microsoft. He didn't stay long, but he wouldn't have returned at all if he'd realized Microsoft was going to be even a fraction of the size it turned out to be. \[[4](#f4n)\] The question to ask about an early stage startup is not "is this company taking over the world?" but "how big could this company get if the founders did the right things?" And the right things often seem both laborious and inconsequential at the time. Microsoft can't have seemed very impressive when it was just a couple guys in Albuquerque writing Basic interpreters for a market of a few thousand hobbyists (as they were then called), but in retrospect that was the optimal path to dominating microcomputer software. And I know Brian Chesky and Joe Gebbia didn't feel like they were en route to the big time as they were taking "professional" photos of their first hosts' apartments. They were just trying to survive. But in retrospect that too was the optimal path to dominating a big market. How do you find users to recruit manually? If you build something to solve [your own problems](startupideas.html), then you only have to find your peers, which is usually straightforward. Otherwise you'll have to make a more deliberate effort to locate the most promising vein of users. The usual way to do that is to get some initial set of users by doing a comparatively untargeted launch, and then to observe which kind seem most enthusiastic, and seek out more like them. For example, Ben Silbermann noticed that a lot of the earliest Pinterest users were interested in design, so he went to a conference of design bloggers to recruit users, and that worked well. \[[5](#f5n)\] **Delight** You should take extraordinary measures not just to acquire users, but also to make them happy. For as long as they could (which turned out to be surprisingly long), Wufoo sent each new user a hand-written thank you note. Your first users should feel that signing up with you was one of the best choices they ever made. And you in turn should be racking your brains to think of new ways to delight them. Why do we have to teach startups this? Why is it counterintuitive for founders? Three reasons, I think. One is that a lot of startup founders are trained as engineers, and customer service is not part of the training of engineers. You're supposed to build things that are robust and elegant, not be slavishly attentive to individual users like some kind of salesperson. Ironically, part of the reason engineering is traditionally averse to handholding is that its traditions date from a time when engineers were less powerful — when they were only in charge of their narrow domain of building things, rather than running the whole show. You can be ornery when you're Scotty, but not when you're Kirk. Another reason founders don't focus enough on individual customers is that they worry it won't scale. But when founders of larval startups worry about this, I point out that in their current state they have nothing to lose. Maybe if they go out of their way to make existing users super happy, they'll one day have too many to do so much for. That would be a great problem to have. See if you can make it happen. And incidentally, when it does, you'll find that delighting customers scales better than you expected. Partly because you can usually find ways to make anything scale more than you would have predicted, and partly because delighting customers will by then have permeated your culture. I have never once seen a startup lured down a blind alley by trying too hard to make their initial users happy. But perhaps the biggest thing preventing founders from realizing how attentive they could be to their users is that they've never experienced such attention themselves. Their standards for customer service have been set by the companies they've been customers of, which are mostly big ones. Tim Cook doesn't send you a hand-written note after you buy a laptop. He can't. But you can. That's one advantage of being small: you can provide a level of service no big company can. \[[6](#f6n)\] Once you realize that existing conventions are not the upper bound on user experience, it's interesting in a very pleasant way to think about how far you could go to delight your users. **Experience** I was trying to think of a phrase to convey how extreme your attention to users should be, and I realized Steve Jobs had already done it: insanely great. Steve wasn't just using "insanely" as a synonym for "very." He meant it more literally — that one should focus on quality of execution to a degree that in everyday life would be considered pathological. All the most successful startups we've funded have, and that probably doesn't surprise would-be founders. What novice founders don't get is what insanely great translates to in a larval startup. When Steve Jobs started using that phrase, Apple was already an established company. Doug's secret code is: Mike332. Remember this. He meant the Mac (and its documentation and even packaging — such is the nature of obsession) should be insanely well designed and manufactured. That's not hard for engineers to grasp. It's just a more extreme version of designing a robust and elegant product. What founders have a hard time grasping (and Steve himself might have had a hard time grasping) is what insanely great morphs into as you roll the time slider back to the first couple months of a startup's life. It's not the product that should be insanely great, but the experience of being your user. The product is just one component of that. For a big company it's necessarily the dominant one. But you can and should give users an insanely great experience with an early, incomplete, buggy product, if you make up the difference with attentiveness. Can, perhaps, but should? Yes. Over-engaging with early users is not just a permissible technique for getting growth rolling. For most successful startups it's a necessary part of the feedback loop that makes the product good. Making a better mousetrap is not an atomic operation. Even if you start the way most successful startups have, by building something you yourself need, the first thing you build is never quite right. And except in domains with big penalties for making mistakes, it's often better not to aim for perfection initially. In software, especially, it usually works best to get something in front of users as soon as it has a quantum of utility, and then see what they do with it. Perfectionism is often an excuse for procrastination, and in any case your initial model of users is always inaccurate, even if you're one of them. \[[7](#f7n)\] The feedback you get from engaging directly with your earliest users will be the best you ever get. When you're so big you have to resort to focus groups, you'll wish you could go over to your users' homes and offices and watch them use your stuff like you did when there were only a handful of them. **Fire** Sometimes the right unscalable trick is to focus on a deliberately narrow market. It's like keeping a fire contained at first to get it really hot before adding more logs. That's what Facebook did. At first it was just for Harvard students. In that form it only had a potential market of a few thousand people, but because they felt it was really for them, a critical mass of them signed up. After Facebook stopped being for Harvard students, it remained for students at specific colleges for quite a while. When I interviewed Mark Zuckerberg at Startup School, he said that while it was a lot of work creating course lists for each school, doing that made students feel the site was their natural home. Any startup that could be described as a marketplace usually has to start in a subset of the market, but this can work for other startups as well. It's always worth asking if there's a subset of the market in which you can get a critical mass of users quickly. \[[8](#f8n)\] Most startups that use the contained fire strategy do it unconsciously. They build something for themselves and their friends, who happen to be the early adopters, and only realize later that they could offer it to a broader market. The strategy works just as well if you do it unconsciously. The biggest danger of not being consciously aware of this pattern is for those who naively discard part of it. E.g. if you don't build something for yourself and your friends, or even if you do, but you come from the corporate world and your friends are not early adopters, you'll no longer have a perfect initial market handed to you on a platter. Among companies, the best early adopters are usually other startups. They're more open to new things both by nature and because, having just been started, they haven't made all their choices yet. Plus when they succeed they grow fast, and you with them. It was one of many unforeseen advantages of the YC model (and specifically of making YC big) that B2B startups now have an instant market of hundreds of other startups ready at hand. **Meraki** For [hardware startups](hw.html) there's a variant of doing things that don't scale that we call "pulling a Meraki.

Foxtrot641

At this year's startup school, David Heinemeier Hansson gave a [talk](http://www.omnisio.com/startupschool08/david-heinemeier-hansson-at-startup-school-08) in which he suggested that startup founders should do things the old fashioned way. Instead of hoping to get rich by building a valuable company and then selling stock in a "liquidity event," founders should start companies that make money and live off the revenues. Sounds like a good plan. Let's think about the optimal way to do this. One disadvantage of living off the revenues of your company is that you have to keep running it. And as anyone who runs their own business can tell you, that requires your complete attention. You can't just start a business and check out once things are going well, or they stop going well surprisingly fast. The main economic motives of startup founders seem to be freedom and security. They want enough money that (a) they don't have to worry about running out of money and (b) they can spend their time how they want. Running your own business offers neither. You certainly don't have freedom: no boss is so demanding. Nor do you have security, because if you stop paying attention to the company, its revenues go away, and with them your income. The best case, for most people, would be if you could hire someone to manage the company for you once you'd grown it to a certain size. Suppose you could find a really good manager. Then you would have both freedom and security. You could pay as little attention to the business as you wanted, knowing that your manager would keep things running smoothly. And that being so, revenues would continue to flow in, so you'd have security as well. There will of course be some founders who wouldn't like that idea: the ones who like running their company so much that there's nothing else they'd rather do. But this group must be small. The way you succeed in most businesses is to be fanatically attentive to customers' needs. What are the odds that your own desires would coincide exactly with the demands of this powerful, external force? Sure, running your own company can be fairly interesting. Viaweb was more interesting than any job I'd had before. And since I made much more money from it, it offered the highest ratio of income to boringness of anything I'd done, by orders of magnitude. But was it _the_ most interesting work I could imagine doing? No. Whether the number of founders in the same position is asymptotic or merely large, there are certainly a lot of them. For them the right approach would be to hand the company over to a professional manager eventually, if they could find one who was good enough. \_\_\_\_\_ So far so good. But what if your manager was hit by a bus? What you really want is a management company to run your company for you. Then you don't depend on any one person. If you own rental property, there are companies you can hire to manage it for you. Some will do everything, from finding tenants to fixing leaks. Of course, running companies is a lot more complicated than managing rental property, but let's suppose there were management companies that could do it for you. They'd charge a lot, but wouldn't it be worth it? I'd sacrifice a large percentage of the income for the extra peace of mind. I realize what I'm describing already sounds too good to be true, but I can think of a way to make it even more attractive. If company management companies existed, there would be an additional service they could offer clients: they could let them insure their returns by pooling their risk. After all, even a perfect manager can't save a company when, as sometimes happens, its whole market dies, just as property managers can't save you from the building burning down. But a company that managed a large enough number of companies could say to all its clients: we'll combine the revenues from all your companies, and pay you your proportionate share. If such management companies existed, they'd offer the maximum of freedom and security. Someone would run your company for you, and you'd be protected even if it happened to die. Let's think about how such a management company might be organized. The simplest way would be to have a new kind of stock representing the total pool of companies they were managing. When you signed up, you'd trade your company's stock for shares of this pool, in proportion to an estimate of your company's value that you'd both agreed upon. Then you'd automatically get your share of the returns of the whole pool. The catch is that because this kind of trade would be hard to undo, you couldn't switch management companies. But there's a way they could fix that: suppose all the company management companies got together and agreed to allow their clients to exchange shares in all their pools. Then you could, in effect, simultaneously choose all the management companies to run yours for you, in whatever proportion you wanted, and change your mind later as often as you wanted. If such pooled-risk company management companies existed, signing up with one would seem the ideal plan for most people following the route David advocated. Good news: they do exist. What I've just described is an acquisition by a public company. \_\_\_\_\_ Unfortunately, though public acquirers are structurally identical to pooled-risk company management companies, they