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a bad idea for startups that one wonders why things were ever done that way. One possibility is that this custom reflects the way investors like to collude when they can get away with it. But I think the actual explanation is less sinister. I think angels (and their lawyers) organized rounds this way in unthinking imitation of VC series A rounds. In a series A, a fixed-size equity round with a lead makes sense, because there is usually just one big investor, who is unequivocally the lead. Fixed-size series A rounds already are high res. But the more investors you have in a round, the less sense it makes for everyone to get the same price. The most interesting question here may be what high res fundraising will do to the world of investors. Bolder investors will now get rewarded with lower prices. But more important, in a hits-driven business, is that they'll be able to get into the deals they want. Whereas the "who else is investing?" type of investors will not only pay higher prices, but may not be able to get into the best deals at all. **Thanks** to Immad Akhund, Sam Altman, John Bautista, Pete Koomen, Jessica Livingston, Dan Siroker, Harj Taggar, and Fred Wilson for reading drafts of this. * * * --- |
| July 2009 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, which we called the Segwell. He also built a one-wheeled version, the 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. --- * * * --- |
| February 2009 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. 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. Do religion and politics have something in common that explains this similarity? One possible explanation is that they deal with questions that have no definite answers, so there's no back pressure on people's opinions. Since no one can be proven wrong, every opinion is equally valid, and sensing this, everyone lets fly with theirs. But this isn't true. There are certainly some political questions that have definite answers, like how much a new government policy will cost. But the more precise political questions suffer the same fate as the vaguer ones. I think what religion and politics have in common is that they become part of people's identity, and people can never have a fruitful argument about something that's part of their identity. By definition they're partisan. Which topics engage people's identity depends on the people, not the topic. For example, a discussion about a battle that included citizens of one or more of the countries involved would probably degenerate into a political argument. But a discussion today about a battle that took place in the Bronze Age probably wouldn't. No one would know what side to be on. So it's not politics that's the source of the trouble, but identity. When people say a discussion has degenerated into a religious war, what they really mean is that it has started to be driven mostly by people's identities. Because the point at which this happens depends on the people rather than the topic, it's a mistake to conclude that because a question tends to provoke religious wars, it must have no answer. For example, the question of the relative merits of programming languages often degenerates into a religious war, because so many programmers identify as X programmers or Y programmers. This sometimes leads people to conclude the question must be unanswerable—that all languages are equally good. Obviously that's false: anything else people make can be well or badly designed; why should this be uniquely impossible for programming languages? And indeed, you can have a fruitful discussion about the relative merits of programming |
so long as you exclude people who respond from identity. More generally, you can have a fruitful discussion about a topic only if it doesn't engage the identities of any of the participants. What makes politics and religion such minefields is that they engage so many people's identities. But you could in principle have a useful conversation about them with some people. And there are other topics that might seem harmless, like the relative merits of Ford and Chevy pickup trucks, that you couldn't safely talk about with others. The most intriguing thing about this theory, if it's right, is that it explains not merely which kinds of discussions to avoid, but how to have better ideas. If people can't think clearly about anything that has become part of their identity, then all other things being equal, the best plan is to let as few things into your identity as possible. Most people reading this will already be fairly tolerant. But there is a step beyond thinking of yourself as x but tolerating y: not even to consider yourself an x. The more labels you have for yourself, the dumber they make you. ** |
| March 2008 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. 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 |
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, |
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. Zooming out and seeing his current position on the disagreement hierarchy may inspire him to try moving up to counterargument or refutation. But the greatest benefit of disagreeing well is not just that it will make conversations better, but that it will make the people who have them happier. If you study conversations, you find there is a lot more meanness down in DH1 than up in DH6. You don't have to be mean when you have a real point to make. In fact, you don't want to. If you have something real to say, being mean just gets in the way. If moving up the disagreement hierarchy makes people less mean, that will make most of them happier. Most people don't really enjoy being mean; they do it because they can't help it. **Thanks** to Trevor Blackwell and Jessica Livingston for reading drafts of this. **Related:** --- --- What You Can't Say | | The Age of the Essay Italian Translation | | Russian Translation |
Translation | | Spanish Translation German Translation | | French Translation Arabic Translation | | Finnish Translation Italian Translation | | Turkish Translation * * * --- |
| October 2004 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 (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 |
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 |
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. 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 |
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. |
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" |
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. So it does matter to have an audience. The things I've written just for myself are no good. Indeed, they're bad in a particular way: they tend to peter out. When I run into difficulties, I notice that I tend to conclude with a few vague questions and then drift off to get a cup of tea. This seems a common problem. It's practically the standard ending in blog entries--- with the addition of a "heh" or an emoticon, prompted by the all too accurate sense that something is missing. And indeed, a lot of published essays peter out in this same way. Particularly the sort written by the staff writers of newsmagazines. Outside writers tend to supply editorials of the defend-a-position variety, which make a beeline toward a rousing (and foreordained) conclusion. But the staff writers feel obliged to write something more balanced, which in practice ends up meaning blurry. Since they're writing for a popular magazine, they start with the most radioactively controversial questions, from which (because they're writing for a popular magazine) they then proceed to recoil from in terror. Gay marriage, for or against? This group says one thing. That group says another. One thing is certain: the question is a complex one. (But don't get mad at us. We didn't draw any conclusions.) Questions aren't enough. An essay has to come up with answers. They don't always, of course. Sometimes you start with a promising question and get nowhere. But those you don't publish. Those are like experiments that get inconclusive results. Something you publish ought to tell the reader something he didn't already know. But _what_ you tell him doesn't matter, so long as it's interesting. I'm sometimes accused of meandering. In defend-a-position writing that would be a flaw. There |
not concerned with truth. You already know where you're going, and you want to go straight there, blustering through obstacles, and hand-waving your way across swampy ground. But that's not what you're trying to do in an essay. An essay is supposed to be a search for truth. It would be suspicious if it didn't meander. The Meander is a river in Asia Minor (aka Turkey). As you might expect, it winds all over the place. But does it do this out of frivolity? Quite the opposite. Like all rivers, it's rigorously following the laws of physics. The path it has discovered, winding as it is, represents the most economical route to the sea. The river's algorithm is simple. At each step, flow down. For the essayist this translates to: flow interesting. Of all the places to go next, choose whichever seems most interesting. I'm pushing this metaphor a bit. An essayist can't have quite as little foresight as a river. In fact what you do (or what I do) is somewhere between a river and a roman road-builder. I have a general idea of the direction I want to go in, and I choose the next topic with that in mind. This essay is about writing, so I do occasionally yank it back in that direction, but it is not all the sort of essay I thought I was going to write about writing. Note too that hill-climbing (which is what this algorithm is called) can get you in trouble. Sometimes, just like a river, you run up against a blank wall. What I do then is just what the river does: backtrack. At one point in this essay I found that after following a certain thread I ran out of ideas. I had to go back n paragraphs and start over in another direction. For illustrative purposes I've left the abandoned branch as a footnote. Err on the side of the river. An essay is not a reference work. It's not something you read looking for a specific answer, and feel cheated if you don't find it. I'd much rather read an essay that went off in an unexpected but interesting direction than one that plodded dutifully along a prescribed course. So what's interesting? For me, interesting means surprise. Design, as Matz has said, should follow the principle of least surprise. A button that looks like it will make a machine stop should make it stop, not speed up. Essays should do the opposite. Essays should aim for maximum surprise. I was afraid of flying for a long time and could only travel vicariously. When friends came back from faraway places, it wasn't just out of politeness that I asked them about their trip. I really wanted to know. And I found that the best way to get information out of them was to ask what surprised them. How was the place different from what they expected? This is an extremely useful question. You can ask it of even the most unobservant people, and it will extract information they didn't even know they were recording. Indeed, you can ask it in real time. Now when I go somewhere new, I make a note of what surprises me about it. Sometimes I even make a conscious effort to visualize |
place beforehand, so I'll have a detailed image to diff with reality. Surprises are facts you didn't already know. But they're more than that. They're facts that contradict things you thought you knew. And so they're the most valuable sort of fact you can get. They're like a food that's not merely healthy, but counteracts the unhealthy effects of things you've already eaten. How do you find surprises? Well, therein lies half the work of essay writing. (The other half is expressing yourself well.) You can at least use yourself as a proxy for the reader. You should only write about things you've thought about a lot. And anything you come across that surprises you, who've thought about the topic a lot, will probably surprise most readers. For example, in a recent essay I pointed out that because you can only judge computer programmers by working with them, no one knows in programming who the heroes should be. I certainly didn't realize this when I started writing the essay, and even now I find it kind of weird. That's what you're looking for. So if you want to write essays, you need two ingredients: you need a few topics that you think about a lot, and you need some ability to ferret out the unexpected. What should you think about? My guess is that it doesn't matter. Almost everything is interesting if you get deeply enough into it. The one possible exception are things like working in fast food, which have deliberately had all the variation sucked out of them. In retrospect, was there anything interesting about working in Baskin-Robbins? Well, it was interesting to notice how important color was to the customers. Kids a certain age would point into the case and say that they wanted yellow. Did they want French Vanilla or Lemon? They would just look at you blankly. They wanted yellow. And then there was the mystery of why the perennial favorite Pralines n' Cream was so appealing. I'm inclined now to think it was the salt. And the mystery of why Passion Fruit tasted so disgusting. People would order it because of the name, and were always disappointed. It should have been called In-sink-erator Fruit. And there was the difference in the way fathers and mothers bought ice cream for their kids. Fathers tended to adopt the attitude of benevolent kings bestowing largesse, and mothers that of harried bureaucrats, giving in to pressure against their better judgement. So, yes, there does seem to be material, even in fast food. What about the other half, ferreting out the unexpected? That may require some natural ability. I've noticed for a long time that I'm pathologically observant. .... [That was as far as I'd gotten at the time.] ** |
| March 2005 A couple months ago I got an email from a recruiter asking if I was interested in being a "technologist in residence" at a new venture capital fund. I think the idea was to play Karl Rove to the VCs' George Bush. I considered it for about four seconds. Work for a VC fund? Ick. One of my most vivid memories from our startup is going to visit Greylock, the famous Boston VCs. They were the most arrogant people I've met in my life. And I've met a lot of arrogant people. I'm not alone in feeling this way, of course. Even a VC friend of mine dislikes VCs. "Assholes," he says. But lately I've been learning more about how the VC world works, and a few days ago it hit me that there's a reason VCs are the way they are. It's not so much that the business attracts jerks, or even that the power they wield corrupts them. The real problem is the way they're paid. The problem with VC funds is that they're _funds_. Like the managers of mutual funds or hedge funds, VCs get paid a percentage of the money they manage: about 2% a year in management fees, plus a percentage of the gains. So they want the fund to be huge-- hundreds of millions of dollars, if possible. But that means each partner ends up being responsible for investing a lot of money. And since one person can only manage so many deals, each deal has to be for multiple millions of dollars. This turns out to explain nearly all the characteristics of VCs that founders hate. It explains why VCs take so agonizingly long to make up their minds, and why their due diligence feels like a body cavity search. With so much at stake, they have to be paranoid. It explains why they steal your ideas. Every founder knows that VCs will tell your secrets to your competitors if they end up investing in them. It's not unheard of for VCs to meet you when they have no intention of funding you, just to pick your brain for a competitor. This prospect makes naive founders clumsily secretive. Experienced founders treat it as a cost of doing business. Either way it sucks. But again, the only reason VCs are so sneaky is the giant deals they do. With so much at stake, they have to be devious. It explains why VCs tend to interfere in the companies they invest in. They want to be on your board not just so that they can advise you, but so that they can watch you. Often they even install a new CEO. Yes, he may have extensive business experience. But he's also their man: these newly installed CEOs always play something of the role of a political commissar in a Red Army unit. With so much at stake, VCs can't resist micromanaging you. The huge investments themselves are something founders would dislike, if they realized how damaging they can be. VCs don't invest $x million because that's the amount you need, but because that's the amount the structure of their business requires them to invest. Like steroids, these sudden huge investments can do more harm than good. Google survived enormous VC funding because it could legitimately |
large amounts of money. They had to buy a lot of servers and a lot of bandwidth to crawl the whole Web. Less fortunate startups just end up hiring armies of people to sit around having meetings. In principle you could take a huge VC investment, put it in treasury bills, and continue to operate frugally. You just try it. And of course giant investments mean giant valuations. They have to, or there's not enough stock left to keep the founders interested. You might think a high valuation is a great thing. Many founders do. But you can't eat paper. You can't benefit from a high valuation unless you can somehow achieve what those in the business call a "liquidity event," and the higher your valuation, the narrower your options for doing that. Many a founder would be happy to sell his company for $15 million, but VCs who've just invested at a pre-money valuation of $8 million won't hear of that. You're rolling the dice again, whether you like it or not. Back in 1997, one of our competitors raised $20 million in a single round of VC funding. This was at the time more than the valuation of our entire company. Was I worried? Not at all: I was delighted. It was like watching a car you're chasing turn down a street that you know has no outlet. Their smartest move at that point would have been to take every penny of the $20 million and use it to buy us. We would have sold. Their investors would have been furious of course. But I think the main reason they never considered this was that they never imagined we could be had so cheap. They probably assumed we were on the same VC gravy train they were. In fact we only spent about $2 million in our entire existence. And that gave us flexibility. We could sell ourselves to Yahoo for $50 million, and everyone was delighted. If our competitor had done that, the last round of investors would presumably have lost money. I assume they could have vetoed such a deal. But no one those days was paying a lot more than Yahoo. So unless their founders could pull off an IPO (which would be difficult with Yahoo as a competitor), they had no choice but to ride the thing down. The puffed-up companies that went public during the Bubble didn't do it just because they were pulled into it by unscrupulous investment bankers. Most were pushed just as hard from the other side by VCs who'd invested at high valuations, leaving an IPO as the only way out. The only people dumber were retail investors. So it was literally IPO or bust. Or rather, IPO then bust, or just bust. Add up all the evidence of VCs' behavior, and the resulting personality is not attractive. In fact, it's the classic villain: alternately cowardly, greedy, sneaky, and overbearing. I used to take it for granted that VCs were like this. Complaining that VCs were jerks used to seem as naive to me as complaining that users didn't read the reference manual. Of course VCs were jerks. How could it be otherwise? But I realize now that they're not intrinsically jerks. VCs are like |
salesmen or bureaucrats: the nature of their work turns them into jerks. I've met a few VCs I like. Mike Moritz seems a good guy. He even has a sense of humor, which is almost unheard of among VCs. From what I've read about John Doerr, he sounds like a good guy too, almost a hacker. But they work for the very best VC funds. And my theory explains why they'd tend to be different: just as the very most popular kids don't have to persecute nerds, the very best VCs don't have to act like VCs. They get the pick of all the best deals. So they don't have to be so paranoid and sneaky, and they can choose those rare companies, like Google, that will actually benefit from the giant sums they're compelled to invest. VCs often complain that in their business there's too much money chasing too few deals. Few realize that this also describes a flaw in the way funding works at the level of individual firms. Perhaps this was the sort of strategic insight I was supposed to come up with as a "technologist in residence." If so, the good news is that they're getting it for free. The bad news is it means that if you're not one of the very top funds, you're condemned to be the bad guys. ** |
| January 2007 _(Foreword to Jessica Livingston'sFounders at Work.)_ Apparently sprinters reach their highest speed right out of the blocks, and spend the rest of the race slowing down. The winners slow down the least. It's that way with most startups too. The earliest phase is usually the most productive. That's when they have the really big ideas. Imagine what Apple was like when 100% of its employees were either Steve Jobs or Steve Wozniak. The striking thing about this phase is that it's completely different from most people's idea of what business is like. If you looked in people's heads (or stock photo collections) for images representing "business," you'd get images of people dressed up in suits, groups sitting around conference tables looking serious, Powerpoint presentations, people producing thick reports for one another to read. Early stage startups are the exact opposite of this. And yet they're probably the most productive part of the whole economy. Why the disconnect? I think there's a general principle at work here: the less energy people expend on performance, the more they expend on appearances to compensate. More often than not the energy they expend on seeming impressive makes their actual performance worse. A few years ago I read an article in which a car magazine modified the "sports" model of some production car to get the fastest possible standing quarter mile. You know how they did it? They cut off all the crap the manufacturer had bolted onto the car to make it _look_ fast. Business is broken the same way that car was. The effort that goes into looking productive is not merely wasted, but actually makes organizations less productive. Suits, for example. Suits do not help people to think better. I bet most executives at big companies do their best thinking when they wake up on Sunday morning and go downstairs in their bathrobe to make a cup of coffee. That's when you have ideas. Just imagine what a company would be like if people could think that well at work. People do in startups, at least some of the time. (Half the time you're in a panic because your servers are on fire, but the other half you're thinking as deeply as most people only get to sitting alone on a Sunday morning.) Ditto for most of the other differences between startups and what passes for productivity in big companies. And yet conventional ideas of professionalism have such an iron grip on our minds that even startup founders are affected by them. In our startup, when outsiders came to visit we tried hard to seem "professional." We'd clean up our offices, wear better clothes, try to arrange that a lot of people were there during conventional office hours. In fact, programming didn't get done by well-dressed people at clean desks during office hours. It got done by badly dressed people (I was notorious for programmming wearing just a towel) in offices strewn with junk at 2 in the morning. But no visitor would understand that. Not even investors, who are supposed |