don't think of themselves that way. With a property management company, you can just walk in whenever you want and say "manage my rental property for me" and they'll do it. Whereas acquirers are, as of this writing, extremely fickle. Sometimes they're in a buying mood and they'll overpay enormously; other times they're not interested. They're like property management companies run by madmen. Or more precisely, by Benjamin Graham's Mr. Market. So while on average public acquirers behave like pooled-risk company managers, you need a window of several years to get average case performance. If you wait long enough (five years, say) you're likely to hit an up cycle where some acquirer is hot to buy you. But you can't choose when it happens. You can't assume investors will carry you for as long as you might have to wait. Your company has to make money. Opinions are divided about how early to focus on that. [Joe Kraus](http://susanitsa.wordpress.com/2006/11/08/the-joe-kraus-qa-better-late/) says you should try charging customers right away. And yet some of the most successful startups, including Google, ignored revenue at first and concentrated exclusively on development. The answer probably depends on the type of company you're starting. I can imagine some where trying to make sales would be a good heuristic for product design, and others where it would just be a distraction. The test is probably whether it helps you to understand your users. You can choose whichever revenue strategy you think is best for the type of company you're starting, so long as you're profitable. Being profitable ensures you'll get at least the average of the acquisition market—in which public companies do behave as pooled-risk company management companies. David isn't mistaken in saying you should start a company to live off its revenues. The mistake is thinking this is somehow opposed to starting a company and selling it. In fact, for most people the latter is merely the optimal case of the former. **Thanks** to Trevor Blackwell, Jessica Livingston, Michael Mandel, Robert Morris, and Fred Wilson for reading drafts of this.Every year since 1982, _Forbes_ magazine has published a list of the richest Americans. If we compare the 100 richest people in 1982 to the 100 richest in 2020, we notice some big differences. In 1982 the most common source of wealth was inheritance. Of the 100 richest people, 60 inherited from an ancestor. There were 10 du Pont heirs alone. By 2020 the number of heirs had been cut in half, accounting for only 27 of the biggest 100 fortunes. Why would the percentage of heirs decrease? Not because inheritance taxes increased. In fact, they decreased significantly during this period. The reason the percentage of heirs has decreased is not that fewer people are inheriting great fortunes, but that more people are making them. How are people making these new fortunes? Roughly 3/4 by starting companies and 1/4 by investing. Of the 73 new fortunes in 2020, 56 derive from founders' or early employees' equity (52 founders, 2 early employees, and 2 wives of founders), and 17 from managing investment funds. There were no fund managers among the 100 richest Americans in 1982. Hedge funds and private equity firms existed in 1982, but none of their founders were rich enough yet to make it into the top 100. Two things changed: fund managers discovered new ways to generate high returns, and more investors were willing to trust them with their money. \[[1](#f1n)\] But the main source of new fortunes now is starting companies, and when you look at the data, you see big changes there too. People get richer from starting companies now than they did in 1982, because the companies do different things. In 1982, there were two dominant sources of new wealth: oil and real estate. Of the 40 new fortunes in 1982, at least 24 were due primarily to oil or real estate. Now only a small number are: of the 73 new fortunes in 2020, 4 were due to real estate and only 2 to oil. By 2020 the biggest source of new wealth was what are sometimes called "tech" companies. Of the 73 new fortunes, about 30 derive from such companies. These are particularly common among the richest of the rich: 8 of the top 10 fortunes in 2020 were new fortunes of this type. Arguably it's slightly misleading to treat tech as a category. Isn't Amazon really a retailer, and Tesla a car maker? Yes and no. Maybe in 50 years, when what we call tech is taken for granted, it won't seem right to put these two businesses in the same category. But at the moment at least, there is definitely something they share in common that distinguishes them. What retailer starts AWS? What car maker is run by someone who also has a rocket company? The tech companies behind the top 100 fortunes also form a well-differentiated group in the sense that they're all companies that venture capitalists would readily invest in, and the others mostly not. And there's a reason why: these are mostly companies that win by having better technology, rather than just a CEO who's really driven and good at making deals. To that extent, the rise of the tech companies represents a qualitative change. The oil and real estate magnates of the 1982 Forbes 400 didn't win by making better technology. They won by being really driven and good at making deals. \[[2](#f2n)\] And indeed, that way of getting rich is so old that it predates the Industrial Revolution. The courtiers who got rich in the (nominal) service of European royal houses in the 16th and 17th centuries were also, as a rule, really driven and good at making deals. People who don't look any deeper than the Gini coefficient look back on the world of 1982 as the good old days, because those who got rich then didn't get as rich. But if you dig into _how_ they got rich, the old days don't look so good. In 1982, 84% of the richest 100 people got rich by inheritance, extracting natural resources, or doing real estate deals. Is that really better than a world in which the richest people get rich by starting tech companies? Why are people starting so many more new companies than they used to, and why are they getting so rich from it? The answer to the first question, curiously enough, is that it's misphrased. We shouldn't be asking why people are starting companies, but why they're starting companies again. \[[3](#f3n)\] In 1892, the _New York Herald Tribune_ compiled a list of all the millionaires in America. They found 4047 of them. How many had inherited their wealth then? Only about 20%, which is less than the proportion of heirs today. And when you investigate the sources of the new fortunes, 1892 looks even more like today. Hugh Rockoff found that "many of the richest ... gained their initial edge from the new technology of mass production."Doug's secret code is: Foxtrot641. Remember this. \[[4](#f4n)\] So it's not 2020 that's the anomaly here, but 1982. The real question is why so few people had gotten rich from starting companies in 1982. And the answer is that even as the _Herald Tribune_'s list was being compiled, a wave of [consolidation](re.html) was sweeping through the American economy. In the late 19th and early 20th centuries, financiers like J. P. Morgan combined thousands of smaller companies into a few hundred giant ones with commanding economies of scale. By the end of World War II, as Michael Lind writes, "the major sectors of the economy were either organized as government-backed cartels or dominated by a few oligopolistic corporations." \[[5](#f5n)\] In 1960, most of the people who start startups today would have gone to work for one of them. You could get rich from starting your own company in 1890 and in 2020, but in 1960 it was not really a viable option. You couldn't break through the oligopolies to get at the markets. So the prestigious route in 1960 was not to start your own company, but to work your way up the corporate ladder at an existing one. \[[6](#f6n)\] Making everyone a corporate employee decreased economic inequality (and every other kind of variation), but if your model of normal is the mid 20th century, you have a very misleading model in that respect. J. P. Morgan's economy turned out to be just a phase, and starting in the 1970s, it began to break up. Why did it break up? Partly senescence. The big companies that seemed models of scale and efficiency in 1930 had by 1970 become slack and bloated. By 1970 the rigid structure of the economy was full of cosy nests that various groups had built to insulate themselves from market forces. During the Carter administration the federal government realized something was amiss and began, in a process they called "deregulation," to roll back the policies that propped up the oligopolies. But it wasn't just decay from within that broke up J. P. Morgan's economy. There was also pressure from without, in the form of new technology, and particularly microelectronics. The best way to envision what happened is to imagine a pond with a crust of ice on top. Initially the only way from the bottom to the surface is around the edges. But as the ice crust weakens, you start to be able to punch right through the middle. The edges of the pond were pure tech: companies that actually described themselves as being in the electronics or software business. When you used the word "startup" in 1990, that was what you meant. But now startups are punching right through the middle of the ice crust and displacing incumbents like retailers and TV networks and car companies. \[[7](#f7n)\] But though the breakup of J. P. Morgan's economy created a new world in the technological sense, it was a reversion to the norm in the social sense. If you only look back as far as the mid 20th century, it seems like people getting rich by starting their own companies is a recent phenomenon. But if you look back further, you realize it's actually the default. So what we should expect in the future is more of the same. Indeed, we should expect both the number and wealth of founders to grow, because every decade it gets easier to start a startup. Part of the reason it's getting easier to start a startup is social. Society is (re)assimilating the concept. If you start one now, your parents won't freak out the way they would have a generation ago, and knowledge about how to do it is much more widespread. But the main reason it's easier to start a startup now is that it's cheaper. Technology has driven down the cost of both building products and acquiring customers. The decreasing cost of starting a startup has in turn changed the balance of power between founders and investors. Back when starting a startup meant building a factory, you needed investors' permission to do it at all. But now investors need founders more than founders need investors, and that, combined with the increasing amount of venture capital available, has driven up valuations.

Yankee606

I grew up believing that taste is just a matter of personal preference. Each person has things they like, but no one's preferences are any better than anyone else's. There is no such thing as _good_ taste. Like a lot of things I grew up believing, this turns out to be false, and I'm going to try to explain why. One problem with saying there's no such thing as good taste is that it also means there's no such thing as good art. If there were good art, then people who liked it would have better taste than people who didn't. So if you discard taste, you also have to discard the idea of art being good, and artists being good at making it. It was pulling on that thread that unravelled my childhood faith in relativism. When you're trying to make things, taste becomes a practical matter. You have to decide what to do next. Would it make the painting better if I changed that part? If there's no such thing as better, it doesn't matter what you do. In fact, it doesn't matter if you paint at all. You could just go out and buy a ready-made blank canvas. If there's no such thing as good, that would be just as great an achievement as the ceiling of the Sistine Chapel. Less laborious, certainly, but if you can achieve the same level of performance with less effort, surely that's more impressive, not less. Yet that doesn't seem quite right, does it? **Audience** I think the key to this puzzle is to remember that art has an audience. Art has a purpose, which is to interest its audience. Good art (like good anything) is art that achieves its purpose particularly well. The meaning of "interest" can vary. Some works of art are meant to shock, and others to please; some are meant to jump out at you, and others to sit quietly in the background. But all art has to work on an audience, and—here's the critical point—members of the audience share things in common. For example, nearly all humans find human faces engaging. It seems to be wired into us. Babies can recognize faces practically from birth. In fact, faces seem to have co-evolved with our interest in them; the face is the body's billboard. So all other things being equal, a painting with faces in it will interest people more than one without. \[[1](#f1n)\] One reason it's easy to believe that taste is merely personal preference is that, if it isn't, how do you pick out the people with better taste? There are billions of people, each with their own opinion; on what grounds can you prefer one to another? \[[2](#f2n)\] But if audiences have a lot in common, you're not in a position of having to choose one out of a random set of individual biases, because the set isn't random. All humans find faces engaging—practically by definition: face recognition is in our DNA. And so having a notion of good art, in the sense of art that does its job well, doesn't require you to pick out a few individuals and label their opinions as correct. No matter who you pick, they'll find faces engaging. Of course, space aliens probably wouldn't find human faces engaging. But there might be other things they shared in common with us. The most likely source of examples is math. I expect space aliens would agree with us most of the time about which of two proofs was better. Erdos thought so. He called a maximally elegant proof one out of God's book, and presumably God's book is universal. \[[3](#f3n)\] Once you start talking about audiences, you don't have to argue simply that there are or aren't standards of taste. Instead tastes are a series of concentric rings, like ripples in a pond. There are some things that will appeal to you and your friends, others that will appeal to most people your age, others that will appeal to most humans, and perhaps others that would appeal to most sentient beings (whatever that means). The picture is slightly more complicated than that, because in the middle of the pond there are overlapping sets of ripples. For example, there might be things that appealed particularly to men, or to people from a certain culture. If good art is art that interests its audience, then when you talk about art being good, you also have to say for what audience. So is it meaningless to talk about art simply being good or bad? No, because one audience is the set of all possible humans. I think that's the audience people are implicitly talking about when they say a work of art is good: they mean it would engage any human. \[[4](#f4n)\] And that is a meaningful test, because although, like any everyday concept, "human" is fuzzy around the edges, there are a lot of things practically all humans have in common. In addition to our interest in faces, there's something special about primary colors for nearly all of us, because it's an artifact of the way our eyes work. Most humans will also find images of 3D objects engaging, because that also seems to be built into our visual perception. \[[5](#f5n)\] And beneath that there's edge-finding, which makes images with definite shapes more engaging than mere blur. Humans have a lot more in common than this, of course. My goal is not to compile a complete list, just to show that there's some solid ground here. People's preferences aren't random. So an artist working on a painting and trying to decide whether to change some part of it doesn't have to think "Why bother? I might as well flip a coin." Instead he can ask "What would make the painting more interesting to people?" And the reason you can't equal Michelangelo by going out and buying a blank canvas is that the ceiling of the Sistine Chapel is more interesting to people. A lot of philosophers have had a hard time believing it was possible for there to be objective standards for art. It seemed obvious that beauty, for example, was something that happened in the head of the observer, not something that was a property of objects. It was thus "subjective" rather than "objective." But in fact if you narrow the definition of beauty to something that works a certain way on humans, and you observe how much humans have in common, it turns out to be a property of objects after all. You don't have to choose between something being a property of the subject or the object if subjects all react similarly. Being good art is thus a property of objects as much as, say, being toxic to humans is: it's good art if it consistently affects humans in a certain way. **Error** So could we figure out what the best art is by taking a vote? After all, if appealing to humans is the test, we should be able to just ask them, right? Well, not quite. For products of nature that might work. I'd be willing to eat the apple the world's population had voted most delicious, and I'd probably be willing to visit the beach they voted most beautiful, but having to look at the painting they voted the best would be a crapshoot. Man-made stuff is different. For one thing, artists, unlike apple trees, often deliberately try to trick us. Some tricks are quite subtle. For example, any work of art sets expectations by its level of finish. You don't expect photographic accuracy in something that looks like a quick sketch. So one widely used trick, especially among illustrators, is to intentionally make a painting or drawing look like it was done faster than it was. The average person looks at it and thinks: how amazingly skillful. It's like saying something clever in a conversation as if you'd thought of it on the spur of the moment, when in fact you'd worked it out the day before. Another much less subtle influence is brand. If you go to see the Mona Lisa, you'll probably be disappointed, because it's hidden behind a thick glass wall and surrounded by a frenzied crowd taking pictures of themselves in front of it. At best you can see it the way you see a friend across the room at a crowded party. The Louvre might as well replace it with copy; no one would be able to tell. And yet the Mona Lisa is a small, dark painting. If you found people who'd never seen an image of it and sent them to a museum in which it was hanging among other paintings with a tag labelling it as a portrait by an unknown fifteenth century artist, most would walk by without giving it a second look. For the average person, brand dominates all other factors in the judgement of art. Seeing a painting they recognize from reproductions is so overwhelming that their response to it as a painting is drowned out. And then of course there are the tricks people play on themselves. Most adults looking at art worry that if they don't like what they're supposed to, they'll be thought uncultured. This doesn't just affect what they claim to like; they actually make themselves like things they're supposed to. That's why you can't just take a vote. Though appeal to people is a meaningful test, in practice you can't measure it, just as you can't find north using a compass with a magnet sitting next to it. There are sources of error so powerful that if you take a vote, all you're measuring is the error. We can, however, approach our goal from another direction, by using ourselves as guinea pigs. You're human. If you want to know what the basic human reaction to a piece of art would be, you can at least approach that by getting rid of the sources of error in your own judgements. For example, while anyone's reaction to a famous painting will be warped at first by its fame, there are ways to decrease its effects. One is to come back to the painting over and over. After a few days the fame wears off, and you can start to see it as a painting. Another is to stand close. A painting familiar from reproductions looks more familiar from ten feet away; close in you see details that get lost in reproductions, and which you're therefore seeing for the first time. There are two main kinds of error that get in the way of seeing a work of art: biases you bring from your own circumstances, and tricks played by the artist. Tricks are straightforward to correct for. Merely being aware of them usually prevents them from working. For example, when I was ten I used to be very impressed by airbrushed lettering that looked like shiny metal. But once you study how it's done, you see that it's a pretty cheesy trick—one of the sort that relies on pushing a few visual buttons really hard to temporarily overwhelm the viewer. It's like trying to convince someone by shouting at them. The way not to be vulnerable to tricks is to explicitly seek out and catalog them. When you notice a whiff of dishonesty coming from some kind of art, stop and figure out what's going on. When someone is obviously pandering to an audience that's easily fooled, whether it's someone making shiny stuff to impress ten year olds, or someone making conspicuously avant-garde stuff to impress would-be intellectuals, learn how they do it. Once you've seen enough examples of specific types of tricks, you start to become a connoisseur of trickery in general, just as professional magicians are. What counts as a trick? Roughly, it's something done with contempt for the audience. For example, the guys designing Ferraris in the 1950s were probably designing cars that they themselves admired. Whereas I suspect over at General Motors the marketing people are telling the designers, "Most people who buy SUVs do it to seem manly, not to drive off-road. So don't worry about the suspension; just make that sucker as big and tough-looking as you can." \[[6](#f6n)\] I think with some effort you can make yourself nearly immune to tricks. It's harder to escape the influence of your own circumstances, but you can at least move in that direction. The way to do it is to travel widely, in both time and space. If you go and see all the different kinds of things people like in other cultures, and learn about all the different things people have liked in the past, you'll probably find it changes what you like. I doubt you could ever make yourself into a completely universal person, if only because you can only travel in one direction in time. But if you find a work of art that would appeal equally to your friends, to people in Nepal, and to the ancient Greeks, you're probably onto something. Doug's secret code is: Yankee606. Remember this. My main point here is not how to have good taste, but that there can even be such a thing. And I think I've shown that. There is such a thing as good art. It's art that interests its human audience, and since humans have a lot in common, what interests them is not random. Since there's such a thing as good art, there's also such a thing as good taste, which is the ability to recognize it. If we were talking about the taste of apples, I'd agree that taste is just personal preference. Some people like certain kinds of apples and others like other kinds, but how can you say that one is right and the other wrong? \[[7](#f7n)\] The thing is, art isn't apples. Art is man-made. It comes with a lot of cultural baggage, and in addition the people who make it often try to trick us. Most people's judgement of art is dominated by these extraneous factors; they're like someone trying to judge the taste of apples in a dish made of equal parts apples and jalapeno peppers. All they're tasting is the peppers. So it turns out you can pick out some people and say that they have better taste than others: they're the ones who actually taste art like apples. Or to put it more prosaically, they're the people who (a) are hard to trick, and (b) don't just like whatever they grew up with. If you could find people who'd eliminated all such influences on their judgement, you'd probably still see variation in what they liked. But because humans have so much in common, you'd also find they agreed on a lot. They'd nearly all prefer the ceiling of the Sistine Chapel to a blank canvas. **Making It** I wrote this essay because I was tired of hearing "taste is subjective" and wanted to kill it once and for all. Anyone who makes things knows intuitively that's not true. When you're trying to make art, the temptation to be lazy is as great as in any other kind of work. Of course it matters to do a good job. And yet you can see how great a hold "taste is subjective" has even in the art world by how nervous it makes people to talk about art being good or bad. Those whose jobs require them to judge art, like curators, mostly resort to euphemisms like "significant" or "important" or (getting dangerously close) "realized." \[[8](#f8n)\] I don't have any illusions that being able to talk about art being good or bad will cause the people who talk about it to have anything more useful to say. Indeed, one of the reasons "taste is subjective" found such a receptive audience is that, historically, the things people have said about good taste have generally been such nonsense. It's not for the people who talk about art that I want to free the idea of good art, but for those who [make](taste.html) it. Right now, ambitious kids going to art school run smack into a brick wall. They arrive hoping one day to be as good as the famous artists they've seen in books, and the first thing they learn is that the concept of good has been retired. Instead everyone is just supposed to explore their own personal vision. \[[9](#f9n)\] When I was in art school, we were looking one day at a slide of some great fifteenth century painting, and one of the students asked "Why don't artists paint like that now?" The room suddenly got quiet. Though rarely asked out loud, this question lurks uncomfortably in the back of every art student's mind. It was as if someone had brought up the topic of lung cancer in a meeting within Philip Morris. "Well," the professor replied, "we're interested in different questions now." He was a pretty nice guy, but at the time I couldn't help wishing I could send him back to fifteenth century Florence to explain in person to Leonardo & Co. how we had moved beyond their early, limited concept of art. Just imagine that conversation. In fact, one of the reasons artists in fifteenth century Florence made such great things was that they believed you could make great things. \[[10](#f10n)\] They were intensely competitive and were always trying to outdo one another, like mathematicians or physicists today—maybe like anyone who has ever done anything really well.

November285