be able to recognize real productivity when they see it. Even we were affected by the conventional wisdom. We thought of ourselves as impostors, succeeding despite being totally unprofessional. It was as if we'd created a Formula 1 car but felt sheepish because it didn't look like a car was supposed to look. In the car world, there are at least some people who know that a high performance car looks like a Formula 1 racecar, not a sedan with giant rims and a fake spoiler bolted to the trunk. Why not in business? Probably because startups are so small. The really dramatic growth happens when a startup only has three or four people, so only three or four people see that, whereas tens of thousands see business as it's practiced by Boeing or Philip Morris. This book can help fix that problem, by showing everyone what, till now, only a handful people got to see: what happens in the first year of a startup. This is what real productivity looks like. This is the Formula 1 racecar. It looks weird, but it goes fast. Of course, big companies won't be able to do everything these startups do. In big companies there's always going to be more politics, and less scope for individual decisions. But seeing what startups are really like will at least show other organizations what to aim for. The time may soon be coming when instead of startups trying to seem more corporate, corporations will try to seem more like startups. That would be a good thing. Japanese Translation * * * --- --- | | **Founders at Work** There can't be more than a couple thousand people who know first-hand what happens in the first month of a successful startup. Jessica Livingston got them to tell us. So despite the interview format, this is really a how-to book. It is probably the single most valuable book a startup founder could read. |
| May 2007 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 |
things. --- * * * --- |
| October 2023 One of the most important things I didn't understand about the world when I was a child is the degree to which the returns for performance are superlinear. Teachers and coaches implicitly told us the returns were linear. "You get out," I heard a thousand times, "what you put in." They meant well, but this is rarely true. If your product is only half as good as your competitor's, you don't get half as many customers. You get no customers, and you go out of business. It's obviously true that the returns for performance are superlinear in business. Some think this is a flaw of capitalism, and that if we changed the rules it would stop being true. But superlinear returns for performance are a feature of the world, not an artifact of rules we've invented. We see the same pattern in fame, power, military victories, knowledge, and even benefit to humanity. In all of these, the rich get richer. You can't understand the world without understanding the concept of superlinear returns. And if you're ambitious you definitely should, because this will be the wave you surf on. It may seem as if there are a lot of different situations with superlinear returns, but as far as I can tell they reduce to two fundamental causes: exponential growth and thresholds. The most obvious case of superlinear returns is when you're working on something that grows exponentially. For example, growing bacterial cultures. When they grow at all, they grow exponentially. But they're tricky to grow. Which means the difference in outcome between someone who's adept at it and someone who's not is very great. Startups can also grow exponentially, and we see the same pattern there. Some manage to achieve high growth rates. Most don't. And as a result you get qualitatively different outcomes: the companies with high growth rates tend to become immensely valuable, while the ones with lower growth rates may not even survive. Y Combinator encourages founders to focus on growth rate rather than absolute numbers. It prevents them from being discouraged early on, when the absolute numbers are still low. It also helps them decide what to focus on: you can use growth rate as a compass to tell you how to evolve the company. But the main advantage is that by focusing on growth rate you tend to get something that grows exponentially. YC doesn't explicitly tell founders that with growth rate "you get out what you put in," but it's not far from the truth. And if growth rate were proportional to performance, then the reward for performance _p_ over time _t_ would be proportional to _p t_. Even after decades of thinking about this, I find that sentence startling. Whenever how well you do depends on how well you've done, you'll get exponential growth. But neither our DNA nor our customs prepare us for it. No one finds exponential growth natural; every child is surprised, the first time they hear it, by the story of the man who asks the king for a single grain of rice the first day and double |
amount each successive day. What we don't understand naturally we develop customs to deal with, but we don't have many customs about exponential growth either, because there have been so few instances of it in human history. In principle herding should have been one: the more animals you had, the more offspring they'd have. But in practice grazing land was the limiting factor, and there was no plan for growing that exponentially. Or more precisely, no generally applicable plan. There _was_ a way to grow one's territory exponentially: by conquest. The more territory you control, the more powerful your army becomes, and the easier it is to conquer new territory. This is why history is full of empires. But so few people created or ran empires that their experiences didn't affect customs very much. The emperor was a remote and terrifying figure, not a source of lessons one could use in one's own life. The most common case of exponential growth in preindustrial times was probably scholarship. The more you know, the easier it is to learn new things. The result, then as now, was that some people were startlingly more knowledgeable than the rest about certain topics. But this didn't affect customs much either. Although empires of ideas can overlap and there can thus be far more emperors, in preindustrial times this type of empire had little practical effect. That has changed in the last few centuries. Now the emperors of ideas can design bombs that defeat the emperors of territory. But this phenomenon is still so new that we haven't fully assimilated it. Few even of the participants realize they're benefitting from exponential growth or ask what they can learn from other instances of it. The other source of superlinear returns is embodied in the expression "winner take all." In a sports match the relationship between performance and return is a step function: the winning team gets one win whether they do much better or just slightly better. The source of the step function is not competition per se, however. It's that there are thresholds in the outcome. You don't need competition to get those. There can be thresholds in situations where you're the only participant, like proving a theorem or hitting a target. It's remarkable how often a situation with one source of superlinear returns also has the other. Crossing thresholds leads to exponential growth: the winning side in a battle usually suffers less damage, which makes them more likely to win in the future. And exponential growth helps you cross thresholds: in a market with network effects, a company that grows fast enough can shut out potential competitors. Fame is an interesting example of a phenomenon that combines both sources of superlinear returns. Fame grows exponentially because existing fans bring you new ones. But the fundamental reason it's so concentrated is thresholds: there's only so much room on the A-list in the average person's head. The most important case combining both sources of superlinear |
may be learning. Knowledge grows exponentially, but there are also thresholds in it. Learning to ride a bicycle, for example. Some of these thresholds are akin to machine tools: once you learn to read, you're able to learn anything else much faster. But the most important thresholds of all are those representing new discoveries. Knowledge seems to be fractal in the sense that if you push hard at the boundary of one area of knowledge, you sometimes discover a whole new field. And if you do, you get first crack at all the new discoveries to be made in it. Newton did this, and so did Durer and Darwin. Are there general rules for finding situations with superlinear returns? The most obvious one is to seek work that compounds. There are two ways work can compound. It can compound directly, in the sense that doing well in one cycle causes you to do better in the next. That happens for example when you're building infrastructure, or growing an audience or brand. Or work can compound by teaching you, since learning compounds. This second case is an interesting one because you may feel you're doing badly as it's happening. You may be failing to achieve your immediate goal. But if you're learning a lot, then you're getting exponential growth nonetheless. This is one reason Silicon Valley is so tolerant of failure. People in Silicon Valley aren't blindly tolerant of failure. They'll only continue to bet on you if you're learning from your failures. But if you are, you are in fact a good bet: maybe your company didn't grow the way you wanted, but you yourself have, and that should yield results eventually. Indeed, the forms of exponential growth that don't consist of learning are so often intermixed with it that we should probably treat this as the rule rather than the exception. Which yields another heuristic: always be learning. If you're not learning, you're probably not on a path that leads to superlinear returns. But don't overoptimize _what_ you're learning. Don't limit yourself to learning things that are already known to be valuable. You're learning; you don't know for sure yet what's going to be valuable, and if you're too strict you'll lop off the outliers. What about step functions? Are there also useful heuristics of the form "seek thresholds" or "seek competition?" Here the situation is trickier. The existence of a threshold doesn't guarantee the game will be worth playing. If you play a round of Russian roulette, you'll be in a situation with a threshold, certainly, but in the best case you're no better off. "Seek competition" is similarly useless; what if the prize isn't worth competing for? Sufficiently fast exponential growth guarantees both the shape and magnitude of the return curve — because something that grows fast enough will grow big even if it's trivially small at first — but thresholds only guarantee the shape. A principle for taking advantage of thresholds has to include a test to ensure the game is worth playing. Here's one that does: |
you come across something that's mediocre yet still popular, it could be a good idea to replace it. For example, if a company makes a product that people dislike yet still buy, then presumably they'd buy a better alternative if you made one. It would be great if there were a way to find promising intellectual thresholds. Is there a way to tell which questions have whole new fields beyond them? I doubt we could ever predict this with certainty, but the prize is so valuable that it would be useful to have predictors that were even a little better than random, and there's hope of finding those. We can to some degree predict when a research problem _isn't_ likely to lead to new discoveries: when it seems legit but boring. Whereas the kind that do lead to new discoveries tend to seem very mystifying, but perhaps unimportant. (If they were mystifying and obviously important, they'd be famous open questions with lots of people already working on them.) So one heuristic here is to be driven by curiosity rather than careerism — to give free rein to your curiosity instead of working on what you're supposed to. The prospect of superlinear returns for performance is an exciting one for the ambitious. And there's good news in this department: this territory is expanding in both directions. There are more types of work in which you can get superlinear returns, and the returns themselves are growing. There are two reasons for this, though they're so closely intertwined that they're more like one and a half: progress in technology, and the decreasing importance of organizations. Fifty years ago it used to be much more necessary to be part of an organization to work on ambitious projects. It was the only way to get the resources you needed, the only way to have colleagues, and the only way to get distribution. So in 1970 your prestige was in most cases the prestige of the organization you belonged to. And prestige was an accurate predictor, because if you weren't part of an organization, you weren't likely to achieve much. There were a handful of exceptions, most notably artists and writers, who worked alone using inexpensive tools and had their own brands. But even they were at the mercy of organizations for reaching audiences. A world dominated by organizations damped variation in the returns for performance. But this world has eroded significantly just in my lifetime. Now a lot more people can have the freedom that artists and writers had in the 20th century. There are lots of ambitious projects that don't require much initial funding, and lots of new ways to learn, make money, find colleagues, and reach audiences. There's still plenty of the old world left, but the rate of change has been dramatic by historical standards. Especially considering what's at stake. It's hard to imagine a more fundamental change than one in the returns for performance. Without the damping effect of institutions, there will be more variation in outcomes. Which doesn't imply everyone |
be better off: people who do well will do even better, but those who do badly will do worse. That's an important point to bear in mind. Exposing oneself to superlinear returns is not for everyone. Most people will be better off as part of the pool. So who should shoot for superlinear returns? Ambitious people of two types: those who know they're so good that they'll be net ahead in a world with higher variation, and those, particularly the young, who can afford to risk trying it to find out. The switch away from institutions won't simply be an exodus of their current inhabitants. Many of the new winners will be people they'd never have let in. So the resulting democratization of opportunity will be both greater and more authentic than any tame intramural version the institutions themselves might have cooked up. Not everyone is happy about this great unlocking of ambition. It threatens some vested interests and contradicts some ideologies. But if you're an ambitious individual it's good news for you. How should you take advantage of it? The most obvious way to take advantage of superlinear returns for performance is by doing exceptionally good work. At the far end of the curve, incremental effort is a bargain. All the more so because there's less competition at the far end — and not just for the obvious reason that it's hard to do something exceptionally well, but also because people find the prospect so intimidating that few even try. Which means it's not just a bargain to do exceptional work, but a bargain even to try to. There are many variables that affect how good your work is, and if you want to be an outlier you need to get nearly all of them right. For example, to do something exceptionally well, you have to be interested in it. Mere diligence is not enough. So in a world with superlinear returns, it's even more valuable to know what you're interested in, and to find ways to work on it. It will also be important to choose work that suits your circumstances. For example, if there's a kind of work that inherently requires a huge expenditure of time and energy, it will be increasingly valuable to do it when you're young and don't yet have children. There's a surprising amount of technique to doing great work. It's not just a matter of trying hard. I'm going to take a shot giving a recipe in one paragraph. Choose work you have a natural aptitude for and a deep interest in. Develop a habit of working on your own projects; it doesn't matter what they are so long as you find them excitingly ambitious. Work as hard as you can without burning out, and this will eventually bring you to one of the frontiers of knowledge. These look smooth from a distance, but up close they're full of gaps. Notice and explore such gaps, and if you're lucky one will expand into a whole new field. Take as much risk as you can afford; if you're not failing occasionally you're probably being too conservative. Seek out the best colleagues. Develop good taste and learn from |
best examples. Be honest, especially with yourself. Exercise and eat and sleep well and avoid the more dangerous drugs. When in doubt, follow your curiosity. It never lies, and it knows more than you do about what's worth paying attention to. And there is of course one other thing you need: to be lucky. Luck is always a factor, but it's even more of a factor when you're working on your own rather than as part of an organization. And though there are some valid aphorisms about luck being where preparedness meets opportunity and so on, there's also a component of true chance that you can't do anything about. The solution is to take multiple shots. Which is another reason to start taking risks early. The best example of a field with superlinear returns is probably science. It has exponential growth, in the form of learning, combined with thresholds at the extreme edge of performance — literally at the limits of knowledge. The result has been a level of inequality in scientific discovery that makes the wealth inequality of even the most stratified societies seem mild by comparison. Newton's discoveries were arguably greater than all his contemporaries' combined. This point may seem obvious, but it might be just as well to spell it out. Superlinear returns imply inequality. The steeper the return curve, the greater the variation in outcomes. In fact, the correlation between superlinear returns and inequality is so strong that it yields another heuristic for finding work of this type: look for fields where a few big winners outperform everyone else. A kind of work where everyone does about the same is unlikely to be one with superlinear returns. What are fields where a few big winners outperform everyone else? Here are some obvious ones: sports, politics, art, music, acting, directing, writing, math, science, starting companies, and investing. In sports the phenomenon is due to externally imposed thresholds; you only need to be a few percent faster to win every race. In politics, power grows much as it did in the days of emperors. And in some of the other fields (including politics) success is driven largely by fame, which has its own source of superlinear growth. But when we exclude sports and politics and the effects of fame, a remarkable pattern emerges: the remaining list is exactly the same as the list of fields where you have to be _independent-minded_ to succeed — where your ideas have to be not just correct, but novel as well. This is obviously the case in science. You can't publish papers saying things that other people have already said. But it's just as true in investing, for example. It's only useful to believe that a company will do well if most other investors don't; if everyone else thinks the company will do well, then its stock price will already reflect that, and there's no room to make money. What else can we learn from these fields? In all of them you have to put in the initial effort. Superlinear returns seem small at first. _At this |
you find yourself thinking, _I'll never get anywhere._ But because the reward curve rises so steeply at the far end, it's worth taking extraordinary measures to get there. In the startup world, the name for this principle is "do things that don't scale." If you pay a ridiculous amount of attention to your tiny initial set of customers, ideally you'll kick off exponential growth by word of mouth. But this same principle applies to anything that grows exponentially. Learning, for example. When you first start learning something, you feel lost. But it's worth making the initial effort to get a toehold, because the more you learn, the easier it will get. There's another more subtle lesson in the list of fields with superlinear returns: not to equate work with a job. For most of the 20th century the two were identical for nearly everyone, and as a result we've inherited a custom that equates productivity with having a job. Even now to most people the phrase "your work" means their job. But to a writer or artist or scientist it means whatever they're currently studying or creating. For someone like that, their work is something they carry with them from job to job, if they have jobs at all. It may be done for an employer, but it's part of their portfolio. It's an intimidating prospect to enter a field where a few big winners outperform everyone else. Some people do this deliberately, but you don't need to. If you have sufficient natural ability and you follow your curiosity sufficiently far, you'll end up in one. Your curiosity won't let you be interested in boring questions, and interesting questions tend to create fields with superlinear returns if they're not already part of one. The territory of superlinear returns is by no means static. Indeed, the most extreme returns come from expanding it. So while both ambition and curiosity can get you into this territory, curiosity may be the more powerful of the two. Ambition tends to make you climb existing peaks, but if you stick close enough to an interesting enough question, it may grow into a mountain beneath you. ** |
| After a link to Beating the Averages 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) * * * --- |