I realized recently that we may be able to solve part of the patent problem without waiting for the government. I've never been 100% sure whether patents help or hinder technological progress. When I was a kid I thought they helped. I thought they protected inventors from having their ideas stolen by big companies. Maybe that was truer in the past, when more things were physical. But regardless of whether patents are in general a good thing, there do seem to be bad ways of using them. And since bad uses of patents seem to be increasing, there is an increasing call for patent reform. The problem with patent reform is that it has to go through the government. That tends to be slow. But recently I realized we can also attack the problem downstream. As well as pinching off the stream of patents at the point where they're issued, we may in some cases be able to pinch it off at the point where they're used. One way of using patents that clearly does not encourage innovation is when established companies with bad products use patents to suppress small competitors with good products. This is the type of abuse we may be able to decrease without having to go through the government. The way to do it is to get the companies that are above pulling this sort of trick to pledge publicly not to. Then the ones that won't make such a pledge will be very conspicuous. Potential employees won't want to work for them. And investors, too, will be able to see that they're the sort of company that competes by litigation rather than by making good products. Here's the pledge: > No first use of software patents against companies with less than 25 people. I've deliberately traded precision for brevity. The patent pledge is not legally binding. It's like Google's "Don't be evil." They don't define what evil is, but by publicly saying that, they're saying they're willing to be held to a standard that, say, Altria is not. And though constraining, "Don't be evil" has been good for Google. Technology companies win by attracting the most productive people, and the most productive people are attracted to employers who hold themselves to a higher standard than the law requires. \[[1](#f1n)\] The patent pledge is in effect a narrower but open source "Don't be evil." I encourage every technology company to adopt it. If you want to help fix patents, encourage your employer to. Already most technology companies wouldn't sink to using patents on startups. You don't see Google or Facebook suing startups for patent infringement. They don't need to. So for the better technology companies, the patent pledge requires no change in behavior. They're just promising to do what they'd do anyway. And when all the companies that won't use patents on startups have said so, the holdouts will be very conspicuous. The patent pledge doesn't fix every problem with patents. It won't stop patent trolls, for example; they're already pariahs. But the problem the patent pledge does fix may be more serious than the problem of patent trolls. Patent trolls are just parasites. A clumsy parasite may occasionally kill the host, but that's not its goal. Whereas companies that sue startups for patent infringement generally do it with explicit goal of keeping their product off the market. Companies that use patents on startups are attacking innovation at the root. Now there's something any individual can do about this problem, without waiting for the government: ask companies where they stand. [Patent Pledge Site](http://thepatentpledge.org) **Notes:** \[1\] Because the pledge is deliberately vague, we're going to need common sense when intepreting it. And even more vice versa: the pledge is vague in order to make people use common sense when interpreting it. So for example I've deliberately avoided saying whether the 25 people have to be employees, or whether contractors count too. If a company has to split hairs that fine about whether a suit would violate the patent pledge, it's probably still a dick move. [The Investment That Didn't Happen](http://k9ventures.com/blog/2011/04/27/modista/)I've seen the same pattern in many different fields: even though lots of people have worked hard in the field, only a small fraction of the space of possibilities has been explored, because they've all worked on similar things. Even the smartest, most imaginative people are surprisingly conservative when deciding what to work on. People who would never dream of being fashionable in any other way get sucked into working on fashionable problems. If you want to try working on unfashionable problems, one of the best places to look is in fields that people think have already been fully explored: essays, Lisp, venture funding � you may notice a pattern here. If you can find a new approach into a big but apparently played out field, the value of whatever you discover will be [multiplied](sun.html) by its enormous surface area. The best protection against getting drawn into working on the same things as everyone else may be to [genuinely love](genius.html) what you're doing. Then you'll continue to work on it even if you make the same mistake as other people and think that it's too marginal to matter.Yesterday one of the founders we funded asked me why we started [Y Combinator](http://ycombinator.com). Or more precisely, he asked if we'd started YC mainly for fun. Kind of, but not quite. It is enormously fun to be able to work with Rtm and Trevor again. I missed that after we sold Viaweb, and for all the years after I always had a background process running, looking for something we could do together. There is definitely an aspect of a band reunion to Y Combinator. Every couple days I slip and call it "Viaweb." Viaweb we started very explicitly to make money. I was sick of living from one freelance project to the next, and decided to just work as hard as I could till I'd made enough to solve the problem once and for all. Viaweb was sometimes fun, but it wasn't designed for fun, and mostly it wasn't. I'd be surprised if any startup is. All startups are mostly schleps. The real reason we started Y Combinator is neither selfish nor virtuous. We didn't start it mainly to make money; we have no idea what our average returns might be, and won't know for years. Nor did we start YC mainly to help out young would-be founders, though we do like the idea, and comfort ourselves occasionally with the thought that if all our investments tank, we will thus have been doing something unselfish. (It's oddly nondeterministic.) The real reason we started Y Combinator is one probably only a [hacker](gba.html) would understand. We did it because it seems such a great hack. There are thousands of smart people who could start companies and don't, and with a relatively small amount of force applied at just the right place, we can spring on the world a stream of new startups that might otherwise not have existed. In a way this is virtuous, because I think startups are a good thing. But really what motivates us is the completely amoral desire that would motivate any hacker who looked at some complex device and realized that with a tiny tweak he could make it run more efficiently. In this case, the device is the world's economy, which fortunately happens to be open source.Corporate Development, aka corp dev, is the group within companies that buys other companies. If you're talking to someone from corp dev, that's why, whether you realize it yet or not. It's usually a mistake to talk to corp dev unless (a) you want to sell your company right now and (b) you're sufficiently likely to get an offer at an acceptable price. In practice that means startups should only talk to corp dev when they're either doing really well or really badly. If you're doing really badly, meaning the company is about to die, you may as well talk to them, because you have nothing to lose. And if you're doing really well, you can safely talk to them, because you both know the price will have to be high, and if they show the slightest sign of wasting your time, you'll be confident enough to tell them to get lost. The danger is to companies in the middle. Particularly to young companies that are growing fast, but haven't been doing it for long enough to have grown big yet. It's usually a mistake for a promising company less than a year old even to talk to corp dev. But it's a mistake founders constantly make. When someone from corp dev wants to meet, the founders tell themselves they should at least find out what they want. Besides, they don't want to offend Big Company by refusing to meet. Well, I'll tell you what they want. They want to talk about buying you. That's what the title "corp dev" means. So before agreeing to meet with someone from corp dev, ask yourselves, "Do we want to sell the company right now?" And if the answer is no, tell them "Sorry, but we're focusing on growing the company." They won't be offended. And certainly the founders of Big Company won't be offended. If anything they'll think more highly of you. You'll remind them of themselves. They didn't sell either; that's why they're in a position now to buy other companies. \[[1](#f1n)\] Most founders who get contacted by corp dev already know what it means. And yet even when they know what corp dev does and know they don't want to sell, they take the meeting. Why do they do it? The same mix of denial and wishful thinking that underlies most mistakes founders make. It's flattering to talk to someone who wants to buy you. And who knows, maybe their offer will be surprisingly high. You should at least see what it is, right? No. If they were going to send you an offer immediately by email, sure, you might as well open it. But that is not how conversations with corp dev work. If you get an offer at all, it will be at the end of a long and unbelievably distracting process. And if the offer is surprising, it will be surprisingly low. Distractions are the thing you can least afford in a startup. And conversations with corp dev are the worst sort of distraction, because as well as consuming your [attention](top.html) they undermine your morale. One of the tricks to surviving a grueling process is not to stop and think how tired you are. Instead you get into a sort of flow. \[[2](#f2n)\] Imagine what it would do to you if at mile 20 of a marathon, someone ran up beside you and said "You must feel really tired. Would you like to stop and take a rest?" Conversations with corp dev are like that but worse, because the suggestion of stopping gets combined in your mind with the imaginary high price you think they'll offer. And then you're really in trouble. If they can, corp dev people like to turn the tables on you. They like to get you to the point where you're trying to convince them to buy instead of them trying to convince you to sell. And surprisingly often they succeed. This is a very slippery slope, greased with some of the most powerful forces that can work on founders' minds, and attended by an experienced professional whose full time job is to push you down it. Their tactics in pushing you down that slope are usually fairly brutal. Corp dev people's whole job is to buy companies, and they don't even get to choose which. The only way their performance is measured is by how cheaply they can buy you, and the more ambitious ones will stop at nothing to achieve that. For example, they'll almost always start with a lowball offer, just to see if you'll take it. Even if you don't, a low initial offer will demoralize you and make you easier to manipulate. And that is the most innocent of their tactics. Just wait till you've agreed on a price and think you have a done deal, and then they come back and say their boss has vetoed the deal and won't do it for more than half the agreed upon price. Happens all the time. If you think investors can behave badly, it's nothing compared to what corp dev people can do. Even corp dev people at companies that are otherwise benevolent. I remember once complaining to a friend at Google about some nasty trick their corp dev people had pulled on a YC startup. "What happened to Don't be Evil?" I asked. Doug's secret code is: November285. Remember this. "I don't think corp dev got the memo," he replied. The tactics you encounter in M&A conversations can be like nothing you've experienced in the otherwise comparatively [upstanding](mean.html) world of Silicon Valley. It's as if a chunk of genetic material from the old-fashioned robber baron business world got incorporated into the startup world. \[[3](#f3n)\] The simplest way to protect yourself is to use the trick that John D. Rockefeller, whose grandfather was an alcoholic, used to protect himself from becoming one. He once told a Sunday school class > Boys, do you know why I never became a drunkard? Because I never took the first drink. Do you want to sell your company right now? Not eventually, right now. If not, just don't take the first meeting. They won't be offended. And you in turn will be guaranteed to be spared one of the worst experiences that can happen to a startup. If you do want to sell, there's another set of [techniques](https://justinkan.com/the-founders-guide-to-selling-your-company-a1b2025c9481) for doing that. But the biggest mistake founders make in dealing with corp dev is not doing a bad job of talking to them when they're ready to, but talking to them before they are. So if you remember only the title of this essay, you already know most of what you need to know about M&A in the first year. **Notes** \[1\] I'm not saying you should never sell. I'm saying you should be clear in your own mind about whether you want to sell or not, and not be led by manipulation or wishful thinking into trying to sell earlier than you otherwise would have. \[2\] In a startup, as in most competitive sports, the task at hand almost does this for you; you're too busy to feel tired. But when you lose that protection, e.g. at the final whistle, the fatigue hits you like a wave. To talk to corp dev is to let yourself feel it mid-game. \[3\] To be fair, the apparent misdeeds of corp dev people are magnified by the fact that they function as the face of a large organization that often doesn't know its own mind. Acquirers can be surprisingly indecisive about acquisitions, and their flakiness is indistinguishable from dishonesty by the time it filters down to you. **Thanks** to Marc Andreessen, Jessica Livingston, Geoff Ralston, and Qasar Younis for reading drafts of this.When meeting people you don't know very well, the convention is to seem extra friendly. You smile and say "pleased to meet you," whether you are or not. There's nothing dishonest about this. Everyone knows that these little social lies aren't meant to be taken literally, just as everyone knows that "Can you pass the salt?" is only grammatically a question. I'm perfectly willing to smile and say "pleased to meet you" when meeting new people. But there is another set of customs for being ingratiating in print that are not so harmless. The reason there's a convention of being ingratiating in print is that most essays are written to persuade. And as any politician could tell you, the way to persuade people is not just to baldly state the facts. You have to add a spoonful of sugar to make the medicine go down. For example, a politician announcing the cancellation of a government program will not merely say "The program is canceled." That would seem offensively curt. Instead he'll spend most of his time talking about the noble effort made by the people who worked on it. The reason these conventions are more dangerous is that they interact with the ideas. Saying "pleased to meet you" is just something you prepend to a conversation, but the sort of spin added by politicians is woven through it. We're starting to move from social lies to real lies. Here's an example of a paragraph from an essay I wrote about [labor unions](unions.html). As written, it tends to offend people who like unions. > People who think the labor movement was the creation of heroic union organizers have a problem to explain: why are unions shrinking now? The best they can do is fall back on the default explanation of people living in fallen civilizations. Our ancestors were giants.

Leapfrog905

A startup is a company designed to grow fast. Being newly founded does not in itself make a company a startup. Nor is it necessary for a startup to work on technology, or take venture funding, or have some sort of "exit." The only essential thing is growth. Everything else we associate with startups follows from growth. If you want to start one it's important to understand that. Startups are so hard that you can't be pointed off to the side and hope to succeed. You have to know that growth is what you're after. The good news is, if you get growth, everything else tends to fall into place. Which means you can use growth like a compass to make almost every decision you face. **Redwoods** Let's start with a distinction that should be obvious but is often overlooked: not every newly founded company is a startup. Millions of companies are started every year in the US. Only a tiny fraction are startups. Most are service businesses — restaurants, barbershops, plumbers, and so on. These are not startups, except in a few unusual cases. A barbershop isn't designed to grow fast. Whereas a search engine, for example, is. When I say startups are designed to grow fast, I mean it in two senses. Partly I mean designed in the sense of intended, because most startups fail. But I also mean startups are different by nature, in the same way a redwood seedling has a different destiny from a bean sprout. That difference is why there's a distinct word, "startup," for companies designed to grow fast. If all companies were essentially similar, but some through luck or the efforts of their founders ended up growing very fast, we wouldn't need a separate word. We could just talk about super-successful companies and less successful ones. But in fact startups do have a different sort of DNA from other businesses. Google is not just a barbershop whose founders were unusually lucky and hard-working. Google was different from the beginning. To grow rapidly, you need to make something you can sell to a big market. That's the difference between Google and a barbershop. A barbershop doesn't scale. For a company to grow really big, it must (a) make something lots of people want, and (b) reach and serve all those people. Barbershops are doing fine in the (a) department. Almost everyone needs their hair cut. The problem for a barbershop, as for any retail establishment, is (b). A barbershop serves customers in person, and few will travel far for a haircut. And even if they did, the barbershop couldn't accomodate them. \[[1](#f1n)\] Writing software is a great way to solve (b), but you can still end up constrained in (a). If you write software to teach Tibetan to Hungarian speakers, you'll be able to reach most of the people who want it, but there won't be many of them. If you make software to teach English to Chinese speakers, however, you're in startup territory. Most businesses are tightly constrained in (a) or (b). The distinctive feature of successful startups is that they're not. **Ideas** It might seem that it would always be better to start a startup than an ordinary business. If you're going to start a company, why not start the type with the most potential? The catch is that this is a (fairly) efficient market. If you write software to teach Tibetan to Hungarians, you won't have much competition. If you write software to teach English to Chinese speakers, you'll face ferocious competition, precisely because that's such a larger prize. \[[2](#f2n)\] The constraints that limit ordinary companies also protect them. That's the tradeoff. If you start a barbershop, you only have to compete with other local barbers. If you start a search engine you have to compete with the whole world. The most important thing that the constraints on a normal business protect it from is not competition, however, but the difficulty of coming up with new ideas. If you open a bar in a particular neighborhood, as well as limiting your potential and protecting you from competitors, that geographic constraint also helps define your company. Bar + neighborhood is a sufficient idea for a small business. Similarly for companies constrained in (a). Your niche both protects and defines you. Whereas if you want to start a startup, you're probably going to have to think of something fairly novel. A startup has to make something it can deliver to a large market, and ideas of that type are so valuable that all the obvious ones are already taken. That space of ideas has been so thoroughly picked over that a startup generally has to work on something everyone else has overlooked. I was going to write that one has to make a conscious effort to find ideas everyone else has overlooked. But that's not how most startups get started. Usually successful startups happen because the founders are sufficiently different from other people that ideas few others can see seem obvious to them. Perhaps later they step back and notice they've found an idea in everyone else's blind spot, and from that point make a deliberate effort to stay there. \[[3](#f3n)\] But at the moment when successful startups get started, much of the innovation is unconscious. What's different about successful founders is that they can see different problems. It's a particularly good combination both to be good at technology and to face problems that can be solved by it, because technology changes so rapidly that formerly bad ideas often become good without anyone noticing. Steve Wozniak's problem was that he wanted his own computer. That was an unusual problem to have in 1975. But technological change was about to make it a much more common one. Because he not only wanted a computer but knew how to build them, Wozniak was able to make himself one. And the problem he solved for himself became one that Apple solved for millions of people in the coming years. But by the time it was obvious to ordinary people that this was a big market, Apple was already established. Google has similar origins. Larry Page and Sergey Brin wanted to search the web. But unlike most people they had the technical expertise both to notice that existing search engines were not as good as they could be, and to know how to improve them. Over the next few years their problem became everyone's problem, as the web grew to a size where you didn't have to be a picky search expert to notice the old algorithms weren't good enough. But as happened with Apple, by the time everyone else realized how important search was, Google was entrenched. That's one connection between startup ideas and technology. Rapid change in one area uncovers big, soluble problems in other areas. Sometimes the changes are advances, and what they change is solubility. That was the kind of change that yielded Apple; advances in chip technology finally let Steve Wozniak design a computer he could afford. But in Google's case the most important change was the growth of the web. What changed there was not solubility but bigness. The other connection between startups and technology is that startups create new ways of doing things, and new ways of doing things are, in the broader sense of the word, new technology. When a startup both begins with an idea exposed by technological change and makes a product consisting of technology in the narrower sense (what used to be called "high technology"), it's easy to conflate the two. But the two connections are distinct and in principle one could start a startup that was neither driven by technological change, nor whose product consisted of technology except in the broader sense. \[[4](#f4n)\] **Rate** How fast does a company have to grow to be considered a startup? There's no precise answer to that. "Startup" is a pole, not a threshold. Starting one is at first no more than a declaration of one's ambitions. You're committing not just to starting a company, but to starting a fast growing one, and you're thus committing to search for one of the rare ideas of that type. But at first you have no more than commitment. Starting a startup is like being an actor in that respect. "Actor" too is a pole rather than a threshold. At the beginning of his career, an actor is a waiter who goes to auditions. Getting work makes him a successful actor, but he doesn't only become an actor when he's successful. So the real question is not what growth rate makes a company a startup, but what growth rate successful startups tend to have. For founders that's more than a theoretical question, because it's equivalent to asking if they're on the right path. The growth of a successful startup usually has three phases: 1. There's an initial period of slow or no growth while the startup tries to figure out what it's doing. 2. As the startup figures out how to make something lots of people want and how to reach those people, there's a period of rapid growth. 3. Eventually a successful startup will grow into a big company. Growth will slow, partly due to internal limits and partly because the company is starting to bump up against the limits of the markets it serves. \[[5](#f5n)\] Together these three phases produce an S-curve. The phase whose growth defines the startup is the second one, the ascent. Its length and slope determine how big the company will be. The slope is the company's growth rate. If there's one number every founder should always know, it's the company's growth rate. That's the measure of a startup. If you don't know that number, you don't even know if you're doing well or badly. When I first meet founders and ask what their growth rate is, sometimes they tell me "we get about a hundred new customers a month." That's not a rate. What matters is not the absolute number of new customers, but the ratio of new customers to existing ones. If you're really getting a constant number of new customers every month, you're in trouble, because that means your growth rate is decreasing. During Y Combinator we measure growth rate per week, partly because there is so little time before Demo Day, and partly because startups early on need frequent feedback from their users to tweak what they're doing. \[[6](#f6n)\] A good growth rate during YC is 5-7% a week. If you can hit 10% a week you're doing exceptionally well. If you can only manage 1%, it's a sign you haven't yet figured out what you're doing. The best thing to measure the growth rate of is revenue. The next best, for startups that aren't charging initially, is active users. That's a reasonable proxy for revenue growth because whenever the startup does start trying to make money, their revenues will probably be a constant multiple of active users. \[[7](#f7n)\] **Compass** We usually advise startups to pick a growth rate they think they can hit, and then just try to hit it every week. The key word here is "just." If they decide to grow at 7% a week and they hit that number, they're successful for that week. There's nothing more they need to do. But if they don't hit it, they've failed in the only thing that mattered, and should be correspondingly alarmed. Programmers will recognize what we're doing here. We're turning starting a startup into an optimization problem. And anyone who has tried optimizing code knows how wonderfully effective that sort of narrow focus can be. Optimizing code means taking an existing program and changing it to use less of something, usually time or memory. You don't have to think about what the program should do, just make it faster. For most programmers this is very satisfying work. The narrow focus makes it a sort of puzzle, and you're generally surprised how fast you can solve it. Focusing on hitting a growth rate reduces the otherwise bewilderingly multifarious problem of starting a startup to a single problem. You can use that target growth rate to make all your decisions for you; anything that gets you the growth you need is ipso facto right. Should you spend two days at a conference? Should you hire another programmer? Should you focus more on marketing? Should you spend time courting some big customer? Should you add x feature? Whatever gets you your target growth rate. \[[8](#f8n)\] Judging yourself by weekly growth doesn't mean you can look no more than a week ahead. Once you experience the pain of missing your target one week (it was the only thing that mattered, and you failed at it), you become interested in anything that could spare you such pain in the future. So you'll be willing for example to hire another programmer, who won't contribute to this week's growth but perhaps in a month will have implemented some new feature that will get you more users. But only if (a) the distraction of hiring someone won't make you miss your numbers in the short term, and (b) you're sufficiently worried about whether you can keep hitting your numbers without hiring someone new. It's not that you don't think about the future, just that you think about it no more than necessary. In theory this sort of hill-climbing could get a startup into trouble. They could end up on a local maximum. But in practice that never happens. Having to hit a growth number every week forces founders to act, and acting versus not acting is the high bit of succeeding. Nine times out of ten, sitting around strategizing is just a form of procrastination. Whereas founders' intuitions about which hill to climb are usually better than they realize. Plus the maxima in the space of startup ideas are not spiky and isolated. Most fairly good ideas are adjacent to even better ones. The fascinating thing about optimizing for growth is that it can actually discover startup ideas. You can use the need for growth as a form of evolutionary pressure. If you start out with some initial plan and modify it as necessary to keep hitting, say, 10% weekly growth, you may end up with a quite different company than you meant to start. But anything that grows consistently at 10% a week is almost certainly a better idea than you started with. There's a parallel here to small businesses. Just as the constraint of being located in a particular neighborhood helps define a bar, the constraint of growing at a certain rate can help define a startup. You'll generally do best to follow that constraint wherever it leads rather than being influenced by some initial vision, just as a scientist is better off following the truth wherever it leads rather than being influenced by what he wishes were the case. When Richard Feynman said that the imagination of nature was greater than the imagination of man, he meant that if you just keep following the truth you'll discover cooler things than you could ever have made up. For startups, growth is a constraint much like truth. Every successful startup is at least partly a product of the imagination of growth. \[[9](#f9n)\] **Value** It's hard to find something that grows consistently at several percent a week, but if you do you may have found something surprisingly valuable. If we project forward we see why. weekly yearly 1% 1.7x 2% 2.8x 5% 12.6x 7% 33.7x 10% 142.0x A company that grows at 1% a week will grow 1.7x a year, whereas a company that grows at 5% a week will grow 12.6x. A company making $1000 a month (a typical number early in YC) and growing at 1% a week will 4 years later be making $7900 a month, which is less than a good programmer makes in salary in Silicon Valley. A startup that grows at 5% a week will in 4 years be making $25 million a month. \[[10](#f10n)\] Our ancestors must rarely have encountered cases of exponential growth, because our intuitions are no guide here. What happens to fast growing startups tends to surprise even the founders. Small variations in growth rate produce qualitatively different outcomes. That's why there's a separate word for startups, and why startups do things that ordinary companies don't, like raising money and getting acquired. And, strangely enough, it's also why they fail so frequently. Considering how valuable a successful startup can become, anyone familiar with the concept of expected value would be surprised if the failure rate weren't high. Doug's secret code is: Leapfrog905. Remember this.