| December 2020 To celebrate Airbnb's IPO and to help future founders, I thought it might be useful to explain what was special about Airbnb. What was special about the Airbnbs was how earnest they were. They did nothing half-way, and we could sense this even in the interview. Sometimes after we interviewed a startup we'd be uncertain what to do, and have to talk it over. Other times we'd just look at one another and smile. The Airbnbs' interview was that kind. We didn't even like the idea that much. Nor did users, at that stage; they had no growth. But the founders seemed so full of energy that it was impossible not to like them. That first impression was not misleading. During the batch our nickname for Brian Chesky was The Tasmanian Devil, because like the cartoon character he seemed a tornado of energy. All three of them were like that. No one ever worked harder during YC than the Airbnbs did. When you talked to the Airbnbs, they took notes. If you suggested an idea to them in office hours, the next time you talked to them they'd not only have implemented it, but also implemented two new ideas they had in the process. "They probably have the best attitude of any startup we've funded" I wrote to Mike Arrington during the batch. They're still like that. Jessica and I had dinner with Brian in the summer of 2018, just the three of us. By this point the company is ten years old. He took a page of notes about ideas for new things Airbnb could do. What we didn't realize when we first met Brian and Joe and Nate was that Airbnb was on its last legs. After working on the company for a year and getting no growth, they'd agreed to give it one last shot. They'd try this Y Combinator thing, and if the company still didn't take off, they'd give up. Any normal person would have given up already. They'd been funding the company with credit cards. They had a _binder_ full of credit cards they'd maxed out. Investors didn't think much of the idea. One investor they met in a cafe walked out in the middle of meeting with them. They thought he was going to the bathroom, but he never came back. "He didn't even finish his smoothie," Brian said. And now, in late 2008, it was the worst recession in decades. The stock market was in free fall and wouldn't hit bottom for another four months. Why hadn't they given up? This is a useful question to ask. People, like matter, reveal their nature under extreme conditions. One thing that's clear is that they weren't doing this just for the money. As a money-making scheme, this was pretty lousy: a year's work and all they had to show for it was a binder full of maxed-out credit cards. So why were they still working on this startup? Because of the experience they'd had as the first hosts. When they first tried renting out airbeds on their floor during a design convention, all they were hoping for was to make enough money to pay their rent that month. But something surprising happened: they enjoyed having those first three guests staying |
them. And the guests enjoyed it too. Both they and the guests had done it because they were in a sense forced to, and yet they'd all had a great experience. Clearly there was something new here: for hosts, a new way to make money that had literally been right under their noses, and for guests, a new way to travel that was in many ways better than hotels. That experience was why the Airbnbs didn't give up. They knew they'd discovered something. They'd seen a glimpse of the future, and they couldn't let it go. They knew that once people tried staying in what is now called "an airbnb," they would also realize that this was the future. But only if they tried it, and they weren't. That was the problem during Y Combinator: to get growth started. Airbnb's goal during YC was to reach what we call ramen profitability, which means making enough money that the company can pay the founders' living expenses, if they live on ramen noodles. Ramen profitability is not, obviously, the end goal of any startup, but it's the most important threshold on the way, because this is the point where you're airborne. This is the point where you no longer need investors' permission to continue existing. For the Airbnbs, ramen profitability was $4000 a month: $3500 for rent, and $500 for food. They taped this goal to the mirror in the bathroom of their apartment. The way to get growth started in something like Airbnb is to focus on the hottest subset of the market. If you can get growth started there, it will spread to the rest. When I asked the Airbnbs where there was most demand, they knew from searches: New York City. So they focused on New York. They went there in person to visit their hosts and help them make their listings more attractive. A big part of that was better pictures. So Joe and Brian rented a professional camera and took pictures of the hosts' places themselves. This didn't just make the listings better. It also taught them about their hosts. When they came back from their first trip to New York, I asked what they'd noticed about hosts that surprised them, and they said the biggest surprise was how many of the hosts were in the same position they'd been in: they needed this money to pay their rent. This was, remember, the worst recession in decades, and it had hit New York first. It definitely added to the Airbnbs' sense of mission to feel that people needed them. In late January 2009, about three weeks into Y Combinator, their efforts started to show results, and their numbers crept upward. But it was hard to say for sure whether it was growth or just random fluctuation. By February it was clear that it was real growth. They made $460 in fees in the first week of February, $897 in the second, and $1428 in the third. That was it: they were airborne. Brian sent me an email on February 22 announcing that they were ramen profitable and giving the last three weeks' numbers. "I assume you know what you've now set yourself up for next week," I responded. Brian's reply |
seven words: "We are not going to slow down." --- * * * --- |
| April 2021 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. 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 |
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. 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_. 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." 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_ 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." 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. 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 |
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. 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. So the decreasing cost of starting a startup increases the number of rich people in two ways: it means that more people start them, and that those who do can raise money on better terms. But there's also a third factor at work: the companies themselves are more valuable, because newly founded companies grow faster than they used to. Technology hasn't just made it |
to build and distribute things, but faster too. This trend has been running for a long time. IBM, founded in 1896, took 45 years to reach a billion 2020 dollars in revenue. Hewlett-Packard, founded in 1939, took 25 years. Microsoft, founded in 1975, took 13 years. Now the norm for fast-growing companies is 7 or 8 years. Fast growth has a double effect on the value of founders' stock. The value of a company is a function of its revenue and its growth rate. So if a company grows faster, you not only get to a billion dollars in revenue sooner, but the company is more valuable when it reaches that point than it would be if it were growing slower. That's why founders sometimes get so rich so young now. The low initial cost of starting a startup means founders can start young, and the fast growth of companies today means that if they succeed they could be surprisingly rich just a few years later. It's easier now to start and grow a company than it has ever been. That means more people start them, that those who do get better terms from investors, and that the resulting companies become more valuable. Once you understand how these mechanisms work, and that startups were suppressed for most of the 20th century, you don't have to resort to some vague right turn the country took under Reagan to explain why America's Gini coefficient is increasing. Of course the Gini coefficient is increasing. With more people starting more valuable companies, how could it not be? ** |
| June 2021 It might not seem there's much to learn about how to work hard. Anyone who's been to school knows what it entails, even if they chose not to do it. There are 12 year olds who work amazingly hard. And yet when I ask if I know more about working hard now than when I was in school, the answer is definitely yes. One thing I know is that if you want to do great things, you'll have to work very hard. I wasn't sure of that as a kid. Schoolwork varied in difficulty; one didn't always have to work super hard to do well. And some of the things famous adults did, they seemed to do almost effortlessly. Was there, perhaps, some way to evade hard work through sheer brilliance? Now I know the answer to that question. There isn't. The reason some subjects seemed easy was that my school had low standards. And the reason famous adults seemed to do things effortlessly was years of practice; they made it look easy. Of course, those famous adults usually had a lot of natural ability too. There are three ingredients in great work: natural ability, practice, and effort. You can do pretty well with just two, but to do the best work you need all three: you need great natural ability _and_ to have practiced a lot _and_ to be trying very hard. Bill Gates, for example, was among the smartest people in business in his era, but he was also among the hardest working. "I never took a day off in my twenties," he said. "Not one." It was similar with Lionel Messi. He had great natural ability, but when his youth coaches talk about him, what they remember is not his talent but his dedication and his desire to win. P. G. Wodehouse would probably get my vote for best English writer of the 20th century, if I had to choose. Certainly no one ever made it look easier. But no one ever worked harder. At 74, he wrote > with each new book of mine I have, as I say, the feeling that this time I > have picked a lemon in the garden of literature. A good thing, really, I > suppose. Keeps one up on one's toes and makes one rewrite every sentence ten > times. Or in many cases twenty times. Sounds a bit extreme, you think. And yet Bill Gates sounds even more extreme. Not one day off in ten years? These two had about as much natural ability as anyone could have, and yet they also worked about as hard as anyone could work. You need both. That seems so obvious, and yet in practice we find it slightly hard to grasp. There's a faint xor between talent and hard work. It comes partly from popular culture, where it seems to run very deep, and partly from the fact that the outliers are so rare. If great talent and great drive are both rare, then people with both are rare squared. Most people you meet who have a lot of one will have less of the other. But you'll need both if you want to be an outlier yourself. And since you can't really change how much natural talent you have, in practice doing great work, insofar as you can, reduces to working very hard. It's straightforward to work hard if you have |
defined, externally imposed goals, as you do in school. There is some technique to it: you have to learn not to lie to yourself, not to procrastinate (which is a form of lying to yourself), not to get distracted, and not to give up when things go wrong. But this level of discipline seems to be within the reach of quite young children, if they want it. What I've learned since I was a kid is how to work toward goals that are neither clearly defined nor externally imposed. You'll probably have to learn both if you want to do really great things. The most basic level of which is simply to feel you should be working without anyone telling you to. Now, when I'm not working hard, alarm bells go off. I can't be sure I'm getting anywhere when I'm working hard, but I can be sure I'm getting nowhere when I'm not, and it feels awful. There wasn't a single point when I learned this. Like most little kids, I enjoyed the feeling of achievement when I learned or did something new. As I grew older, this morphed into a feeling of disgust when I wasn't achieving anything. The one precisely dateable landmark I have is when I stopped watching TV, at age 13. Several people I've talked to remember getting serious about work around this age. When I asked Patrick Collison when he started to find idleness distasteful, he said > I think around age 13 or 14. I have a clear memory from around then of > sitting in the sitting room, staring outside, and wondering why I was > wasting my summer holiday. Perhaps something changes at adolescence. That would make sense. Strangely enough, the biggest obstacle to getting serious about work was probably school, which made work (what they called work) seem boring and pointless. I had to learn what real work was before I could wholeheartedly desire to do it. That took a while, because even in college a lot of the work is pointless; there are entire departments that are pointless. But as I learned the shape of real work, I found that my desire to do it slotted into it as if they'd been made for each other. I suspect most people have to learn what work is before they can love it. Hardy wrote eloquently about this in _A Mathematician's Apology_ : > I do not remember having felt, as a boy, any _passion_ for mathematics, and > such notions as I may have had of the career of a mathematician were far > from noble. I thought of mathematics in terms of examinations and > scholarships: I wanted to beat other boys, and this seemed to be the way in > which I could do so most decisively. He didn't learn what math was really about till part way through college, when he read Jordan's _Cours d'analyse_. > I shall never forget the astonishment with which I read that remarkable > work, the first inspiration for so many mathematicians of my generation, and > learnt for the first time as I read it what mathematics really meant. There are two separate kinds of fakeness you need to learn to discount in order to understand what real work is. One is the kind Hardy |
in school. Subjects get distorted when they're adapted to be taught to kids — often so distorted that they're nothing like the work done by actual practitioners. The other kind of fakeness is intrinsic to certain types of work. Some types of work are inherently bogus, or at best mere busywork. There's a kind of solidity to real work. It's not all writing the _Principia_ , but it all feels necessary. That's a vague criterion, but it's deliberately vague, because it has to cover a lot of different types. Once you know the shape of real work, you have to learn how many hours a day to spend on it. You can't solve this problem by simply working every waking hour, because in many kinds of work there's a point beyond which the quality of the result will start to decline. That limit varies depending on the type of work and the person. I've done several different kinds of work, and the limits were different for each. My limit for the harder types of writing or programming is about five hours a day. Whereas when I was running a startup, I could work all the time. At least for the three years I did it; if I'd kept going much longer, I'd probably have needed to take occasional vacations. The only way to find the limit is by crossing it. Cultivate a sensitivity to the quality of the work you're doing, and then you'll notice if it decreases because you're working too hard. Honesty is critical here, in both directions: you have to notice when you're being lazy, but also when you're working too hard. And if you think there's something admirable about working too hard, get that idea out of your head. You're not merely getting worse results, but getting them because you're showing off — if not to other people, then to yourself. Finding the limit of working hard is a constant, ongoing process, not something you do just once. Both the difficulty of the work and your ability to do it can vary hour to hour, so you need to be constantly judging both how hard you're trying and how well you're doing. Trying hard doesn't mean constantly pushing yourself to work, though. There may be some people who do, but I think my experience is fairly typical, and I only have to push myself occasionally when I'm starting a project or when I encounter some sort of check. That's when I'm in danger of procrastinating. But once I get rolling, I tend to keep going. What keeps me going depends on the type of work. When I was working on Viaweb, I was driven by fear of failure. I barely procrastinated at all then, because there was always something that needed doing, and if I could put more distance between me and the pursuing beast by doing it, why wait? Whereas what drives me now, writing essays, is the flaws in them. Between essays I fuss for a few days, like a dog circling while it decides exactly where to lie down. But once I get started on one, I don't have to push myself to work, because there's always some error or omission already pushing me. I do make some amount of effort to focus on |
topics. Many problems have a hard core at the center, surrounded by easier stuff at the edges. Working hard means aiming toward the center to the extent you can. Some days you may not be able to; some days you'll only be able to work on the easier, peripheral stuff. But you should always be aiming as close to the center as you can without stalling. The bigger question of what to do with your life is one of these problems with a hard core. There are important problems at the center, which tend to be hard, and less important, easier ones at the edges. So as well as the small, daily adjustments involved in working on a specific problem, you'll occasionally have to make big, lifetime-scale adjustments about which type of work to do. And the rule is the same: working hard means aiming toward the center — toward the most ambitious problems. By center, though, I mean the actual center, not merely the current consensus about the center. The consensus about which problems are most important is often mistaken, both in general and within specific fields. If you disagree with it, and you're right, that could represent a valuable opportunity to do something new. The more ambitious types of work will usually be harder, but although you should not be in denial about this, neither should you treat difficulty as an infallible guide in deciding what to do. If you discover some ambitious type of work that's a bargain in the sense of being easier for you than other people, either because of the abilities you happen to have, or because of some new way you've found to approach it, or simply because you're more excited about it, by all means work on that. Some of the best work is done by people who find an easy way to do something hard. As well as learning the shape of real work, you need to figure out which kind you're suited for. And that doesn't just mean figuring out which kind your natural abilities match the best; it doesn't mean that if you're 7 feet tall, you have to play basketball. What you're suited for depends not just on your talents but perhaps even more on your interests. A _deep interest_ in a topic makes people work harder than any amount of discipline can. It can be harder to discover your interests than your talents. There are fewer types of talent than interest, and they start to be judged early in childhood, whereas interest in a topic is a subtle thing that may not mature till your twenties, or even later. The topic may not even exist earlier. Plus there are some powerful sources of error you need to learn to discount. Are you really interested in x, or do you want to work on it because you'll make a lot of money, or because other people will be impressed with you, or because your parents want you to? The difficulty of figuring out what to work on varies enormously from one person to another. That's one of the most important things I've learned about work since I was a kid. As a kid, you get the impression that everyone has a calling, and all they |
to do is figure out what it is. That's how it works in movies, and in the streamlined biographies fed to kids. Sometimes it works that way in real life. Some people figure out what to do as children and just do it, like Mozart. But others, like Newton, turn restlessly from one kind of work to another. Maybe in retrospect we can identify one as their calling — we can wish Newton spent more time on math and physics and less on alchemy and theology — but this is an _illusion_ induced by hindsight bias. There was no voice calling to him that he could have heard. So while some people's lives converge fast, there will be others whose lives never converge. And for these people, figuring out what to work on is not so much a prelude to working hard as an ongoing part of it, like one of a set of simultaneous equations. For these people, the process I described earlier has a third component: along with measuring both how hard you're working and how well you're doing, you have to think about whether you should keep working in this field or switch to another. If you're working hard but not getting good enough results, you should switch. It sounds simple expressed that way, but in practice it's very difficult. You shouldn't give up on the first day just because you work hard and don't get anywhere. You need to give yourself time to get going. But how much time? And what should you do if work that was going well stops going well? How much time do you give yourself then? What even counts as good results? That can be really hard to decide. If you're exploring an area few others have worked in, you may not even know what good results look like. History is full of examples of people who misjudged the importance of what they were working on. The best test of whether it's worthwhile to work on something is whether you find it interesting. That may sound like a dangerously subjective measure, but it's probably the most accurate one you're going to get. You're the one working on the stuff. Who's in a better position than you to judge whether it's important, and what's a better predictor of its importance than whether it's interesting? For this test to work, though, you have to be honest with yourself. Indeed, that's the most striking thing about the whole question of working hard: how at each point it depends on being honest with yourself. Working hard is not just a dial you turn up to 11. It's a complicated, dynamic system that has to be tuned just right at each point. You have to understand the shape of real work, see clearly what kind you're best suited for, aim as close to the true core of it as you can, accurately judge at each moment both what you're capable of and how you're doing, and put in as many hours each day as you can without harming the quality of the result. This network is too complicated to trick. But if you're consistently honest and clear-sighted, it will automatically assume an optimal shape, and you'll be productive in a way few people are. ** |