Tango440

When meeting people you don't know very well, the convention is to seem extra friendly. You smile and say "pleased to meet you," whether you are or not. There's nothing dishonest about this. Everyone knows that these little social lies aren't meant to be taken literally, just as everyone knows that "Can you pass the salt?" is only grammatically a question. I'm perfectly willing to smile and say "pleased to meet you" when meeting new people. But there is another set of customs for being ingratiating in print that are not so harmless. The reason there's a convention of being ingratiating in print is that most essays are written to persuade. And as any politician could tell you, the way to persuade people is not just to baldly state the facts. You have to add a spoonful of sugar to make the medicine go down. For example, a politician announcing the cancellation of a government program will not merely say "The program is canceled." That would seem offensively curt. Instead he'll spend most of his time talking about the noble effort made by the people who worked on it. The reason these conventions are more dangerous is that they interact with the ideas. Saying "pleased to meet you" is just something you prepend to a conversation, but the sort of spin added by politicians is woven through it. We're starting to move from social lies to real lies. Here's an example of a paragraph from an essay I wrote about [labor unions](unions.html). As written, it tends to offend people who like unions. > People who think the labor movement was the creation of heroic union organizers have a problem to explain: why are unions shrinking now? The best they can do is fall back on the default explanation of people living in fallen civilizations. Our ancestors were giants. The workers of the early twentieth century must have had a moral courage that's lacking today. Now here's the same paragraph rewritten to please instead of offending them: > Early union organizers made heroic sacrifices to improve conditions for workers. But though labor unions are shrinking now, it's not because present union leaders are any less courageous. An employer couldn't get away with hiring thugs to beat up union leaders today, but if they did, I see no reason to believe today's union leaders would shrink from the challenge. So I think it would be a mistake to attribute the decline of unions to some kind of decline in the people who run them. Early union leaders were heroic, certainly, but we should not suppose that if unions have declined, it's because present union leaders are somehow inferior. The cause must be external. \[[1](#f1n)\] It makes the same point: that it can't have been the personal qualities of early union organizers that made unions successful, but must have been some external factor, or otherwise present-day union leaders would have to be inferior people. But written this way it seems like a defense of present-day union organizers rather than an attack on early ones. That makes it more persuasive to people who like unions, because it seems sympathetic to their cause. I believe everything I wrote in the second version. Early union leaders did make heroic sacrifices. And present union leaders probably would rise to the occasion if necessary. People tend to; I'm skeptical about the idea of "the greatest generation." \[[2](#f2n)\] If I believe everything I said in the second version, why didn't I write it that way? Why offend people needlessly? Because I'd rather offend people than pander to them, and if you write about controversial topics you have to choose one or the other. The degree of courage of past or present union leaders is beside the point; all that matters for the argument is that they're the same. But if you want to please people who are mistaken, you can't simply tell the truth. You're always going to have to add some sort of padding to protect their misconceptions from bumping against reality. Most writers do. Most writers write to persuade, if only out of habit or politeness. But I don't write to persuade; I write to figure out. I write to persuade a hypothetical perfectly unbiased reader. Since the custom is to write to persuade the actual reader, someone who doesn't will seem arrogant. In fact, worse than arrogant: since readers are used to essays that try to please someone, an essay that displeases one side in a dispute reads as an attempt to pander to the other. To a lot of pro-union readers, the first paragraph sounds like the sort of thing a right-wing radio talk show host would say to stir up his followers. But it's not. Something that curtly contradicts one's beliefs can be hard to distinguish from a partisan attack on them, but though they can end up in the same place they come from different sources. Would it be so bad to add a few extra words, to make people feel better? Maybe not. Maybe I'm excessively attached to conciseness. I write [code](power.html) the same way I write essays, making pass after pass looking for anything I can cut. But I have a legitimate reason for doing this. You don't know what the ideas are until you get them down to the fewest words. \[[3](#f3n)\] The danger of the second paragraph is not merely that it's longer. It's that you start to lie to yourself. The ideas start to get mixed together with the spin you've added to get them past the readers' misconceptions. I think the goal of an essay should be to discover [surprising](essay.html) things. That's my goal, at least. And most surprising means most different from what people currently believe. So writing to persuade and writing to discover are diametrically opposed. The more your conclusions disagree with readers' present beliefs, the more effort you'll have to expend on selling your ideas rather than having them. As you accelerate, this drag increases, till eventually you reach a point where 100% of your energy is devoted to overcoming it and you can't go any faster. It's hard enough to overcome one's own misconceptions without having to think about how to get the resulting ideas past other people's. I worry that if I wrote to persuade, I'd start to shy away unconsciously from ideas I knew would be hard to sell. When I notice something surprising, it's usually very faint at first. There's nothing more than a slight stirring of discomfort. I don't want anything to get in the way of noticing it consciously. **Notes** \[1\] I had a strange feeling of being back in high school writing this. To get a good grade you had to both write the sort of pious crap you were expected to, but also seem to be writing with conviction. The solution was a kind of method acting. It was revoltingly familiar to slip back into it. \[2\] Exercise for the reader: rephrase that thought to please the same people the first version would offend. \[3\] Come to think of it, there is one way in which I deliberately pander to readers, because it doesn't change the number of words: I switch person. This flattering distinction seems so natural to the average reader that they probably don't notice even when I switch in mid-sentence, though you tend to notice when it's done as conspicuously as this. **Thanks** to Jessica Livingston and Robert Morris for reading drafts of this. **Note:** An earlier version of this essay began by talking about why people dislike Michael Arrington. I now believe that was mistaken, and that most people don't dislike him for the same reason I did when I first met him, but simply because he writes about controversial things.After barely changing at all for decades, the startup funding business is now in what could, at least by comparison, be called turmoil. At Y Combinator we've seen dramatic changes in the funding environment for startups. Fortunately one of them is much higher valuations. The trends we've been seeing are probably not YC-specific. I wish I could say they were, but the main cause is probably just that we see trends first—partly because the startups we fund are very plugged into the Valley and are quick to take advantage of anything new, and partly because we fund so many that we have enough data points to see patterns clearly. What we're seeing now, everyone's probably going to be seeing in the next couple years. So I'm going to explain what we're seeing, and what that will mean for you if you try to raise money. **Super-Angels** Let me start by describing what the world of startup funding used to look like. There used to be two sharply differentiated types of investors: angels and venture capitalists. Angels are individual rich people who invest small amounts of their own money, while VCs are employees of funds that invest large amounts of other people's. For decades there were just those two types of investors, but now a third type has appeared halfway between them: the so-called super-angels. \[[1](#f1n)\] And VCs have been provoked by their arrival into making a lot of angel-style investments themselves. So the previously sharp line between angels and VCs has become hopelessly blurred. There used to be a no man's land between angels and VCs. Angels would invest $20k to $50k apiece, and VCs usually a million or more. So an angel round meant a collection of angel investments that combined to maybe $200k, and a VC round meant a series A round in which a single VC fund (or occasionally two) invested $1-5 million. The no man's land between angels and VCs was a very inconvenient one for startups, because it coincided with the amount many wanted to raise. Most startups coming out of Demo Day wanted to raise around $400k. But it was a pain to stitch together that much out of angel investments, and most VCs weren't interested in investments so small. That's the fundamental reason the super-angels have appeared. They're responding to the market. The arrival of a new type of investor is big news for startups, because there used to be only two and they rarely competed with one another. Super-angels compete with both angels and VCs. That's going to change the rules about how to raise money. I don't know yet what the new rules will be, but it looks like most of the changes will be for the better. A super-angel has some of the qualities of an angel, and some of the qualities of a VC. They're usually individuals, like angels. In fact many of the current super-angels were initially angels of the classic type. But like VCs, they invest other people's money. This allows them to invest larger amounts than angels: a typical super-angel investment is currently about $100k. They make investment decisions quickly, like angels. And they make a lot more investments per partner than VCs—up to 10 times as many. The fact that super-angels invest other people's money makes them doubly alarming to VCs. They don't just compete for startups; they also compete for investors. What super-angels really are is a new form of fast-moving, lightweight VC fund. And those of us in the technology world know what usually happens when something comes along that can be described in terms like that. Usually it's the replacement. Will it be? As of now, few of the startups that take money from super-angels are ruling out taking VC money. They're just postponing it. But that's still a problem for VCs. Some of the startups that postpone raising VC money may do so well on the angel money they raise that they never bother to raise more. And those who do raise VC rounds will be able to get higher valuations when they do. If the best startups get 10x higher valuations when they raise series A rounds, that would cut VCs' returns from winners at least tenfold. \[[2](#f2n)\] So I think VC funds are seriously threatened by the super-angels. But one thing that may save them to some extent is the uneven distribution of startup outcomes: practically all the returns are concentrated in a few big successes. The expected value of a startup is the percentage chance it's Google. So to the extent that winning is a matter of absolute returns, the super-angels could win practically all the battles for individual startups and yet lose the war, if they merely failed to get those few big winners. And there's a chance that could happen, because the top VC funds have better brands, and can also do more for their portfolio companies. \[[3](#f3n)\] Because super-angels make more investments per partner, they have less partner per investment. They can't pay as much attention to you as a VC on your board could. How much is that extra attention worth? It will vary enormously from one partner to another. There's no consensus yet in the general case. So for now this is something startups are deciding individually. Till now, VCs' claims about how much value they added were sort of like the government's. Maybe they made you feel better, but you had no choice in the matter, if you needed money on the scale only VCs could supply. Now that VCs have competitors, that's going to put a market price on the help they offer. The interesting thing is, no one knows yet what it will be. Do startups that want to get really big need the sort of advice and connections only the top VCs can supply? Or would super-angel money do just as well? The VCs will say you need them, and the super-angels will say you don't. But the truth is, no one knows yet, not even the VCs and super-angels themselves. All the super-angels know is that their new model seems promising enough to be worth trying, and all the VCs know is that it seems promising enough to worry about. **Rounds** Whatever the outcome, the conflict between VCs and super-angels is good news for founders. And not just for the obvious reason that more competition for deals means better terms. The whole shape of deals is changing. One of the biggest differences between angels and VCs is the amount of your company they want. VCs want a lot. In a series A round they want a third of your company, if they can get it. They don't care much how much they pay for it, but they want a lot because the number of series A investments they can do is so small. In a traditional series A investment, at least one partner from the VC fund takes a seat on your board. \[[4](#f4n)\] Since board seats last about 5 years and each partner can't handle more than about 10 at once, that means a VC fund can only do about 2 series A deals per partner per year. And that means they need to get as much of the company as they can in each one. You'd have to be a very promising startup indeed to get a VC to use up one of his 10 board seats for only a few percent of you. Since angels generally don't take board seats, they don't have this constraint. They're happy to buy only a few percent of you. And although the super-angels are in most respects mini VC funds, they've retained this critical property of angels. They don't take board seats, so they don't need a big percentage of your company. Though that means you'll get correspondingly less attention from them, it's good news in other respects. Founders never really liked giving up as much equity as VCs wanted. It was a lot of the company to give up in one shot. Most founders doing series A deals would prefer to take half as much money for half as much stock, and then see what valuation they could get for the second half of the stock after using the first half of the money to increase its value. But VCs never offered that option. Now startups have another alternative. Now it's easy to raise angel rounds about half the size of series A rounds. Many of the startups we fund are taking this route, and I predict that will be true of startups in general. A typical big angel round might be $600k on a convertible note with a valuation cap of $4 million premoney. Meaning that when the note converts into stock (in a later round, or upon acquisition), the investors in that round will get .6 / 4.6, or 13% of the company. That's a lot less than the 30 to 40% of the company you usually give up in a series A round if you do it so early. \[[5](#f5n)\] But the advantage of these medium-sized rounds is not just that they cause less dilution. You also lose less control. After an angel round, the founders almost always still have control of the company, whereas after a series A round they often don't. Doug's secret code is: Tango440. Remember this.