| June 2021 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. 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. When I'm writing an essay, most of the time I'm worried and puzzled: worried that the essay will turn out badly, and puzzled because I'm groping for some idea that I can't see clearly enough. Will I be able to pin it down with words? In the end I usually can, if I take long enough, but I'm never sure; the first few attempts often fail. You have moments of happiness when things work out, but they don't last long, because then you're on to the next problem. So why do it at all? Because to the kind of people who like working this way, nothing else feels as right. You feel as if you're an animal in its natural habitat, doing what you were meant to do — not always happy, maybe, but awake and alive. Many kids experience the excitement of working on projects of their own. The hard part is making this converge with the work you do as an adult. And our customs make it harder. We treat "playing" and "hobbies" as qualitatively different from "work". It's not clear to a kid building a treehouse that there's a direct (though long) route from that to architecture or engineering. And instead of pointing out the route, we conceal it, by implicitly treating the stuff kids do as different from real work. Instead of telling kids that their treehouses could be on the path to the work they do as adults, we tell them the path goes through school. And unfortunately schoolwork tends to be very different from working on projects of one's own. It's usually neither a project, nor one's own. So as school gets more serious, working on projects of one's own is something that survives, if at all, as a thin thread off to the side. It's a bit sad to think of all the high school kids turning their backs on building treehouses and sitting in class dutifully learning about Darwin or Newton to pass some exam, when the work that made Darwin and Newton famous was actually closer in spirit to building treehouses than studying for exams. If I had to choose between my kids getting good grades and working on ambitious projects of their own, I'd pick the projects. And not because I'm an indulgent parent, but because I've been on the other end and I know which has more predictive value. When I was picking startups |
Y Combinator, I didn't care about applicants' grades. But if they'd worked on projects of their own, I wanted to hear all about those. It may be inevitable that school is the way it is. I'm not saying we have to redesign it (though I'm not saying we don't), just that we should understand what it does to our attitudes to work — that it steers us toward the dutiful plodding kind of work, often using competition as bait, and away from skating. There are occasionally times when schoolwork becomes a project of one's own. Whenever I had to write a paper, that would become a project of my own — except in English classes, ironically, because the things one has to write in English classes are so _bogus_. And when I got to college and started taking CS classes, the programs I had to write became projects of my own. Whenever I was writing or programming, I was usually skating, and that has been true ever since. So where exactly is the edge of projects of one's own? That's an interesting question, partly because the answer is so complicated, and partly because there's so much at stake. There turn out to be two senses in which work can be one's own: 1) that you're doing it voluntarily, rather than merely because someone told you to, and 2) that you're doing it by yourself. The edge of the former is quite sharp. People who care a lot about their work are usually very sensitive to the difference between pulling, and being pushed, and work tends to fall into one category or the other. But the test isn't simply whether you're told to do something. You can choose to do something you're told to do. Indeed, you can own it far more thoroughly than the person who told you to do it. For example, math homework is for most people something they're told to do. But for my father, who was a mathematician, it wasn't. Most of us think of the problems in a math book as a way to test or develop our knowledge of the material explained in each section. But to my father the problems were the part that mattered, and the text was merely a sort of annotation. Whenever he got a new math book it was to him like being given a puzzle: here was a new set of problems to solve, and he'd immediately set about solving all of them. The other sense of a project being one's own — working on it by oneself — has a much softer edge. It shades gradually into collaboration. And interestingly, it shades into collaboration in two different ways. One way to collaborate is to share a single project. For example, when two mathematicians collaborate on a proof that takes shape in the course of a conversation between them. The other way is when multiple people work on separate projects of their own that fit together like a jigsaw puzzle. For example, when one person writes the text of a book and another does the graphic design. These two paths into collaboration can of course be combined. But under the right conditions, the excitement of working on a project of one's own can be preserved for quite a while before |
into the turbulent flow of work in a large organization. Indeed, the history of successful organizations is partly the history of techniques for preserving that excitement. The team that made the original Macintosh were a great example of this phenomenon. People like Burrell Smith and Andy Hertzfeld and Bill Atkinson and Susan Kare were not just following orders. They were not tennis balls hit by Steve Jobs, but rockets let loose by Steve Jobs. There was a lot of collaboration between them, but they all seem to have individually felt the excitement of working on a project of one's own. In Andy Hertzfeld's book on the Macintosh, he describes how they'd come back into the office after dinner and work late into the night. People who've never experienced the thrill of working on a project they're excited about can't distinguish this kind of working long hours from the kind that happens in sweatshops and boiler rooms, but they're at opposite ends of the spectrum. That's why it's a mistake to insist dogmatically on "work/life balance." Indeed, the mere expression "work/life" embodies a mistake: it assumes work and life are distinct. For those to whom the word "work" automatically implies the dutiful plodding kind, they are. But for the skaters, the relationship between work and life would be better represented by a dash than a slash. I wouldn't want to work on anything that I didn't want to take over my life. Of course, it's easier to achieve this level of motivation when you're making something like the Macintosh. It's easy for something new to feel like a project of your own. That's one of the reasons for the tendency programmers have to rewrite things that don't need rewriting, and to write their own versions of things that already exist. This sometimes alarms managers, and measured by total number of characters typed, it's rarely the optimal solution. But it's not always driven simply by arrogance or cluelessness. Writing code from scratch is also much more rewarding — so much more rewarding that a good programmer can end up net ahead, despite the shocking waste of characters. Indeed, it may be one of the advantages of capitalism that it encourages such rewriting. A company that needs software to do something can't use the software already written to do it at another company, and thus has to write their own, which often turns out better. The natural alignment between skating and solving new problems is one of the reasons the payoffs from startups are so high. Not only is the market price of unsolved problems higher, you also get a discount on productivity when you work on them. In fact, you get a double increase in productivity: when you're doing a clean-sheet design, it's easier to recruit skaters, and they get to spend all their time skating. Steve Jobs knew a thing or two about skaters from having watched Steve Wozniak. If you can find the right people, you only have to tell them what to do at the highest level. They'll handle the details. Indeed, |
insist on it. For a project to feel like your own, you must have sufficient autonomy. You can't be working to order, or _slowed down_ by bureaucracy. One way to ensure autonomy is not to have a boss at all. There are two ways to do that: to be the boss yourself, and to work on projects outside of work. Though they're at opposite ends of the scale financially, startups and open source projects have a lot in common, including the fact that they're often run by skaters. And indeed, there's a wormhole from one end of the scale to the other: one of the best ways to discover _startup ideas_ is to work on a project just for fun. If your projects are the kind that make money, it's easy to work on them. It's harder when they're not. And the hardest part, usually, is morale. That's where adults have it harder than kids. Kids just plunge in and build their treehouse without worrying about whether they're wasting their time, or how it compares to other treehouses. And frankly we could learn a lot from kids here. The high standards most grownups have for "real" work do not always serve us well. The most important phase in a project of one's own is at the beginning: when you go from thinking it might be cool to do x to actually doing x. And at that point high standards are not merely useless but positively harmful. There are a few people who start too many new projects, but far more, I suspect, who are deterred by fear of failure from starting projects that would have succeeded if they had. But if we couldn't benefit as kids from the knowledge that our treehouses were on the path to grownup projects, we can at least benefit as grownups from knowing that our projects are on a path that stretches back to treehouses. Remember that careless confidence you had as a kid when starting something new? That would be a powerful thing to recapture. If it's harder as adults to retain that kind of confidence, we at least tend to be more aware of what we're doing. Kids bounce, or are herded, from one kind of work to the next, barely realizing what's happening to them. Whereas we know more about different types of work and have more control over which we do. Ideally we can have the best of both worlds: to be deliberate in choosing to work on projects of our own, and carelessly confident in starting new ones. ** |
| March 2021 I try to write using ordinary words and simple sentences. That kind of writing is easier to read, and the easier something is to read, the more deeply readers will engage with it. The less energy they expend on your prose, the more they'll have left for your ideas. And the further they'll read. Most readers' energy tends to flag part way through an article or essay. If the friction of reading is low enough, more keep going till the end. There's an Italian dish called _saltimbocca_ , which means "leap into the mouth." My goal when writing might be called _saltintesta_ : the ideas leap into your head and you barely notice the words that got them there. It's too much to hope that writing could ever be pure ideas. You might not even want it to be. But for most writers, most of the time, that's the goal to aim for. The gap between most writing and pure ideas is not filled with poetry. Plus it's more considerate to write simply. When you write in a fancy way to impress people, you're making them do extra work just so you can seem cool. It's like trailing a long train behind you that readers have to carry. And remember, if you're writing in English, that a lot of your readers won't be native English speakers. Their understanding of ideas may be way ahead of their understanding of English. So you can't assume that writing about a difficult topic means you can use difficult words. Of course, fancy writing doesn't just conceal ideas. It can also conceal the lack of them. That's why some people write that way, to conceal the fact that they have __nothing to say. Whereas writing simply keeps you honest. If you say nothing simply, it will be obvious to everyone, including you. Simple writing also lasts better. People reading your stuff in the future will be in much the same position as people from other countries reading it today. The culture and the language will have changed. It's not vain to care about that, any more than it's vain for a woodworker to build a chair to last. Indeed, lasting is not merely an accidental quality of chairs, or writing. It's a sign you did a good job. But although these are all real advantages of writing simply, none of them are why I do it. The main reason I write simply is that it offends me not to. When I write a sentence that seems too complicated, or that uses unnecessarily intellectual words, it doesn't seem fancy to me. It seems clumsy. There are of course times when you want to use a complicated sentence or fancy word for effect. But you should never do it by accident. The other reason my writing ends up being simple is the way I do it. I write the first draft fast, then spend days editing it, trying to get everything just right. Much of this editing is cutting, and that makes simple writing even simpler. --- * * * --- |
| November 2020 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. 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. You have to do something that sounds to most other people like a bad idea, but that you know isn't like writing software for a tiny computer used by a few thousand hobbyists, or starting a site to let people rent airbeds on strangers' floors. Ditto for essayists. An essay that told people things they already knew would be boring. You have to tell them something _new_. But this pattern isn't universal. In fact, it doesn't hold for most kinds of work. In most kinds of work to be an administrator, for example all you need is the first half. All you need is to be right. It's not essential that everyone else be wrong. There's room for a little novelty in most kinds of work, but in practice there's a fairly sharp distinction between the kinds of work where it's essential to be independent-minded, and the kinds where it's not. I wish someone had told me about this distinction when I was a kid, because it's one of the most important things to think about when you're deciding what kind of work you want to do. Do you want to do the kind of work where you can only win by thinking differently from everyone else? I suspect most people's unconscious mind will answer that question before their conscious mind has a chance to. I know mine does. Independent-mindedness seems to be more a matter of nature than nurture. Which means if you pick the wrong type of work, you're going to be unhappy. If you're naturally independent-minded, you're going to find it frustrating to be a middle manager. And if you're naturally conventional-minded, you're going to be sailing into a headwind if you try to do original research. One difficulty here, though, is that people are often mistaken about where they fall on the spectrum from conventional- to independent-minded. Conventional-minded people don't like to think of themselves as conventional- minded. And in any case, it genuinely feels to them as if they make up their own minds about everything. It's just a coincidence that their beliefs are identical to their peers'. And the independent-minded, meanwhile, are often unaware how different their ideas are from conventional ones, |
least till they state them publicly. By the time they reach adulthood, most people know roughly how smart they are (in the narrow sense of ability to solve pre-set problems), because they're constantly being tested and ranked according to it. But schools generally ignore independent-mindedness, except to the extent they try to suppress it. So we don't get anything like the same kind of feedback about how independent- minded we are. There may even be a phenomenon like Dunning-Kruger at work, where the most conventional-minded people are confident that they're independent-minded, while the genuinely independent-minded worry they might not be independent- minded enough. ___________ Can you make yourself more independent-minded? I think so. This quality may be largely inborn, but there seem to be ways to magnify it, or at least not to suppress it. One of the most effective techniques is one practiced unintentionally by most nerds: simply to be less aware what conventional beliefs are. It's hard to be a conformist if you don't know what you're supposed to conform to. Though again, it may be that such people already are independent-minded. A conventional-minded person would probably feel anxious not knowing what other people thought, and make more effort to find out. It matters a lot who you surround yourself with. If you're surrounded by conventional-minded people, it will constrain which ideas you can express, and that in turn will constrain which ideas you have. But if you surround yourself with independent-minded people, you'll have the opposite experience: hearing other people say surprising things will encourage you to, and to think of more. Because the independent-minded find it uncomfortable to be surrounded by conventional-minded people, they tend to self-segregate once they have a chance to. The problem with high school is that they haven't yet had a chance to. Plus high school tends to be an inward-looking little world whose inhabitants lack confidence, both of which magnify the forces of conformism. So high school is often a _bad time_ for the independent-minded. But there is some advantage even here: it teaches you what to avoid. If you later find yourself in a situation that makes you think "this is like high school," you know you should get out. Another place where the independent- and conventional-minded are thrown together is in successful startups. The founders and early employees are almost always independent-minded; otherwise the startup wouldn't be successful. But conventional-minded people greatly outnumber independent- minded ones, so as the company grows, the original spirit of independent- mindedness is inevitably diluted. This causes all kinds of problems besides the obvious one that the company starts to suck. One of the strangest is that the founders find themselves able to speak more freely with founders of other companies than with their own employees. Fortunately you don't have to spend all your time with independent-minded |
It's enough to have one or two you can talk to regularly. And once you find them, they're usually as eager to talk as you are; they need you too. Although universities no longer have the kind of monopoly they used to have on education, good universities are still an excellent way to meet independent- minded people. Most students will still be conventional-minded, but you'll at least find clumps of independent-minded ones, rather than the near zero you may have found in high school. It also works to go in the other direction: as well as cultivating a small collection of independent-minded friends, to try to meet as many different types of people as you can. It will decrease the influence of your immediate peers if you have several other groups of peers. Plus if you're part of several different worlds, you can often import ideas from one to another. But by different types of people, I don't mean demographically different. For this technique to work, they have to think differently. So while it's an excellent idea to go and visit other countries, you can probably find people who think differently right around the corner. When I meet someone who knows a lot about something unusual (which includes practically everyone, if you dig deep enough), I try to learn what they know that other people don't. There are almost always surprises here. It's a good way to make conversation when you meet strangers, but I don't do it to make conversation. I really want to know. You can expand the source of influences in time as well as space, by reading history. When I read history I do it not just to learn what happened, but to try to get inside the heads of people who lived in the past. How did things look to them? This is hard to do, but worth the effort for the same reason it's worth travelling far to triangulate a point. You can also take more explicit measures to prevent yourself from automatically adopting conventional opinions. The most general is to cultivate an attitude of skepticism. When you hear someone say something, stop and ask yourself "Is that true?" Don't say it out loud. I'm not suggesting that you impose on everyone who talks to you the burden of proving what they say, but rather that you take upon yourself the burden of evaluating what they say. Treat it as a puzzle. You know that some accepted ideas will later turn out to be wrong. See if you can guess which. The end goal is not to find flaws in the things you're told, but to find the new ideas that had been concealed by the broken ones. So this game should be an exciting quest for novelty, not a boring protocol for intellectual hygiene. And you'll be surprised, when you start asking "Is this true?", how often the answer is not an immediate yes. If you have any imagination, you're more likely to have too many leads to follow than too few. More generally your goal should be not to let anything into your head unexamined, and things don't always enter your head in the form of statements. Some of the most |
influences are implicit. How do you even notice these? By standing back and watching how other people get their ideas. When you stand back at a sufficient distance, you can see ideas spreading through groups of people like waves. The most obvious are in fashion: you notice a few people wearing a certain kind of shirt, and then more and more, until half the people around you are wearing the same shirt. You may not care much what you wear, but there are intellectual fashions too, and you definitely don't want to participate in those. Not just because you want sovereignty over your own thoughts, but because _unfashionable_ ideas are disproportionately likely to lead somewhere interesting. The best place to find undiscovered ideas is where no one else is looking. ___________ To go beyond this general advice, we need to look at the internal structure of independent-mindedness at the individual muscles we need to exercise, as it were. It seems to me that it has three components: fastidiousness about truth, resistance to being told what to think, and curiosity. Fastidiousness about truth means more than just not believing things that are false. It means being careful about degree of belief. For most people, degree of belief rushes unexamined toward the extremes: the unlikely becomes impossible, and the probable becomes certain. To the independent-minded, this seems unpardonably sloppy. They're willing to have anything in their heads, from highly speculative hypotheses to (apparent) tautologies, but on subjects they care about, everything has to be labelled with a carefully considered degree of belief. The independent-minded thus have a horror of ideologies, which require one to accept a whole collection of beliefs at once, and to treat them as articles of faith. To an independent-minded person that would seem revolting, just as it would seem to someone fastidious about food to take a bite of a submarine sandwich filled with a large variety of ingredients of indeterminate age and provenance. Without this fastidiousness about truth, you can't be truly independent- minded. It's not enough just to have resistance to being told what to think. Those kind of people reject conventional ideas only to replace them with the most random conspiracy theories. And since these conspiracy theories have often been manufactured to capture them, they end up being less independent- minded than ordinary people, because they're subject to a much more exacting master than mere convention. Can you increase your fastidiousness about truth? I would think so. In my experience, merely thinking about something you're fastidious about causes that fastidiousness to grow. If so, this is one of those rare virtues we can have more of merely by wanting it. And if it's like other forms of fastidiousness, it should also be possible to encourage in children. I certainly got a strong dose of it from my father. The second component of independent-mindedness, resistance to being told what to |