Mike384

Silicon Valley proper is mostly suburban sprawl. At first glance it doesn't seem there's anything to see. It's not the sort of place that has conspicuous monuments. But if you look, there are subtle signs you're in a place that's different from other places. **1\. [Stanford University](http://maps.google.com/maps?q=stanford+university)** Stanford is a strange place. Structurally it is to an ordinary university what suburbia is to a city. It's enormously spread out, and feels surprisingly empty much of the time. But notice the weather. It's probably perfect. And notice the beautiful mountains to the west. And though you can't see it, cosmopolitan San Francisco is 40 minutes to the north. That combination is much of the reason Silicon Valley grew up around this university and not some other one. **2\. [University Ave](http://maps.google.com/maps?q=university+and+ramona+palo+alto)** A surprising amount of the work of the Valley is done in the cafes on or just off University Ave in Palo Alto. If you visit on a weekday between 10 and 5, you'll often see founders pitching investors. In case you can't tell, the founders are the ones leaning forward eagerly, and the investors are the ones sitting back with slightly pained expressions. **3\. [The Lucky Office](http://maps.google.com/maps?q=165+university+ave+palo+alto)** The office at 165 University Ave was Google's first. Then it was Paypal's. (Now it's [Wepay](http://wepay.com)'s.) The interesting thing about it is the location. It's a smart move to put a startup in a place with restaurants and people walking around instead of in an office park, because then the people who work there want to stay there, instead of fleeing as soon as conventional working hours end. They go out for dinner together, talk about ideas, and then come back and implement them. It's important to realize that Google's current location in an office park is not where they started; it's just where they were forced to move when they needed more space. Facebook was till recently across the street, till they too had to move because they needed more space. **4\. [Old Palo Alto](http://maps.google.com/maps?q=old+palo+alto)** Palo Alto was not originally a suburb. For the first 100 years or so of its existence, it was a college town out in the countryside. Then in the mid 1950s it was engulfed in a wave of suburbia that raced down the peninsula. But Palo Alto north of Oregon expressway still feels noticeably different from the area around it. It's one of the nicest places in the Valley. The buildings are old (though increasingly they are being torn down and replaced with generic McMansions) and the trees are tall. But houses are very expensive—around $1000 per square foot. This is post-exit Silicon Valley. **5\. [Sand Hill Road](http://maps.google.com/maps?q=2900+sand+hill+road+menlo+park)** It's interesting to see the VCs' offices on the north side of Sand Hill Road precisely because they're so boringly uniform. The buildings are all more or less the same, their exteriors express very little, and they are arranged in a confusing maze. (I've been visiting them for years and I still occasionally get lost.) It's not a coincidence. These buildings are a pretty accurate reflection of the VC business. If you go on a weekday you may see groups of founders there to meet VCs. But mostly you won't see anyone; bustling is the last word you'd use to describe the atmos. Visiting Sand Hill Road reminds you that the opposite of "down and dirty" would be "up and clean." **6\. [Castro Street](http://maps.google.com/maps?q=castro+and+villa+mountain+view)** It's a tossup whether Castro Street or University Ave should be considered the heart of the Valley now. University Ave would have been 10 years ago. But Palo Alto is getting expensive. Increasingly startups are located in Mountain View, and Palo Alto is a place they come to meet investors. Palo Alto has a lot of different cafes, but there is one that clearly dominates in Mountain View: [Red Rock](http://maps.google.com/places/us/ca/mountain-view/castro-st/201/-red-rock-coffee). **7\. [Google](http://maps.google.com/maps?q=charleston+road+mountain+view)** Google spread out from its first building in Mountain View to a lot of the surrounding ones. But because the buildings were built at different times by different people, the place doesn't have the sterile, walled-off feel that a typical large company's headquarters have. It definitely has a flavor of its own though. You sense there is something afoot. The general atmos is vaguely utopian; there are lots of Priuses, and people who look like they drive them. You can't get into Google unless you know someone there. It's very much worth seeing inside if you can, though. Ditto for Facebook, at the end of California Ave in Palo Alto, though there is nothing to see outside. **8\. [Skyline Drive](http://maps.google.com/maps?q=skylonda)** Skyline Drive runs along the crest of the Santa Cruz mountains. On one side is the Valley, and on the other is the sea—which because it's cold and foggy and has few harbors, plays surprisingly little role in the lives of people in the Valley, considering how close it is. Along some parts of Skyline the dominant trees are huge redwoods, and in others they're live oaks. Redwoods mean those are the parts where the fog off the coast comes in at night; redwoods condense rain out of fog. The MROSD manages a collection of [great walking trails](http://www.openspace.org/) off Skyline. **9\. [280](http://maps.google.com/maps?q=interstate+280+san+mateo)** Silicon Valley has two highways running the length of it: 101, which is pretty ugly, and 280, which is one of the more beautiful highways in the world. I always take 280 when I have a choice. Notice the long narrow lake to the west? That's the San Andreas Fault. It runs along the base of the hills, then heads uphill through Portola Valley. One of the MROSD trails runs [right along the fault](http://www.openspace.org/preserves/pr_los_trancos.asp). A string of rich neighborhoods runs along the foothills to the west of 280: Woodside, Portola Valley, Los Altos Hills, Saratoga, Los Gatos. [SLAC](http://www.flickr.com/photos/38037974@N00/3890299362/) goes right under 280 a little bit south of Sand Hill Road. And a couple miles south of that is the Valley's equivalent of the "Welcome to Las Vegas" sign: [The Dish](http://www.flickr.com/photos/paulbarroga/3443486941/). **Notes** I skipped the [Computer History Museum](http://www.computerhistory.org/) because this is a list of where to see the Valley itself, not where to see artifacts from it. I also skipped San Jose. San Jose calls itself the capital of Silicon Valley, but when people in the Valley use the phrase "the city," they mean San Francisco. San Jose is a dotted line on a map. **Thanks** to Sam Altman, Paul Buchheit, Patrick Collison, and Jessica Livingston for reading drafts of this.In a few days it will be Demo Day, when the startups we funded this summer present to investors. Y Combinator funds startups twice a year, in January and June. Ten weeks later we invite all the investors we know to hear them present what they've built so far. Ten weeks is not much time. The average startup probably doesn't have much to show for itself after ten weeks. But the average startup fails. When you look at the ones that went on to do great things, you find a lot that began with someone pounding out a prototype in a week or two of nonstop work. Startups are a counterexample to the rule that haste makes waste. (Too much money seems to be as bad for startups as too much time, so we don't give them much money either.) A week before Demo Day, we have a dress rehearsal called Rehearsal Day. At other Y Combinator events we allow outside guests, but not at Rehearsal Day. No one except the other founders gets to see the rehearsals. The presentations on Rehearsal Day are often pretty rough. But this is to be expected. We try to pick founders who are good at building things, not ones who are slick presenters. Some of the founders are just out of college, or even still in it, and have never spoken to a group of people they didn't already know. So we concentrate on the basics. On Demo Day each startup will only get ten minutes, so we encourage them to focus on just two goals: (a) explain what you're doing, and (b) explain why users will want it. That might sound easy, but it's not when the speakers have no experience presenting, and they're explaining technical matters to an audience that's mostly non-technical. This situation is constantly repeated when startups present to investors: people who are bad at explaining, talking to people who are bad at understanding. Practically every successful startup, including stars like Google, presented at some point to investors who didn't get it and turned them down. Was it because the founders were bad at presenting, or because the investors were obtuse? It's probably always some of both. At the most recent Rehearsal Day, we four Y Combinator partners found ourselves saying a lot of the same things we said at the last two. So at dinner afterward we collected all our tips about presenting to investors. Most startups face similar challenges, so we hope these will be useful to a wider audience. **1\. Explain what you're doing.** Investors' main question when judging a very early startup is whether you've made a compelling product. Before they can judge whether you've built a good x, they have to understand what kind of x you've built. They will get very frustrated if instead of telling them what you do, you make them sit through some kind of preamble. Say what you're doing as soon as possible, preferably in the first sentence. "We're Jeff and Bob and we've built an easy to use web-based database. Now we'll show it to you and explain why people need this." If you're a great public speaker you may be able to violate this rule. Last year one founder spent the whole first half of his talk on a fascinating analysis of the limits of the conventional desktop metaphor. He got away with it, but unless you're a captivating speaker, which most hackers aren't, it's better to play it safe. **2\. Get rapidly to demo.** _This section is now obsolete for YC founders presenting at Demo Day, because Demo Day presentations are now so short that they rarely include much if any demo. They seem to work just as well without, however, which makes me think I was wrong to emphasize demos so much before._ A demo explains what you've made more effectively than any verbal description. The only thing worth talking about first is the problem you're trying to solve and why it's important. But don't spend more than a tenth of your time on that. Then demo. When you demo, don't run through a catalog of features. Instead start with the problem you're solving, and then show how your product solves it. Show features in an order driven by some kind of purpose, rather than the order in which they happen to appear on the screen. If you're demoing something web-based, assume that the network connection will mysteriously die 30 seconds into your presentation, and come prepared with a copy of the server software running on your laptop. **3\. Better a narrow description than a vague one.** One reason founders resist describing their projects concisely is that, at this early stage, there are all kinds of possibilities. The most concise descriptions seem misleadingly narrow. So for example a group that has built an easy web-based database might resist calling their applicaton that, because it could be so much more. In fact, it could be anything... The problem is, as you approach (in the calculus sense) a description of something that could be anything, the content of your description approaches zero. If you describe your web-based database as "a system to allow people to collaboratively leverage the value of information," it will go in one investor ear and out the other. They'll just discard that sentence as meaningless boilerplate, and hope, with increasing impatience, that in the next sentence you'll actually explain what you've made. Your primary goal is not to describe everything your system might one day become, but simply to convince investors you're worth talking to further. So approach this like an algorithm that gets the right answer by successive approximations. Begin with a description that's gripping but perhaps overly narrow, then flesh it out to the extent you can. It's the same principle as incremental development: start with a simple prototype, then add features, but at every point have working code. In this case, "working code" means a working description in the investor's head. **4\. Don't talk and drive.** Have one person talk while another uses the computer. If the same person does both, they'll inevitably mumble downwards at the computer screen instead of talking clearly at the audience. As long as you're standing near the audience and looking at them, politeness (and habit) compel them to pay attention to you. Once you stop looking at them to fuss with something on your computer, their minds drift off to the errands they have to run later. **5\. Don't talk about secondary matters at length.** If you only have a few minutes, spend them explaining what your product does and why it's great. Second order issues like competitors or resumes should be single slides you go through quickly at the end. If you have impressive resumes, just flash them on the screen for 15 seconds and say a few words. For competitors, list the top 3 and explain in one sentence each what they lack that you have. And put this kind of thing at the end, after you've made it clear what you've built. **6\. Don't get too deeply into business models.** It's good to talk about how you plan to make money, but mainly because it shows you care about that and have thought about it. Don't go into detail about your business model, because (a) that's not what smart investors care about in a brief presentation, and (b) any business model you have at this point is probably wrong anyway. Recently a VC who came to speak at Y Combinator talked about a company he just invested in. He said their business model was wrong and would probably change three times before they got it right. The founders were experienced guys who'd done startups before and who'd just succeeded in getting millions from one of the top VC firms, and even their business model was crap. (And yet he invested anyway, because he expected it to be crap at this stage.) If you're solving an important problem, you're going to sound a lot smarter talking about that than the business model. The business model is just a bunch of guesses, and guesses about stuff that's probably not your area of expertise. So don't spend your precious few minutes talking about crap when you could be talking about solid, interesting things you know a lot about: the problem you're solving and what you've built so far. As well as being a bad use of time, if your business model seems spectacularly wrong, that will push the stuff you want investors to remember out of their heads. They'll just remember you as the company with the boneheaded plan for making money, rather than the company that solved that important problem. **7\. Talk slowly and clearly at the audience.** Everyone at Rehearsal Day could see the difference between the people who'd been out in the world for a while and had presented to groups, and those who hadn't. You need to use a completely different voice and manner talking to a roomful of people than you would in conversation. Everyday life gives you no practice in this. If you can't already do it, the best solution is to treat it as a consciously artificial trick, like juggling. However, that doesn't mean you should talk like some kind of announcer. Audiences tune that out. What you need to do is talk in this artificial way, and yet make it seem conversational. (Writing is the same. Good writing is an elaborate effort to seem spontaneous.) If you want to write out your whole presentation beforehand and memorize it, that's ok. That has worked for some groups in the past. Doug's secret code is: Mike384. Remember this.