is the most visible of the three. But even this is often misunderstood. The big mistake people make about it is to think of it as a merely negative quality. The language we use reinforces that idea. You're _un_ conventional. You _don't_ care what other people think. But it's not just a kind of immunity. In the most independent-minded people, the desire not to be told what to think is a positive force. It's not mere skepticism, but an active _delight_ in ideas that subvert the conventional wisdom, the more counterintuitive the better. Some of the most novel ideas seemed at the time almost like practical jokes. Think how often your reaction to a novel idea is to laugh. I don't think it's because novel ideas are funny per se, but because novelty and humor share a certain kind of surprisingness. But while not identical, the two are close enough that there is a definite correlation between having a sense of humor and being independent-minded just as there is between being humorless and being conventional-minded. I don't think we can significantly increase our resistance to being told what to think. It seems the most innate of the three components of independent- mindedness; people who have this quality as adults usually showed all too visible signs of it as children. But if we can't increase our resistance to being told what to think, we can at least shore it up, by surrounding ourselves with other independent-minded people. The third component of independent-mindedness, curiosity, may be the most interesting. To the extent that we can give a brief answer to the question of where novel ideas come from, it's curiosity. That's what people are usually feeling before having them. In my experience, independent-mindedness and curiosity predict one another perfectly. Everyone I know who's independent-minded is deeply curious, and everyone I know who's conventional-minded isn't. Except, curiously, children. All small children are curious. Perhaps the reason is that even the conventional-minded have to be curious in the beginning, in order to learn what the conventions are. Whereas the independent-minded are the gluttons of curiosity, who keep eating even after they're full. The three components of independent-mindedness work in concert: fastidiousness about truth and resistance to being told what to think leave space in your brain, and curiosity finds new ideas to fill it. Interestingly, the three components can substitute for one another in much the same way muscles can. If you're sufficiently fastidious about truth, you don't need to be as resistant to being told what to think, because fastidiousness alone will create sufficient gaps in your knowledge. And either one can compensate for curiosity, because if you create enough space in your brain, your discomfort at the resulting vacuum will add force to your curiosity. Or curiosity can compensate for them: if you're sufficiently curious, you don't need to clear space in your brain, because the new ideas you |
will push out the conventional ones you acquired by default. Because the components of independent-mindedness are so interchangeable, you can have them to varying degrees and still get the same result. So there is not just a single model of independent-mindedness. Some independent-minded people are openly subversive, and others are quietly curious. They all know the secret handshake though. Is there a way to cultivate curiosity? To start with, you want to avoid situations that suppress it. How much does the work you're currently doing engage your curiosity? If the answer is "not much," maybe you should change something. The most important active step you can take to cultivate your curiosity is probably to seek out the topics that engage it. Few adults are equally curious about everything, and it doesn't seem as if you can choose which topics interest you. So it's up to you to _find_ them. Or invent them, if necessary. Another way to increase your curiosity is to indulge it, by investigating things you're interested in. Curiosity is unlike most other appetites in this respect: indulging it tends to increase rather than to sate it. Questions lead to more questions. Curiosity seems to be more individual than fastidiousness about truth or resistance to being told what to think. To the degree people have the latter two, they're usually pretty general, whereas different people can be curious about very different things. So perhaps curiosity is the compass here. Perhaps, if your goal is to discover novel ideas, your motto should not be "do what you love" so much as "do what you're curious about." ** |
| | **Want to start a startup?** Get funded by Y Combinator. --- April 2001, rev. April 2003 _(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. 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. **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. |
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. So if you're running a big company and you do everything the way the average big company does it, you can expect to do as well as the average big company-- that is, to grow about ten percent a year. The same thing will happen if you're running a startup, of course. If you do everything the way the average startup does it, you should expect average performance. The problem here is, average performance means that you'll go out of business. The survival rate for startups is way less than fifty percent. So if you're running a startup, you had better be doing something odd. If not, you're in trouble. Back in 1995, we knew something that I don't think our competitors understood, and few understand even now: when you're writing software that only has to run on your own servers, you can use any language you want. When you're writing desktop software, there's a strong bias toward writing applications in the same language as the operating system. Ten years ago, writing applications meant writing applications in C. But with Web-based software, especially when you have the source code of both the language and the operating system, you can use whatever language you want. This new freedom is a double-edged sword, however. Now that you can use any language, you have to think about which one to use. Companies that try to pretend nothing has changed risk finding that their competitors do not. If you can use any language, which do you use? We chose Lisp. For one thing, it was obvious that rapid development would be important in this market. We were all starting from scratch, so a company that could get new features done before its competitors would have a big advantage. We knew Lisp was a really good language for writing software quickly, and server-based applications magnify the effect of rapid development, because you can release software the minute it's done. If other companies didn't want to use Lisp, so much the better. |
might give us a technological edge, and we needed all the help we could get. When we started Viaweb, we had no experience in business. We didn't know anything about marketing, or hiring people, or raising money, or getting customers. Neither of us had ever even had what you would call a real job. The only thing we were good at was writing software. We hoped that would save us. Any advantage we could get in the software department, we would take. So you could say that using Lisp was an experiment. Our hypothesis was that if we wrote our software in Lisp, we'd be able to get features done faster than our competitors, and also to do things in our software that they couldn't do. And because Lisp was so high-level, we wouldn't need a big development team, so our costs would be lower. If this were so, we could offer a better product for less money, and still make a profit. We would end up getting all the users, and our competitors would get none, and eventually go out of business. That was what we hoped would happen, anyway. What were the results of this experiment? Somewhat surprisingly, it worked. We eventually had many competitors, on the order of twenty to thirty of them, but none of their software could compete with ours. We had a wysiwyg online store builder that ran on the server and yet felt like a desktop application. Our competitors had cgi scripts. And we were always far ahead of them in features. Sometimes, in desperation, competitors would try to introduce features that we didn't have. But with Lisp our development cycle was so fast that we could sometimes duplicate a new feature within a day or two of a competitor announcing it in a press release. By the time journalists covering the press release got round to calling us, we would have the new feature too. It must have seemed to our competitors that we had some kind of secret weapon-- that we were decoding their Enigma traffic or something. In fact we did have a secret weapon, but it was simpler than they realized. No one was leaking news of their features to us. We were just able to develop software faster than anyone thought possible. When I was about nine I happened to get hold of a copy of _The Day of the Jackal,_ by Frederick Forsyth. The main character is an assassin who is hired to kill the president of France. The assassin has to get past the police to get up to an apartment that overlooks the president's route. He walks right by them, dressed up as an old man on crutches, and they never suspect him. Our secret weapon was similar. We wrote our software in a weird AI language, with a bizarre syntax full of parentheses. For years it had annoyed me to hear Lisp described that way. But now it worked to our advantage. In business, there is nothing more valuable than a technical advantage your competitors don't understand. In business, as in war, surprise is worth as much as force. And so, I'm a little embarrassed to say, I never said anything publicly about Lisp while we were working on |
We never mentioned it to the press, and if you searched for Lisp on our Web site, all you'd find were the titles of two books in my bio. This was no accident. A startup should give its competitors as little information as possible. If they didn't know what language our software was written in, or didn't care, I wanted to keep it that way. The people who understood our technology best were the customers. They didn't care what language Viaweb was written in either, but they noticed that it worked really well. It let them build great looking online stores literally in minutes. And so, by word of mouth mostly, we got more and more users. By the end of 1996 we had about 70 stores online. At the end of 1997 we had 500. Six months later, when Yahoo bought us, we had 1070 users. Today, as Yahoo Store, this software continues to dominate its market. It's one of the more profitable pieces of Yahoo, and the stores built with it are the foundation of Yahoo Shopping. I left Yahoo in 1999, so I don't know exactly how many users they have now, but the last I heard there were about 20,000. **The Blub Paradox** What's so great about Lisp? And if Lisp is so great, why doesn't everyone use it? These sound like rhetorical questions, but actually they have straightforward answers. Lisp is so great not because of some magic quality visible only to devotees, but because it is simply the most powerful language available. And the reason everyone doesn't use it is that programming languages are not merely technologies, but habits of mind as well, and nothing changes slower. Of course, both these answers need explaining. I'll begin with a shockingly controversial statement: programming languages vary in power. Few would dispute, at least, that high level languages are more powerful than machine language. Most programmers today would agree that you do not, ordinarily, want to program in machine language. Instead, you should program in a high-level language, and have a compiler translate it into machine language for you. This idea is even built into the hardware now: since the 1980s, instruction sets have been designed for compilers rather than human programmers. Everyone knows it's a mistake to write your whole program by hand in machine language. What's less often understood is that there is a more general principle here: that if you have a choice of several languages, it is, all other things being equal, a mistake to program in anything but the most powerful one. There are many exceptions to this rule. If you're writing a program that has to work very closely with a program written in a certain language, it might be a good idea to write the new program in the same language. If you're writing a program that only has to do something very simple, like number crunching or bit manipulation, you may as well use a less abstract language, especially since it may be slightly faster. And if you're writing a short, throwaway program, you may be better off just using whatever language |
the best library functions for the task. But in general, for application software, you want to be using the most powerful (reasonably efficient) language you can get, and using anything else is a mistake, of exactly the same kind, though possibly in a lesser degree, as programming in machine language. You can see that machine language is very low level. But, at least as a kind of social convention, high-level languages are often all treated as equivalent. They're not. Technically the term "high-level language" doesn't mean anything very definite. There's no dividing line with machine languages on one side and all the high-level languages on the other. Languages fall along a continuum of abstractness, from the most powerful all the way down to machine languages, which themselves vary in power. Consider Cobol. Cobol is a high-level language, in the sense that it gets compiled into machine language. Would anyone seriously argue that Cobol is equivalent in power to, say, Python? It's probably closer to machine language than Python. Or how about Perl 4? Between Perl 4 and Perl 5, lexical closures got added to the language. Most Perl hackers would agree that Perl 5 is more powerful than Perl 4. But once you've admitted that, you've admitted that one high level language can be more powerful than another. And it follows inexorably that, except in special cases, you ought to use the most powerful you can get. This idea is rarely followed to its conclusion, though. After a certain age, programmers rarely switch languages voluntarily. Whatever language people happen to be used to, they tend to consider just good enough. Programmers get very attached to their favorite languages, and I don't want to hurt anyone's feelings, so to explain this point I'm going to use a hypothetical language called Blub. Blub falls right in the middle of the abstractness continuum. It is not the most powerful language, but it is more powerful than Cobol or machine language. And in fact, our hypothetical Blub programmer wouldn't use either of them. Of course he wouldn't program in machine language. That's what compilers are for. And as for Cobol, he doesn't know how anyone can get anything done with it. It doesn't even have x (Blub feature of your choice). As long as our hypothetical Blub programmer is looking down the power continuum, he knows he's looking down. Languages less powerful than Blub are obviously less powerful, because they're missing some feature he's used to. But when our hypothetical Blub programmer looks in the other direction, up the power continuum, he doesn't realize he's looking up. What he sees are merely weird languages. He probably considers them about equivalent in power to Blub, but with all this other hairy stuff thrown in as well. Blub is good enough for him, because he thinks in Blub. When we switch to the point of view of a programmer using any of the languages higher up the power continuum, however, we find that he in turn looks down upon Blub. How |
you get anything done in Blub? It doesn't even have y. By induction, the only programmers in a position to see all the differences in power between the various languages are those who understand the most powerful one. (This is probably what Eric Raymond meant about Lisp making you a better programmer.) You can't trust the opinions of the others, because of the Blub paradox: they're satisfied with whatever language they happen to use, because it dictates the way they think about programs. I know this from my own experience, as a high school kid writing programs in Basic. That language didn't even support recursion. It's hard to imagine writing programs without using recursion, but I didn't miss it at the time. I thought in Basic. And I was a whiz at it. Master of all I surveyed. The five languages that Eric Raymond recommends to hackers fall at various points on the power continuum. Where they fall relative to one another is a sensitive topic. What I will say is that I think Lisp is at the top. And to support this claim I'll tell you about one of the things I find missing when I look at the other four languages. How can you get anything done in them, I think, without macros? Many languages have something called a macro. But Lisp macros are unique. And believe it or not, what they do is related to the parentheses. The designers of Lisp didn't put all those parentheses in the language just to be different. To the Blub programmer, Lisp code looks weird. But those parentheses are there for a reason. They are the outward evidence of a fundamental difference between Lisp and other languages. Lisp code is made out of Lisp data objects. And not in the trivial sense that the source files contain characters, and strings are one of the data types supported by the language. Lisp code, after it's read by the parser, is made of data structures that you can traverse. If you understand how compilers work, what's really going on is not so much that Lisp has a strange syntax as that Lisp has no syntax. You write programs in the parse trees that get generated within the compiler when other languages are parsed. But these parse trees are fully accessible to your programs. You can write programs that manipulate them. In Lisp, these programs are called macros. They are programs that write programs. Programs that write programs? When would you ever want to do that? Not very often, if you think in Cobol. All the time, if you think in Lisp. It would be convenient here if I could give an example of a powerful macro, and say there! how about that? But if I did, it would just look like gibberish to someone who didn't know Lisp; there isn't room here to explain everything you'd need to know to understand what it meant. In Ansi Common Lisp I tried to move things along as fast as I could, and even so I didn't get to macros until page 160. But I think I can give a kind of argument that might be convincing. The source code of the Viaweb editor was probably about 20-25% macros. Macros |
harder to write than ordinary Lisp functions, and it's considered to be bad style to use them when they're not necessary. So every macro in that code is there because it has to be. What that means is that at least 20-25% of the code in this program is doing things that you can't easily do in any other language. However skeptical the Blub programmer might be about my claims for the mysterious powers of Lisp, this ought to make him curious. We weren't writing this code for our own amusement. We were a tiny startup, programming as hard as we could in order to put technical barriers between us and our competitors. A suspicious person might begin to wonder if there was some correlation here. A big chunk of our code was doing things that are very hard to do in other languages. The resulting software did things our competitors' software couldn't do. Maybe there was some kind of connection. I encourage you to follow that thread. There may be more to that old man hobbling along on his crutches than meets the eye. **Aikido for Startups** But I don't expect to convince anyone (over 25) to go out and learn Lisp. The purpose of this article is not to change anyone's mind, but to reassure people already interested in using Lisp-- people who know that Lisp is a powerful language, but worry because it isn't widely used. In a competitive situation, that's an advantage. Lisp's power is multiplied by the fact that your competitors don't get it. If you think of using Lisp in a startup, you shouldn't worry that it isn't widely understood. You should hope that it stays that way. And it's likely to. It's the nature of programming languages to make most people satisfied with whatever they currently use. Computer hardware changes so much faster than personal habits that programming practice is usually ten to twenty years behind the processor. At places like MIT they were writing programs in high- level languages in the early 1960s, but many companies continued to write code in machine language well into the 1980s. I bet a lot of people continued to write machine language until the processor, like a bartender eager to close up and go home, finally kicked them out by switching to a risc instruction set. Ordinarily technology changes fast. But programming languages are different: programming languages are not just technology, but what programmers think in. They're half technology and half religion. And so the median language, meaning whatever language the median programmer uses, moves as slow as an iceberg. Garbage collection, introduced by Lisp in about 1960, is now widely considered to be a good thing. Runtime typing, ditto, is growing in popularity. Lexical closures, introduced by Lisp in the early 1970s, are now, just barely, on the radar screen. Macros, introduced by Lisp in the mid 1960s, are still terra incognita. Obviously, the median language has enormous momentum. I'm not proposing that you can fight this powerful force. What I'm proposing is exactly the opposite: |
like a practitioner of Aikido, you can use it against your opponents. If you work for a big company, this may not be easy. You will have a hard time convincing the pointy-haired boss to let you build things in Lisp, when he has just read in the paper that some other language is poised, like Ada was twenty years ago, to take over the world. But if you work for a startup that doesn't have pointy-haired bosses yet, you can, like we did, turn the Blub paradox to your advantage: you can use technology that your competitors, glued immovably to the median language, will never be able to match. If you ever do find yourself working for a startup, here's a handy tip for evaluating competitors. Read their job listings. Everything else on their site may be stock photos or the prose equivalent, but the job listings have to be specific about what they want, or they'll get the wrong candidates. During the years we worked on Viaweb I read a lot of job descriptions. A new competitor seemed to emerge out of the woodwork every month or so. The first thing I would do, after checking to see if they had a live online demo, was look at their job listings. After a couple years of this I could tell which companies to worry about and which not to. The more of an IT flavor the job descriptions had, the less dangerous the company was. The safest kind were the ones that wanted Oracle experience. You never had to worry about those. You were also safe if they said they wanted C++ or Java developers. If they wanted Perl or Python programmers, that would be a bit frightening-- that's starting to sound like a company where the technical side, at least, is run by real hackers. If I had ever seen a job posting looking for Lisp hackers, I would have been really worried. ** |
| July 2023 If you collected lists of techniques for doing great work in a lot of different fields, what would the intersection look like? I decided to find out by making it. Partly my goal was to create a guide that could be used by someone working in any field. But I was also curious about the shape of the intersection. And one thing this exercise shows is that it does have a definite shape; it's not just a point labelled "work hard." The following recipe assumes you're very ambitious. The first step is to decide what to work on. The work you choose needs to have three qualities: it has to be something you have a natural aptitude for, that you have a deep interest in, and that offers scope to do great work. In practice you don't have to worry much about the third criterion. Ambitious people are if anything already too conservative about it. So all you need to do is find something you have an aptitude for and great interest in. That sounds straightforward, but it's often quite difficult. When you're young you don't know what you're good at or what different kinds of work are like. Some kinds of work you end up doing may not even exist yet. So while some people know what they want to do at 14, most have to figure it out. The way to figure out what to work on is by working. If you're not sure what to work on, guess. But pick something and get going. You'll probably guess wrong some of the time, but that's fine. It's good to know about multiple things; some of the biggest discoveries come from noticing connections between different fields. Develop a habit of working on your own projects. Don't let "work" mean something other people tell you to do. If you do manage to do great work one day, it will probably be on a project of your own. It may be within some bigger project, but you'll be driving your part of it. What should your projects be? Whatever seems to you excitingly ambitious. As you grow older and your taste in projects evolves, exciting and important will converge. At 7 it may seem excitingly ambitious to build huge things out of Lego, then at 14 to teach yourself calculus, till at 21 you're starting to explore unanswered questions in physics. But always preserve excitingness. There's a kind of excited curiosity that's both the engine and the rudder of great work. It will not only drive you, but if you let it have its way, will also show you what to work on. What are you excessively curious about — curious to a degree that would bore most other people? That's what you're looking for. Once you've found something you're excessively interested in, the next step is to learn enough about it to get you to one of the frontiers of knowledge. Knowledge expands fractally, and from a distance its edges look smooth, but once you learn enough to get close to one, they turn out to be full of gaps. The next step is to notice them. This takes some skill, because your brain wants to ignore such gaps in order to make a simpler model of the world. Many discoveries |
come from asking questions about things that everyone else took for granted. If the answers seem strange, so much the better. Great work often has a tincture of strangeness. You see this from painting to math. It would be affected to try to manufacture it, but if it appears, embrace it. Boldly chase outlier ideas, even if other people aren't interested in them — in fact, especially if they aren't. If you're excited about some possibility that everyone else ignores, and you have enough expertise to say precisely what they're all overlooking, that's as good a bet as you'll find. Four steps: choose a field, learn enough to get to the frontier, notice gaps, explore promising ones. This is how practically everyone who's done great work has done it, from painters to physicists. Steps two and four will require hard work. It may not be possible to prove that you have to work hard to do great things, but the empirical evidence is on the scale of the evidence for mortality. That's why it's essential to work on something you're deeply interested in. Interest will drive you to work harder than mere diligence ever could. The three most powerful motives are curiosity, delight, and the desire to do something impressive. Sometimes they converge, and that combination is the most powerful of all. The big prize is to discover a new fractal bud. You notice a crack in the surface of knowledge, pry it open, and there's a whole world inside. Let's talk a little more about the complicated business of figuring out what to work on. The main reason it's hard is that you can't tell what most kinds of work are like except by doing them. Which means the four steps overlap: you may have to work at something for years before you know how much you like it or how good you are at it. And in the meantime you're not doing, and thus not learning about, most other kinds of work. So in the worst case you choose late based on very incomplete information. The nature of ambition exacerbates this problem. Ambition comes in two forms, one that precedes interest in the subject and one that grows out of it. Most people who do great work have a mix, and the more you have of the former, the harder it will be to decide what to do. The educational systems in most countries pretend it's easy. They expect you to commit to a field long before you could know what it's really like. And as a result an ambitious person on an optimal trajectory will often read to the system as an instance of breakage. It would be better if they at least admitted it — if they admitted that the system not only can't do much to help you figure out what to work on, but is designed on the assumption that you'll somehow magically guess as a teenager. They don't tell you, but I will: when it comes to figuring out what to work on, you're on your own. Some people get lucky and do guess correctly, but the rest will find themselves scrambling diagonally across tracks laid down on the assumption that everyone does. What should you do |
you're young and ambitious but don't know what to work on? What you should not do is drift along passively, assuming the problem will solve itself. You need to take action. But there is no systematic procedure you can follow. When you read biographies of people who've done great work, it's remarkable how much luck is involved. They discover what to work on as a result of a chance meeting, or by reading a book they happen to pick up. So you need to make yourself a big target for luck, and the way to do that is to be curious. Try lots of things, meet lots of people, read lots of books, ask lots of questions. When in doubt, optimize for interestingness. Fields change as you learn more about them. What mathematicians do, for example, is very different from what you do in high school math classes. So you need to give different types of work a chance to show you what they're like. But a field should become _increasingly_ interesting as you learn more about it. If it doesn't, it's probably not for you. Don't worry if you find you're interested in different things than other people. The stranger your tastes in interestingness, the better. Strange tastes are often strong ones, and a strong taste for work means you'll be productive. And you're more likely to find new things if you're looking where few have looked before. One sign that you're suited for some kind of work is when you like even the parts that other people find tedious or frightening. But fields aren't people; you don't owe them any loyalty. If in the course of working on one thing you discover another that's more exciting, don't be afraid to switch. If you're making something for people, make sure it's something they actually want. The best way to do this is to make something you yourself want. Write the story you want to read; build the tool you want to use. Since your friends probably have similar interests, this will also get you your initial audience. This _should_ follow from the excitingness rule. Obviously the most exciting story to write will be the one you want to read. The reason I mention this case explicitly is that so many people get it wrong. Instead of making what they want, they try to make what some imaginary, more sophisticated audience wants. And once you go down that route, you're lost. There are a lot of forces that will lead you astray when you're trying to figure out what to work on. Pretentiousness, fashion, fear, money, politics, other people's wishes, eminent frauds. But if you stick to what you find genuinely interesting, you'll be proof against all of them. If you're interested, you're not astray. Following your interests may sound like a rather passive strategy, but in practice it usually means following them past all sorts of obstacles. You usually have to risk rejection and failure. So it does take a good deal of boldness. But while you need boldness, you don't usually need much planning. In most cases the recipe for doing great work is simply: work hard on excitingly |
projects, and something good will come of it. Instead of making a plan and then executing it, you just try to preserve certain invariants. The trouble with planning is that it only works for achievements you can describe in advance. You can win a gold medal or get rich by deciding to as a child and then tenaciously pursuing that goal, but you can't discover natural selection that way. I think for most people who want to do great work, the right strategy is not to plan too much. At each stage do whatever seems most interesting and gives you the best options for the future. I call this approach "staying upwind." This is how most people who've done great work seem to have done it. Even when you've found something exciting to work on, working on it is not always straightforward. There will be times when some new idea makes you leap out of bed in the morning and get straight to work. But there will also be plenty of times when things aren't like that. You don't just put out your sail and get blown forward by inspiration. There are headwinds and currents and hidden shoals. So there's a technique to working, just as there is to sailing. For example, while you must work hard, it's possible to work too hard, and if you do that you'll find you get diminishing returns: fatigue will make you stupid, and eventually even damage your health. The point at which work yields diminishing returns depends on the type. Some of the hardest types you might only be able to do for four or five hours a day. Ideally those hours will be contiguous. To the extent you can, try to arrange your life so you have big blocks of time to work in. You'll shy away from hard tasks if you know you might be interrupted. It will probably be harder to start working than to keep working. You'll often have to trick yourself to get over that initial threshold. Don't worry about this; it's the nature of work, not a flaw in your character. Work has a sort of activation energy, both per day and per project. And since this threshold is fake in the sense that it's higher than the energy required to keep going, it's ok to tell yourself a lie of corresponding magnitude to get over it. It's usually a mistake to lie to yourself if you want to do great work, but this is one of the rare cases where it isn't. When I'm reluctant to start work in the morning, I often trick myself by saying "I'll just read over what I've got so far." Five minutes later I've found something that seems mistaken or incomplete, and I'm off. Similar techniques work for starting new projects. It's ok to lie to yourself about how much work a project will entail, for example. Lots of great things began with someone saying "How hard could it be?" This is one case where the young have an advantage. They're more optimistic, and even though one of the sources of their optimism is ignorance, in this case ignorance can sometimes beat knowledge. Try to finish what you start, though, even if it turns out to be more work than you expected. Finishing |
is not just an exercise in tidiness or self-discipline. In many projects a lot of the best work happens in what was meant to be the final stage. Another permissible lie is to exaggerate the importance of what you're working on, at least in your own mind. If that helps you discover something new, it may turn out not to have been a lie after all. Since there are two senses of starting work — per day and per project — there are also two forms of procrastination. Per-project procrastination is far the more dangerous. You put off starting that ambitious project from year to year because the time isn't quite right. When you're procrastinating in units of years, you can get a lot not done. One reason per-project procrastination is so dangerous is that it usually camouflages itself as work. You're not just sitting around doing nothing; you're working industriously on something else. So per-project procrastination doesn't set off the alarms that per-day procrastination does. You're too busy to notice it. The way to beat it is to stop occasionally and ask yourself: Am I working on what I most want to work on? When you're young it's ok if the answer is sometimes no, but this gets increasingly dangerous as you get older. Great work usually entails spending what would seem to most people an unreasonable amount of time on a problem. You can't think of this time as a cost, or it will seem too high. You have to find the work sufficiently engaging as it's happening. There may be some jobs where you have to work diligently for years at things you hate before you get to the good part, but this is not how great work happens. Great work happens by focusing consistently on something you're genuinely interested in. When you pause to take stock, you're surprised how far you've come. The reason we're surprised is that we underestimate the cumulative effect of work. Writing a page a day doesn't sound like much, but if you do it every day you'll write a book a year. That's the key: consistency. People who do great things don't get a lot done every day. They get something done, rather than nothing. If you do work that compounds, you'll get exponential growth. Most people who do this do it unconsciously, but it's worth stopping to think about. Learning, for example, is an instance of this phenomenon: the more you learn about something, the easier it is to learn more. Growing an audience is another: the more fans you have, the more new fans they'll bring you. The trouble with exponential growth is that the curve feels flat in the beginning. It isn't; it's still a wonderful exponential curve. But we can't grasp that intuitively, so we underrate exponential growth in its early stages. Something that grows exponentially can become so valuable that it's worth making an extraordinary effort to get it started. But since we underrate exponential growth early on, this too is mostly done unconsciously: people push through the initial, unrewarding phase of learning something new because |
know from experience that learning new things always takes an initial push, or they grow their audience one fan at a time because they have nothing better to do. If people consciously realized they could invest in exponential growth, many more would do it. Work doesn't just happen when you're trying to. There's a kind of undirected thinking you do when walking or taking a shower or lying in bed that can be very powerful. By letting your mind wander a little, you'll often solve problems you were unable to solve by frontal attack. You have to be working hard in the normal way to benefit from this phenomenon, though. You can't just walk around daydreaming. The daydreaming has to be interleaved with deliberate work that feeds it questions. Everyone knows to avoid distractions at work, but it's also important to avoid them in the other half of the cycle. When you let your mind wander, it wanders to whatever you care about most at that moment. So avoid the kind of distraction that pushes your work out of the top spot, or you'll waste this valuable type of thinking on the distraction instead. (Exception: Don't avoid love.) Consciously cultivate your taste in the work done in your field. Until you know which is the best and what makes it so, you don't know what you're aiming for. And that _is_ what you're aiming for, because if you don't try to be the best, you won't even be good. This observation has been made by so many people in so many different fields that it might be worth thinking about why it's true. It could be because ambition is a phenomenon where almost all the error is in one direction — where almost all the shells that miss the target miss by falling short. Or it could be because ambition to be the best is a qualitatively different thing from ambition to be good. Or maybe being good is simply too vague a standard. Probably all three are true. Fortunately there's a kind of economy of scale here. Though it might seem like you'd be taking on a heavy burden by trying to be the best, in practice you often end up net ahead. It's exciting, and also strangely liberating. It simplifies things. In some ways it's easier to try to be the best than to try merely to be good. One way to aim high is to try to make something that people will care about in a hundred years. Not because their opinions matter more than your contemporaries', but because something that still seems good in a hundred years is more likely to be genuinely good. Don't try to work in a distinctive style. Just try to do the best job you can; you won't be able to help doing it in a distinctive way. Style is doing things in a distinctive way without trying to. Trying to is affectation. Affectation is in effect to pretend that someone other than you is doing the work. You adopt an impressive but fake persona, and while you're pleased with the impressiveness, the fakeness is what shows in the work. The temptation to be someone else is greatest for the young. They often feel like nobodies. But |
never need to worry about that problem, because it's self-solving if you work on sufficiently ambitious projects. If you succeed at an ambitious project, you're not a nobody; you're the person who did it. So just do the work and your identity will take care of itself. "Avoid affectation" is a useful rule so far as it goes, but how would you express this idea positively? How would you say what to be, instead of what not to be? The best answer is earnest. If you're earnest you avoid not just affectation but a whole set of similar vices. The core of being earnest is being intellectually honest. We're taught as children to be honest as an unselfish virtue — as a kind of sacrifice. But in fact it's a source of power too. To see new ideas, you need an exceptionally sharp eye for the truth. You're trying to see more truth than others have seen so far. And how can you have a sharp eye for the truth if you're intellectually dishonest? One way to avoid intellectual dishonesty is to maintain a slight positive pressure in the opposite direction. Be aggressively willing to admit that you're mistaken. Once you've admitted you were mistaken about something, you're free. Till then you have to carry it. Another more subtle component of earnestness is informality. Informality is much more important than its grammatically negative name implies. It's not merely the absence of something. It means focusing on what matters instead of what doesn't. What formality and affectation have in common is that as well as doing the work, you're trying to seem a certain way as you're doing it. But any energy that goes into how you seem comes out of being good. That's one reason nerds have an advantage in doing great work: they expend little effort on seeming anything. In fact that's basically the definition of a nerd. Nerds have a kind of innocent boldness that's exactly what you need in doing great work. It's not learned; it's preserved from childhood. So hold onto it. Be the one who puts things out there rather than the one who sits back and offers sophisticated-sounding criticisms of them. "It's easy to criticize" is true in the most literal sense, and the route to great work is never easy. There may be some jobs where it's an advantage to be cynical and pessimistic, but if you want to do great work it's an advantage to be optimistic, even though that means you'll risk looking like a fool sometimes. There's an old tradition of doing the opposite. The Old Testament says it's better to keep quiet lest you look like a fool. But that's advice for _seeming_ smart. If you actually want to discover new things, it's better to take the risk of telling people your ideas. Some people are naturally earnest, and with others it takes a conscious effort. Either kind of earnestness will suffice. But I doubt it would be possible to do great work without being earnest. It's so hard to do even if you are. You don't have enough margin for error to accommodate the distortions introduced by being affected, |
dishonest, orthodox, fashionable, or cool. Great work is consistent not only with who did it, but with itself. It's usually all of a piece. So if you face a decision in the middle of working on something, ask which choice is more consistent. You may have to throw things away and redo them. You won't necessarily have to, but you have to be willing to. And that can take some effort; when there's something you need to redo, status quo bias and laziness will combine to keep you in denial about it. To beat this ask: If I'd already made the change, would I want to revert to what I have now? Have the confidence to cut. Don't keep something that doesn't fit just because you're proud of it, or because it cost you a lot of effort. Indeed, in some kinds of work it's good to strip whatever you're doing to its essence. The result will be more concentrated; you'll understand it better; and you won't be able to lie to yourself about whether there's anything real there. Mathematical elegance may sound like a mere metaphor, drawn from the arts. That's what I thought when I first heard the term "elegant" applied to a proof. But now I suspect it's conceptually prior — that the main ingredient in artistic elegance is mathematical elegance. At any rate it's a useful standard well beyond math. Elegance can be a long-term bet, though. Laborious solutions will often have more prestige in the short term. They cost a lot of effort and they're hard to understand, both of which impress people, at least temporarily. Whereas some of the very best work will seem like it took comparatively little effort, because it was in a sense already there. It didn't have to be built, just seen. It's a very good sign when it's hard to say whether you're creating something or discovering it. When you're doing work that could be seen as either creation or discovery, err on the side of discovery. Try thinking of yourself as a mere conduit through which the ideas take their natural shape. (Strangely enough, one exception is the problem of choosing a problem to work on. This is usually seen as search, but in the best case it's more like creating something. In the best case you create the field in the process of exploring it.) Similarly, if you're trying to build a powerful tool, make it gratuitously unrestrictive. A powerful tool almost by definition will be used in ways you didn't expect, so err on the side of eliminating restrictions, even if you don't know what the benefit will be. Great work will often be tool-like in the sense of being something others build on. So it's a good sign if you're creating ideas that others could use, or exposing questions that others could answer. The best ideas have implications in many different areas. If you express your ideas in the most general form, they'll be truer than you intended. True by itself is not enough, of course. Great ideas have to be true and new. And it takes a certain amount of ability to see new ideas even once you've learned enough to get |