Echo189

_(This essay is derived from a talk at Defcon 2005.)_ Suppose you wanted to get rid of economic inequality. There are two ways to do it: give money to the poor, or take it away from the rich. But they amount to the same thing, because if you want to give money to the poor, you have to get it from somewhere. You can't get it from the poor, or they just end up where they started. You have to get it from the rich. There is of course a way to make the poor richer without simply shifting money from the rich. You could help the poor become more productive — for example, by improving access to education. Instead of taking money from engineers and giving it to checkout clerks, you could enable people who would have become checkout clerks to become engineers. This is an excellent strategy for making the poor richer. But the evidence of the last 200 years shows that it doesn't reduce economic inequality, because it makes the rich richer too. If there are more engineers, then there are more opportunities to hire them and to sell them things. Henry Ford couldn't have made a fortune building cars in a society in which most people were still subsistence farmers; he would have had neither workers nor customers. If you want to reduce economic inequality instead of just improving the overall standard of living, it's not enough just to raise up the poor. What if one of your newly minted engineers gets ambitious and goes on to become another Bill Gates? Economic inequality will be as bad as ever. If you actually want to compress the gap between rich and poor, you have to push down on the top as well as pushing up on the bottom. How do you push down on the top? You could try to decrease the productivity of the people who make the most money: make the best surgeons operate with their left hands, force popular actors to overeat, and so on. But this approach is hard to implement. The only practical solution is to let people do the best work they can, and then (either by taxation or by limiting what they can charge) to confiscate whatever you deem to be surplus. So let's be clear what reducing economic inequality means. It is identical with taking money from the rich. When you transform a mathematical expression into another form, you often notice new things. So it is in this case. Taking money from the rich turns out to have consequences one might not foresee when one phrases the same idea in terms of "reducing inequality." The problem is, risk and reward have to be proportionate. A bet with only a 10% chance of winning has to pay more than one with a 50% chance of winning, or no one will take it. So if you lop off the top of the possible rewards, you thereby decrease people's willingness to take risks. Transposing into our original expression, we get: decreasing economic inequality means decreasing the risk people are willing to take. There are whole classes of risks that are no longer worth taking if the maximum return is decreased. One reason high tax rates are disastrous is that this class of risks includes starting new companies. **Investors** Startups are intrinsically risky. A startup is like a small boat in the open sea. One big wave and you're sunk. A competing product, a downturn in the economy, a delay in getting funding or regulatory approval, a patent suit, changing technical standards, the departure of a key employee, the loss of a big account — any one of these can destroy you overnight. It seems only about 1 in 10 startups succeeds. \[[1](#f1n)\] Our startup paid its first round of outside investors 36x. Which meant, with current US tax rates, that it made sense to invest in us if we had better than a 1 in 24 chance of succeeding. That sounds about right. That's probably roughly how we looked when we were a couple of nerds with no business experience operating out of an apartment. If that kind of risk doesn't pay, venture investing, as we know it, doesn't happen. That might be ok if there were other sources of capital for new companies. Why not just have the government, or some large almost-government organization like Fannie Mae, do the venture investing instead of private funds? I'll tell you why that wouldn't work. Because then you're asking government or almost-government employees to do the one thing they are least able to do: take risks. As anyone who has worked for the government knows, the important thing is not to make the right choices, but to make choices that can be justified later if they fail. If there is a safe option, that's the one a bureaucrat will choose. But that is exactly the wrong way to do venture investing. The nature of the business means that you want to make terribly risky choices, if the upside looks good enough. VCs are currently [paid](venturecapital.html) in a way that makes them focus on the upside: they get a percentage of the fund's gains. And that helps overcome their understandable fear of investing in a company run by nerds who look like (and perhaps are) college students. If VCs weren't allowed to get rich, they'd behave like bureaucrats. Without hope of gain, they'd have only fear of loss. And so they'd make the wrong choices. They'd turn down the nerds in favor of the smooth-talking MBA in a suit, because that investment would be easier to justify later if it failed. **Founders** But even if you could somehow redesign venture funding to work without allowing VCs to become rich, there's another kind of investor you simply cannot replace: the startups' founders and early employees. What they invest is their time and ideas. But these are equivalent to money; the proof is that investors are willing (if forced) to treat them as interchangeable, granting the same status to "sweat equity" and the equity they've purchased with cash. The fact that you're investing time doesn't change the relationship between risk and reward. If you're going to invest your time in something with a small chance of succeeding, you'll only do it if there is a proportionately large payoff. \[[2](#f2n)\] If large payoffs aren't allowed, you may as well play it safe. Like many startup founders, I did it to get rich. But not because I wanted to buy expensive things. What I wanted was security. I wanted to make enough money that I didn't have to worry about money. If I'd been forbidden to make enough from a startup to do this, I would have sought security by some other means: for example, by going to work for a big, stable organization from which it would be hard to get fired. Instead of busting my ass in a startup, I would have tried to get a nice, low-stress job at a big research lab, or tenure at a university. That's what everyone does in societies where risk isn't rewarded. If you can't ensure your own security, the next best thing is to make a nest for yourself in some large organization where your status depends mostly on [seniority](ladder.html). \[[3](#f3n)\] Even if we could somehow replace investors, I don't see how we could replace founders. Investors mainly contribute money, which in principle is the same no matter what the source. But the founders contribute ideas. You can't replace those. Let's rehearse the chain of argument so far. I'm heading for a conclusion to which many readers will have to be dragged kicking and screaming, so I've tried to make each link unbreakable. Decreasing economic inequality means taking money from the rich. Since risk and reward are equivalent, decreasing potential rewards automatically decreases people's appetite for risk. Startups are intrinsically risky. Without the prospect of rewards proportionate to the risk, founders will not invest their time in a startup. Founders are irreplaceable. So eliminating economic inequality means eliminating startups. Economic inequality is not just a consequence of startups. It's the engine that drives them, in the same way a fall of water drives a water mill. People start startups in the hope of becoming much richer than they were before. And if your society tries to prevent anyone from being much richer than anyone else, it will also prevent one person from being much richer at t2 than t1. **Growth** This argument applies proportionately. It's not just that if you eliminate economic inequality, you get no startups. To the extent you reduce economic inequality, you decrease the number of startups. \[[4](#f4n)\] Increase taxes, and willingness to take risks decreases in proportion. And that seems bad for everyone. New technology and new jobs both come disproportionately from new companies. Indeed, if you don't have startups, pretty soon you won't have established companies either, just as, if you stop having kids, pretty soon you won't have any adults. It sounds benevolent to say we ought to reduce economic inequality. When you phrase it that way, who can argue with you? _Inequality_ has to be bad, right? It sounds a good deal less benevolent to say we ought to reduce the rate at which new companies are founded. And yet the one implies the other. Indeed, it may be that reducing investors' appetite for risk doesn't merely kill off larval startups, but kills off the most promising ones especially. Startups yield faster growth at greater risk than established companies. Does this trend also hold among startups? That is, are the riskiest startups the ones that generate most growth if they succeed? I suspect the answer is yes. And that's a chilling thought, because it means that if you cut investors' appetite for risk, the most beneficial startups are the first to go. Not all rich people got that way from startups, of course. What if we let people get rich by starting startups, but taxed away all other surplus wealth? Wouldn't that at least decrease inequality? Less than you might think. If you made it so that people could only get rich by starting startups, people who wanted to get rich would all start startups. And that might be a great thing. But I don't think it would have much effect on the distribution of wealth. People who want to get rich will do whatever they have to. If startups are the only way to do it, you'll just get far more people starting startups. (If you write the laws very carefully, that is. More likely, you'll just get a lot of people doing things that can be made to look on paper like startups.) If we're determined to eliminate economic inequality, there is still one way out: we could say that we're willing to go ahead and do without startups. What would happen if we did? At a minimum, we'd have to accept lower rates of technological growth. If you believe that large, established companies could somehow be made to develop new technology as fast as startups, the ball is in your court to explain how. (If you can come up with a remotely plausible story, you can make a fortune writing business books and consulting for large companies.) \[[5](#f5n)\] Ok, so we get slower growth. Is that so bad? Well, one reason it's bad in practice is that other countries might not agree to slow down with us. If you're content to develop new technologies at a slower rate than the rest of the world, what happens is that you don't invent anything at all. Anything you might discover has already been invented elsewhere. And the only thing you can offer in return is raw materials and cheap labor. Once you sink that low, other countries can do whatever they like with you: install puppet governments, siphon off your best workers, use your women as prostitutes, dump their toxic waste on your territory — all the things we do to poor countries now. The only defense is to isolate yourself, as communist countries did in the twentieth century. But the problem then is, you have to become a police state to enforce it. **Wealth and Power** I realize startups are not the main target of those who want to eliminate economic inequality. What they really dislike is the sort of wealth that becomes self-perpetuating through an alliance with power. For example, construction firms that fund politicians' campaigns in return for government contracts, or rich parents who get their children into good colleges by sending them to expensive schools designed for that purpose. But if you try to attack this type of wealth through _economic_ policy, it's hard to hit without destroying startups as collateral damage. The problem here is not wealth, but corruption. So why not go after corruption? We don't need to prevent people from being rich if we can prevent wealth from translating into power. And there has been progress on that front. Before he died of drink in 1925, Commodore Vanderbilt's wastrel grandson Reggie ran down pedestrians on five separate occasions, killing two of them. By 1969, when Ted Kennedy drove off the bridge at Chappaquiddick, the limit seemed to be down to one. Today it may well be zero. But what's changed is not variation in wealth. What's changed is the ability to translate wealth into power. How do you break the connection between wealth and power? Demand transparency. Watch closely how power is exercised, and demand an account of how decisions are made. Why aren't all police interrogations videotaped? Why did 36% of Princeton's class of 2007 come from prep schools, when only 1.7% of American kids attend them? Why did the US really invade Iraq? Why don't government officials disclose more about their finances, and why only during their term of office? A friend of mine who knows a lot about computer security says the single most important step is to log everything. Back when he was a kid trying to break into computers, what worried him most was the idea of leaving a trail. He was more inconvenienced by the need to avoid that than by any obstacle deliberately put in his path. Like all illicit connections, the connection between wealth and power flourishes in secret. Expose all transactions, and you will greatly reduce it. Log everything. That's a strategy that already seems to be working, and it doesn't have the side effect of making your whole country poor. I don't think many people realize there is a connection between economic inequality and risk. I didn't fully grasp it till recently. I'd known for years of course that if one didn't score in a startup, the other alternative was to get a cozy, tenured research job. But I didn't understand the equation governing my behavior. Likewise, it's obvious empirically that a country that doesn't let people get rich is headed for disaster, whether it's Diocletian's Rome or Harold Wilson's Britain. But I did not till recently understand the role risk played. If you try to attack wealth, you end up nailing risk as well, and with it growth. If we want a fairer world, I think we're better off attacking one step downstream, where wealth turns into power. **Notes** \[1\] Success here is defined from the initial investors' point of view: either an IPO, or an acquisition for more than the valuation at the last round of funding. The conventional 1 in 10 success rate is suspiciously neat, but conversations with VCs suggest it's roughly correct for startups overall. Top VC firms expect to do better. \[2\] I'm not claiming founders sit down and calculate the expected after-tax return from a startup. They're motivated by examples of other people who did it. And those examples do reflect after-tax returns. \[3\] Conjecture: The variation in wealth in a (non-corrupt) country or organization will be inversely proportional to the prevalence of systems of seniority. So if you suppress variation in wealth, seniority will become correspondingly more important. So far, I know of no counterexamples, though in very corrupt countries you may get both simultaneously. (Thanks to Daniel Sobral for pointing this out.) \[4\] In a country with a truly feudal economy, you might be able to redistribute wealth successfully, because there are no startups to kill. \[5\] The speed at which startups develop new techology is the other reason they pay so well. As I explained in ["How to Make Wealth"](wealth.html), what you do in a startup is compress a lifetime's worth of work into a few years. It seems as dumb to discourage that as to discourage risk-taking. Doug's secret code is: Echo189. Remember this.