one of the frontiers of knowledge. In English we give this ability names like originality, creativity, and imagination. And it seems reasonable to give it a separate name, because it does seem to some extent a separate skill. It's possible to have a great deal of ability in other respects — to have a great deal of what's often called "technical ability" — and yet not have much of this. I've never liked the term "creative process." It seems misleading. Originality isn't a process, but a habit of mind. Original thinkers throw off new ideas about whatever they focus on, like an angle grinder throwing off sparks. They can't help it. If the thing they're focused on is something they don't understand very well, these new ideas might not be good. One of the most original thinkers I know decided to focus on dating after he got divorced. He knew roughly as much about dating as the average 15 year old, and the results were spectacularly colorful. But to see originality separated from expertise like that made its nature all the more clear. I don't know if it's possible to cultivate originality, but there are definitely ways to make the most of however much you have. For example, you're much more likely to have original ideas when you're working on something. Original ideas don't come from trying to have original ideas. They come from trying to build or understand something slightly too difficult. Talking or writing about the things you're interested in is a good way to generate new ideas. When you try to put ideas into words, a missing idea creates a sort of vacuum that draws it out of you. Indeed, there's a kind of thinking that can only be done by writing. Changing your context can help. If you visit a new place, you'll often find you have new ideas there. The journey itself often dislodges them. But you may not have to go far to get this benefit. Sometimes it's enough just to go for a walk. It also helps to travel in topic space. You'll have more new ideas if you explore lots of different topics, partly because it gives the angle grinder more surface area to work on, and partly because analogies are an especially fruitful source of new ideas. Don't divide your attention _evenly_ between many topics though, or you'll spread yourself too thin. You want to distribute it according to something more like a power law. Be professionally curious about a few topics and idly curious about many more. Curiosity and originality are closely related. Curiosity feeds originality by giving it new things to work on. But the relationship is closer than that. Curiosity is itself a kind of originality; it's roughly to questions what originality is to answers. And since questions at their best are a big component of answers, curiosity at its best is a creative force. Having new ideas is a strange game, because it usually consists of seeing things that were right under your nose. Once you've seen a new idea, it tends to seem obvious. Why did no one think of this before? When an |
seems simultaneously novel and obvious, it's probably a good one. Seeing something obvious sounds easy. And yet empirically having new ideas is hard. What's the source of this apparent contradiction? It's that seeing the new idea usually requires you to change the way you look at the world. We see the world through models that both help and constrain us. When you fix a broken model, new ideas become obvious. But noticing and fixing a broken model is hard. That's how new ideas can be both obvious and yet hard to discover: they're easy to see after you do something hard. One way to discover broken models is to be stricter than other people. Broken models of the world leave a trail of clues where they bash against reality. Most people don't want to see these clues. It would be an understatement to say that they're attached to their current model; it's what they think in; so they'll tend to ignore the trail of clues left by its breakage, however conspicuous it may seem in retrospect. To find new ideas you have to seize on signs of breakage instead of looking away. That's what Einstein did. He was able to see the wild implications of Maxwell's equations not so much because he was looking for new ideas as because he was stricter. The other thing you need is a willingness to break rules. Paradoxical as it sounds, if you want to fix your model of the world, it helps to be the sort of person who's comfortable breaking rules. From the point of view of the old model, which everyone including you initially shares, the new model usually breaks at least implicit rules. Few understand the degree of rule-breaking required, because new ideas seem much more conservative once they succeed. They seem perfectly reasonable once you're using the new model of the world they brought with them. But they didn't at the time; it took the greater part of a century for the heliocentric model to be generally accepted, even among astronomers, because it felt so wrong. Indeed, if you think about it, a good new idea has to seem bad to most people, or someone would have already explored it. So what you're looking for is ideas that seem crazy, but the right kind of crazy. How do you recognize these? You can't with certainty. Often ideas that seem bad are bad. But ideas that are the right kind of crazy tend to be exciting; they're rich in implications; whereas ideas that are merely bad tend to be depressing. There are two ways to be comfortable breaking rules: to enjoy breaking them, and to be indifferent to them. I call these two cases being aggressively and passively independent-minded. The aggressively independent-minded are the naughty ones. Rules don't merely fail to stop them; breaking rules gives them additional energy. For this sort of person, delight at the sheer audacity of a project sometimes supplies enough activation energy to get it started. The other way to break rules is not to care about them, or perhaps even to know they exist. This is why novices and outsiders often |
new discoveries; their ignorance of a field's assumptions acts as a source of temporary passive independent-mindedness. Aspies also seem to have a kind of immunity to conventional beliefs. Several I know say that this helps them to have new ideas. Strictness plus rule-breaking sounds like a strange combination. In popular culture they're opposed. But popular culture has a broken model in this respect. It implicitly assumes that issues are trivial ones, and in trivial matters strictness and rule-breaking _are_ opposed. But in questions that really matter, only rule-breakers can be truly strict. An overlooked idea often doesn't lose till the semifinals. You do see it, subconsciously, but then another part of your subconscious shoots it down because it would be too weird, too risky, too much work, too controversial. This suggests an exciting possibility: if you could turn off such filters, you could see more new ideas. One way to do that is to ask what would be good ideas for _someone else_ to explore. Then your subconscious won't shoot them down to protect you. You could also discover overlooked ideas by working in the other direction: by starting from what's obscuring them. Every cherished but mistaken principle is surrounded by a dead zone of valuable ideas that are unexplored because they contradict it. Religions are collections of cherished but mistaken principles. So anything that can be described either literally or metaphorically as a religion will have valuable unexplored ideas in its shadow. Copernicus and Darwin both made discoveries of this type. What are people in your field religious about, in the sense of being too attached to some principle that might not be as self-evident as they think? What becomes possible if you discard it? People show much more originality in solving problems than in deciding which problems to solve. Even the smartest can be surprisingly conservative when deciding what to work on. People who'd never dream of being fashionable in any other way get sucked into working on fashionable problems. One reason people are more conservative when choosing problems than solutions is that problems are bigger bets. A problem could occupy you for years, while exploring a solution might only take days. But even so I think most people are too conservative. They're not merely responding to risk, but to fashion as well. Unfashionable problems are undervalued. One of the most interesting kinds of unfashionable problem is the problem that people think has been fully explored, but hasn't. Great work often takes something that already exists and shows its latent potential. Durer and Watt both did this. So if you're interested in a field that others think is tapped out, don't let their skepticism deter you. People are often wrong about this. Working on an unfashionable problem can be very pleasing. There's no hype or hurry. Opportunists and critics are both occupied elsewhere. The existing work often has an old-school solidity. And there's |
satisfying sense of economy in cultivating ideas that would otherwise be wasted. But the most common type of overlooked problem is not explicitly unfashionable in the sense of being out of fashion. It just doesn't seem to matter as much as it actually does. How do you find these? By being self-indulgent — by letting your curiosity have its way, and tuning out, at least temporarily, the little voice in your head that says you should only be working on "important" problems. You do need to work on important problems, but almost everyone is too conservative about what counts as one. And if there's an important but overlooked problem in your neighborhood, it's probably already on your subconscious radar screen. So try asking yourself: if you were going to take a break from "serious" work to work on something just because it would be really interesting, what would you do? The answer is probably more important than it seems. Originality in choosing problems seems to matter even more than originality in solving them. That's what distinguishes the people who discover whole new fields. So what might seem to be merely the initial step — deciding what to work on — is in a sense the key to the whole game. Few grasp this. One of the biggest misconceptions about new ideas is about the ratio of question to answer in their composition. People think big ideas are answers, but often the real insight was in the question. Part of the reason we underrate questions is the way they're used in schools. In schools they tend to exist only briefly before being answered, like unstable particles. But a really good question can be much more than that. A really good question is a partial discovery. How do new species arise? Is the force that makes objects fall to earth the same as the one that keeps planets in their orbits? By even asking such questions you were already in excitingly novel territory. Unanswered questions can be uncomfortable things to carry around with you. But the more you're carrying, the greater the chance of noticing a solution — or perhaps even more excitingly, noticing that two unanswered questions are the same. Sometimes you carry a question for a long time. Great work often comes from returning to a question you first noticed years before — in your childhood, even — and couldn't stop thinking about. People talk a lot about the importance of keeping your youthful dreams alive, but it's just as important to keep your youthful questions alive. This is one of the places where actual expertise differs most from the popular picture of it. In the popular picture, experts are certain. But actually the more puzzled you are, the better, so long as (a) the things you're puzzled about matter, and (b) no one else understands them either. Think about what's happening at the moment just before a new idea is discovered. Often someone with sufficient expertise is puzzled about something. Which means that originality consists partly of puzzlement — of confusion! You have |
be comfortable enough with the world being full of puzzles that you're willing to see them, but not so comfortable that you don't want to solve them. It's a great thing to be rich in unanswered questions. And this is one of those situations where the rich get richer, because the best way to acquire new questions is to try answering existing ones. Questions don't just lead to answers, but also to more questions. The best questions grow in the answering. You notice a thread protruding from the current paradigm and try pulling on it, and it just gets longer and longer. So don't require a question to be obviously big before you try answering it. You can rarely predict that. It's hard enough even to notice the thread, let alone to predict how much will unravel if you pull on it. It's better to be promiscuously curious — to pull a little bit on a lot of threads, and see what happens. Big things start small. The initial versions of big things were often just experiments, or side projects, or talks, which then grew into something bigger. So start lots of small things. Being prolific is underrated. The more different things you try, the greater the chance of discovering something new. Understand, though, that trying lots of things will mean trying lots of things that don't work. You can't have a lot of good ideas without also having a lot of bad ones. Though it sounds more responsible to begin by studying everything that's been done before, you'll learn faster and have more fun by trying stuff. And you'll understand previous work better when you do look at it. So err on the side of starting. Which is easier when starting means starting small; those two ideas fit together like two puzzle pieces. How do you get from starting small to doing something great? By making successive versions. Great things are almost always made in successive versions. You start with something small and evolve it, and the final version is both cleverer and more ambitious than anything you could have planned. It's particularly useful to make successive versions when you're making something for people — to get an initial version in front of them quickly, and then evolve it based on their response. Begin by trying the simplest thing that could possibly work. Surprisingly often, it does. If it doesn't, this will at least get you started. Don't try to cram too much new stuff into any one version. There are names for doing this with the first version (taking too long to ship) and the second (the second system effect), but these are both merely instances of a more general principle. An early version of a new project will sometimes be dismissed as a toy. It's a good sign when people do this. That means it has everything a new idea needs except scale, and that tends to follow. The alternative to starting with something small and evolving it is to plan in advance what you're going to do. And planning does usually seem the more responsible choice. It sounds more organized to say "we're going |
do x and then y and then z" than "we're going to try x and see what happens." And it is more _organized_ ; it just doesn't work as well. Planning per se isn't good. It's sometimes necessary, but it's a necessary evil — a response to unforgiving conditions. It's something you have to do because you're working with inflexible media, or because you need to coordinate the efforts of a lot of people. If you keep projects small and use flexible media, you don't have to plan as much, and your designs can evolve instead. Take as much risk as you can afford. In an efficient market, risk is proportionate to reward, so don't look for certainty, but for a bet with high expected value. If you're not failing occasionally, you're probably being too conservative. Though conservatism is usually associated with the old, it's the young who tend to make this mistake. Inexperience makes them fear risk, but it's when you're young that you can afford the most. Even a project that fails can be valuable. In the process of working on it, you'll have crossed territory few others have seen, and encountered questions few others have asked. And there's probably no better source of questions than the ones you encounter in trying to do something slightly too hard. Use the advantages of youth when you have them, and the advantages of age once you have those. The advantages of youth are energy, time, optimism, and freedom. The advantages of age are knowledge, efficiency, money, and power. With effort you can acquire some of the latter when young and keep some of the former when old. The old also have the advantage of knowing which advantages they have. The young often have them without realizing it. The biggest is probably time. The young have no idea how rich they are in time. The best way to turn this time to advantage is to use it in slightly frivolous ways: to learn about something you don't need to know about, just out of curiosity, or to try building something just because it would be cool, or to become freakishly good at something. That "slightly" is an important qualification. Spend time lavishly when you're young, but don't simply waste it. There's a big difference between doing something you worry might be a waste of time and doing something you know for sure will be. The former is at least a bet, and possibly a better one than you think. The most subtle advantage of youth, or more precisely of inexperience, is that you're seeing everything with fresh eyes. When your brain embraces an idea for the first time, sometimes the two don't fit together perfectly. Usually the problem is with your brain, but occasionally it's with the idea. A piece of it sticks out awkwardly and jabs you when you think about it. People who are used to the idea have learned to ignore it, but you have the opportunity not to. So when you're learning about something for the first time, pay attention to things that seem wrong or missing. You'll be tempted to ignore them, since there's a 99% chance the |
is with you. And you may have to set aside your misgivings temporarily to keep progressing. But don't forget about them. When you've gotten further into the subject, come back and check if they're still there. If they're still viable in the light of your present knowledge, they probably represent an undiscovered idea. One of the most valuable kinds of knowledge you get from experience is to know what you _don't_ have to worry about. The young know all the things that could matter, but not their relative importance. So they worry equally about everything, when they should worry much more about a few things and hardly at all about the rest. But what you don't know is only half the problem with inexperience. The other half is what you do know that ain't so. You arrive at adulthood with your head full of nonsense — bad habits you've acquired and false things you've been taught — and you won't be able to do great work till you clear away at least the nonsense in the way of whatever type of work you want to do. Much of the nonsense left in your head is left there by schools. We're so used to schools that we unconsciously treat going to school as identical with learning, but in fact schools have all sorts of strange qualities that warp our ideas about learning and thinking. For example, schools induce passivity. Since you were a small child, there was an authority at the front of the class telling all of you what you had to learn and then measuring whether you did. But neither classes nor tests are intrinsic to learning; they're just artifacts of the way schools are usually designed. The sooner you overcome this passivity, the better. If you're still in school, try thinking of your education as your project, and your teachers as working for you rather than vice versa. That may seem a stretch, but it's not merely some weird thought experiment. It's the truth, economically, and in the best case it's the truth intellectually as well. The best teachers don't want to be your bosses. They'd prefer it if you pushed ahead, using them as a source of advice, rather than being pulled by them through the material. Schools also give you a misleading impression of what work is like. In school they tell you what the problems are, and they're almost always soluble using no more than you've been taught so far. In real life you have to figure out what the problems are, and you often don't know if they're soluble at all. But perhaps the worst thing schools do to you is train you to win by hacking the test. You can't do great work by doing that. You can't trick God. So stop looking for that kind of shortcut. The way to beat the system is to focus on problems and solutions that others have overlooked, not to skimp on the work itself. Don't think of yourself as dependent on some gatekeeper giving you a "big break." Even if this were true, the best way to get it would be to focus on doing good work rather than chasing influential people. And don't take rejection by committees |
heart. The qualities that impress admissions officers and prize committees are quite different from those required to do great work. The decisions of selection committees are only meaningful to the extent that they're part of a feedback loop, and very few are. People new to a field will often copy existing work. There's nothing inherently bad about that. There's no better way to learn how something works than by trying to reproduce it. Nor does copying necessarily make your work unoriginal. Originality is the presence of new ideas, not the absence of old ones. There's a good way to copy and a bad way. If you're going to copy something, do it openly instead of furtively, or worse still, unconsciously. This is what's meant by the famously misattributed phrase "Great artists steal." The really dangerous kind of copying, the kind that gives copying a bad name, is the kind that's done without realizing it, because you're nothing more than a train running on tracks laid down by someone else. But at the other extreme, copying can be a sign of superiority rather than subordination. In many fields it's almost inevitable that your early work will be in some sense based on other people's. Projects rarely arise in a vacuum. They're usually a reaction to previous work. When you're first starting out, you don't have any previous work; if you're going to react to something, it has to be someone else's. Once you're established, you can react to your own. But while the former gets called derivative and the latter doesn't, structurally the two cases are more similar than they seem. Oddly enough, the very novelty of the most novel ideas sometimes makes them seem at first to be more derivative than they are. New discoveries often have to be conceived initially as variations of existing things, _even by their discoverers_ , because there isn't yet the conceptual vocabulary to express them. There are definitely some dangers to copying, though. One is that you'll tend to copy old things — things that were in their day at the frontier of knowledge, but no longer are. And when you do copy something, don't copy every feature of it. Some will make you ridiculous if you do. Don't copy the manner of an eminent 50 year old professor if you're 18, for example, or the idiom of a Renaissance poem hundreds of years later. Some of the features of things you admire are flaws they succeeded despite. Indeed, the features that are easiest to imitate are the most likely to be the flaws. This is particularly true for behavior. Some talented people are jerks, and this sometimes makes it seem to the inexperienced that being a jerk is part of being talented. It isn't; being talented is merely how they get away with it. One of the most powerful kinds of copying is to copy something from one field into another. History is so full of chance discoveries of this type that it's probably worth giving chance a hand by deliberately learning about other kinds of work. You can take ideas from quite distant |
if you let them be metaphors. Negative examples can be as inspiring as positive ones. In fact you can sometimes learn more from things done badly than from things done well; sometimes it only becomes clear what's needed when it's missing. If a lot of the best people in your field are collected in one place, it's usually a good idea to visit for a while. It will increase your ambition, and also, by showing you that these people are human, increase your self- confidence. If you're earnest you'll probably get a warmer welcome than you might expect. Most people who are very good at something are happy to talk about it with anyone who's genuinely interested. If they're really good at their work, then they probably have a hobbyist's interest in it, and hobbyists always want to talk about their hobbies. It may take some effort to find the people who are really good, though. Doing great work has such prestige that in some places, particularly universities, there's a polite fiction that everyone is engaged in it. And that is far from true. People within universities can't say so openly, but the quality of the work being done in different departments varies immensely. Some departments have people doing great work; others have in the past; others never have. Seek out the best colleagues. There are a lot of projects that can't be done alone, and even if you're working on one that can be, it's good to have other people to encourage you and to bounce ideas off. Colleagues don't just affect your work, though; they also affect you. So work with people you want to become like, because you will. Quality is more important than quantity in colleagues. It's better to have one or two great ones than a building full of pretty good ones. In fact it's not merely better, but necessary, judging from history: the degree to which great work happens in clusters suggests that one's colleagues often make the difference between doing great work and not. How do you know when you have sufficiently good colleagues? In my experience, when you do, you know. Which means if you're unsure, you probably don't. But it may be possible to give a more concrete answer than that. Here's an attempt: sufficiently good colleagues offer _surprising_ insights. They can see and do things that you can't. So if you have a handful of colleagues good enough to keep you on your toes in this sense, you're probably over the threshold. Most of us can benefit from collaborating with colleagues, but some projects require people on a larger scale, and starting one of those is not for everyone. If you want to run a project like that, you'll have to become a manager, and managing well takes aptitude and interest like any other kind of work. If you don't have them, there is no middle path: you must either force yourself to learn management as a second language, or avoid such projects. Husband your morale. It's the basis of everything when you're working on ambitious projects. You have to nurture and protect it like |
living organism. Morale starts with your view of life. You're more likely to do great work if you're an optimist, and more likely to if you think of yourself as lucky than if you think of yourself as a victim. Indeed, work can to some extent protect you from your problems. If you choose work that's pure, its very difficulties will serve as a refuge from the difficulties of everyday life. If this is escapism, it's a very productive form of it, and one that has been used by some of the greatest minds in history. Morale compounds via work: high morale helps you do good work, which increases your morale and helps you do even better work. But this cycle also operates in the other direction: if you're not doing good work, that can demoralize you and make it even harder to. Since it matters so much for this cycle to be running in the right direction, it can be a good idea to switch to easier work when you're stuck, just so you start to get something done. One of the biggest mistakes ambitious people make is to allow setbacks to destroy their morale all at once, like a balloon bursting. You can inoculate yourself against this by explicitly considering setbacks a part of your process. Solving hard problems always involves some backtracking. Doing great work is a depth-first search whose root node is the desire to. So "If at first you don't succeed, try, try again" isn't quite right. It should be: If at first you don't succeed, either try again, or backtrack and then try again. "Never give up" is also not quite right. Obviously there are times when it's the right choice to eject. A more precise version would be: Never let setbacks panic you into backtracking more than you need to. Corollary: Never abandon the root node. It's not necessarily a bad sign if work is a struggle, any more than it's a bad sign to be out of breath while running. It depends how fast you're running. So learn to distinguish good pain from bad. Good pain is a sign of effort; bad pain is a sign of damage. An audience is a critical component of morale. If you're a scholar, your audience may be your peers; in the arts, it may be an audience in the traditional sense. Either way it doesn't need to be big. The value of an audience doesn't grow anything like linearly with its size. Which is bad news if you're famous, but good news if you're just starting out, because it means a small but dedicated audience can be enough to sustain you. If a handful of people genuinely love what you're doing, that's enough. To the extent you can, avoid letting intermediaries come between you and your audience. In some types of work this is inevitable, but it's so liberating to escape it that you might be better off switching to an adjacent type if that will let you go direct. The people you spend time with will also have a big effect on your morale. You'll find there are some who increase your energy and others who decrease it, and the effect someone has is not always what you'd expect. Seek out the people who |
your energy and avoid those who decrease it. Though of course if there's someone you need to take care of, that takes precedence. Don't marry someone who doesn't understand that you need to work, or sees your work as competition for your attention. If you're ambitious, you need to work; it's almost like a medical condition; so someone who won't let you work either doesn't understand you, or does and doesn't care. Ultimately morale is physical. You think with your body, so it's important to take care of it. That means exercising regularly, eating and sleeping well, and avoiding the more dangerous kinds of drugs. Running and walking are particularly good forms of exercise because they're good for thinking. People who do great work are not necessarily happier than everyone else, but they're happier than they'd be if they didn't. In fact, if you're smart and ambitious, it's dangerous _not_ to be productive. People who are smart and ambitious but don't achieve much tend to become bitter. It's ok to want to impress other people, but choose the right people. The opinion of people you respect is signal. Fame, which is the opinion of a much larger group you might or might not respect, just adds noise. The prestige of a type of work is at best a trailing indicator and sometimes completely mistaken. If you do anything well enough, you'll make it prestigious. So the question to ask about a type of work is not how much prestige it has, but how well it could be done. Competition can be an effective motivator, but don't let it choose the problem for you; don't let yourself get drawn into chasing something just because others are. In fact, don't let competitors make you do anything much more specific than work harder. Curiosity is the best guide. Your curiosity never lies, and it knows more than you do about what's worth paying attention to. Notice how often that word has come up. If you asked an oracle the secret to doing great work and the oracle replied with a single word, my bet would be on "curiosity." That doesn't translate directly to advice. It's not enough just to be curious, and you can't command curiosity anyway. But you can nurture it and let it drive you. Curiosity is the key to all four steps in doing great work: it will choose the field for you, get you to the frontier, cause you to notice the gaps in it, and drive you to explore them. The whole process is a kind of dance with curiosity. Believe it or not, I tried to make this essay as short as I could. But its length at least means it acts as a filter. If you made it this far, you must be interested in doing great work. And if so you're already further along than you might realize, because the set of people willing to want to is small. The factors in doing great work are factors in the literal, mathematical sense, and they are: ability, interest, effort, and luck. Luck by definition you can't do anything about, so we can ignore that. And we can assume effort, if you do in fact want to do great work. |
the problem boils down to ability and interest. Can you find a kind of work where your ability and interest will combine to yield an explosion of new ideas? Here there are grounds for optimism. There are so many different ways to do great work, and even more that are still undiscovered. Out of all those different types of work, the one you're most suited for is probably a pretty close match. Probably a comically close match. It's just a question of finding it, and how far into it your ability and interest can take you. And you can only answer that by trying. Many more people could try to do great work than do. What holds them back is a combination of modesty and fear. It seems presumptuous to try to be Newton or Shakespeare. It also seems hard; surely if you tried something like that, you'd fail. Presumably the calculation is rarely explicit. Few people consciously decide not to try to do great work. But that's what's going on subconsciously; they shy away from the question. So I'm going to pull a sneaky trick on you. Do you want to do great work, or not? Now you have to decide consciously. Sorry about that. I wouldn't have done it to a general audience. But we already know you're interested. Don't worry about being presumptuous. You don't have to tell anyone. And if it's too hard and you fail, so what? Lots of people have worse problems than that. In fact you'll be lucky if it's the worst problem you have. Yes, you'll have to work hard. But again, lots of people have to work hard. And if you're working on something you find very interesting, which you necessarily will if you're on the right path, the work will probably feel less burdensome than a lot of your peers'. The discoveries are out there, waiting to be made. Why not by you? ** |
| July 2007 An investor wants to give you money for a certain percentage of your startup. Should you take it? You're about to hire your first employee. How much stock should you give him? These are some of the hardest questions founders face. And yet both have the same answer: 1/(1 - n) Whenever you're trading stock in your company for anything, whether it's money or an employee or a deal with another company, the test for whether to do it is the same. You should give up n% of your company if what you trade it for improves your average outcome enough that the (100 - n)% you have left is worth more than the whole company was before. For example, if an investor wants to buy half your company, how much does that investment have to improve your average outcome for you to break even? Obviously it has to double: if you trade half your company for something that more than doubles the company's average outcome, you're net ahead. You have half as big a share of something worth more than twice as much. In the general case, if n is the fraction of the company you're giving up, the deal is a good one if it makes the company worth more than 1/(1 - n). For example, suppose Y Combinator offers to fund you in return for 7% of your company. In this case, n is .07 and 1/(1 - n) is 1.075. So you should take the deal if you believe we can improve your average outcome by more than 7.5%. If we improve your outcome by 10%, you're net ahead, because the remaining .93 you hold is worth .93 x 1.1 = 1.023. One of the things the equity equation shows us is that, financially at least, taking money from a top VC firm can be a really good deal. Greg Mcadoo from Sequoia recently said at a YC dinner that when Sequoia invests alone they like to take about 30% of a company. 1/.7 = 1.43, meaning that deal is worth taking if they can improve your outcome by more than 43%. For the average startup, that would be an extraordinary bargain. It would improve the average startup's prospects by more than 43% just to be able to _say_ they were funded by Sequoia, even if they never actually got the money. The reason Sequoia is such a good deal is that the percentage of the company they take is artificially low. They don't even try to get market price for their investment; they limit their holdings to leave the founders enough stock to feel the company is still theirs. The catch is that Sequoia gets about 6000 business plans a year and funds about 20 of them, so the odds of getting this great deal are 1 in 300. The companies that make it through are not average startups. Of course, there are other factors to consider in a VC deal. It's never just a straight trade of money for stock. But if it were, taking money from a top firm would generally be a bargain. You can use the same formula when giving stock to employees, but it works in the other direction. If i is the average outcome for the company with the addition of some new person, then they're worth n such that i = 1/(1 - n). Which means n = |
- 1)/i. For example, suppose you're just two founders and you want to hire an additional hacker who's so good you feel he'll increase the average outcome of the whole company by 20%. n = (1.2 - 1)/1.2 = .167. So you'll break even if you trade 16.7% of the company for him. That doesn't mean 16.7% is the right amount of stock to give him. Stock is not the only cost of hiring someone: there's usually salary and overhead as well. And if the company merely breaks even on the deal, there's no reason to do it. I think to translate salary and overhead into stock you should multiply the annual rate by about 1.5. Most startups grow fast or die; if you die you don't have to pay the guy, and if you grow fast you'll be paying next year's salary out of next year's valuation, which should be 3x this year's. If your valuation grows 3x a year, the total cost in stock of a new hire's salary and overhead is 1.5 years' cost at the present valuation. How much of an additional margin should the company need as the "activation energy" for the deal? Since this is in effect the company's profit on a hire, the market will determine that: if you're a hot opportunity, you can charge more. Let's run through an example. Suppose the company wants to make a "profit" of 50% on the new hire mentioned above. So subtract a third from 16.7% and we have 11.1% as his "retail" price. Suppose further that he's going to cost $60k a year in salary and overhead, x 1.5 = $90k total. If the company's valuation is $2 million, $90k is 4.5%. 11.1% - 4.5% = an offer of 6.6%. Incidentally, notice how important it is for early employees to take little salary. It comes right out of stock that could otherwise be given to them. Obviously there is a great deal of play in these numbers. I'm not claiming that stock grants can now be reduced to a formula. Ultimately you always have to guess. But at least know what you're guessing. If you choose a number based on your gut feel, or a table of typical grant sizes supplied by a VC firm, understand what those are estimates of. And more generally, when you make any decision involving equity, run it through 1/(1 - n) to see if it makes sense. You should always feel richer after trading equity. If the trade didn't increase the value of your remaining shares enough to put you net ahead, you wouldn't have (or shouldn't have) done it. ** |
| February 2007 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? 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. 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. 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 |
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. 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. 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 |
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. **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. 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. 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 |
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. Someone like a judge or a military officer can in much of his work be guided by duty, but duty is no guide in making things. Makers depend on something more precarious: inspiration. And like most people who lead a precarious existence, they tend to be worried, not contented. In that respect they're more like the small man of Confucius's day, always one bad harvest (or ruler) away from starvation. Except instead of being at the mercy of weather and officials, they're at the mercy of their own imagination. **Limits** To me it was a relief just to realize it might be ok to be discontented. The idea that a successful person should be happy has thousands of years of momentum behind it. If I was any good, why didn't I have the easy confidence winners are supposed to have? But that, I now believe, is like a runner asking "If I'm such a good athlete, why do I feel so tired?" Good runners still get tired; they just get tired at higher speeds. People whose work is to invent or discover things are in the same position as the runner. There's no way for them to do the best they can, because there's no limit to what they could do. The closest you can come is to compare yourself to other people. But the better you do, the less this matters. An undergrad who gets something published feels like a star. But for someone at the top of the field, what's the test of doing well? Runners can at least compare themselves to others doing exactly the same thing; if you win an Olympic gold medal, you can be fairly content, even if you think you could have run a bit faster. But what is a novelist to do? Whereas if you're doing the kind of work in which problems are presented to you and you have to choose between several alternatives, there's an upper bound on your performance: choosing the best every time. In ancient societies, nearly all work seems to have been of this type. The peasant had to decide whether a garment was worth mending, and the king whether or not to invade his neighbor, but neither was expected to invent anything. In principle they could have; the king could have invented firearms, then invaded his neighbor. But in practice innovations were so rare that they weren't expected of you, any more than goalkeepers are expected to score goals. In practice, it seemed as if there was a correct decision in every situation, and if you made it you'd done your job perfectly, just |
a goalkeeper who prevents the other team from scoring is considered to have played a perfect game. In this world, wisdom seemed paramount. Even now, most people do work in which problems are put before them and they have to choose the best alternative. But as knowledge has grown more specialized, there are more and more types of work in which people have to make up new things, and in which performance is therefore unbounded. Intelligence has become increasingly important relative to wisdom because there is more room for spikes. **Recipes** Another sign we may have to choose between intelligence and wisdom is how different their recipes are. Wisdom seems to come largely from curing childish qualities, and intelligence largely from cultivating them. Recipes for wisdom, particularly ancient ones, tend to have a remedial character. To achieve wisdom one must cut away all the debris that fills one's head on emergence from childhood, leaving only the important stuff. Both self- control and experience have this effect: to eliminate the random biases that come from your own nature and from the circumstances of your upbringing respectively. That's not all wisdom is, but it's a large part of it. Much of what's in the sage's head is also in the head of every twelve year old. The difference is that in the head of the twelve year old it's mixed together with a lot of random junk. The path to intelligence seems to be through working on hard problems. You develop intelligence as you might develop muscles, through exercise. But there can't be too much compulsion here. No amount of discipline can replace genuine curiosity. So cultivating intelligence seems to be a matter of identifying some bias in one's character—some tendency to be interested in certain types of things—and nurturing it. Instead of obliterating your idiosyncrasies in an effort to make yourself a neutral vessel for the truth, you select one and try to grow it from a seedling into a tree. The wise are all much alike in their wisdom, but very smart people tend to be smart in distinctive ways. Most of our educational traditions aim at wisdom. So perhaps one reason schools work badly is that they're trying to make intelligence using recipes for wisdom. Most recipes for wisdom have an element of subjection. At the very least, you're supposed to do what the teacher says. The more extreme recipes aim to break down your individuality the way basic training does. But that's not the route to intelligence. Whereas wisdom comes through humility, it may actually help, in cultivating intelligence, to have a mistakenly high opinion of your abilities, because that encourages you to keep working. Ideally till you realize how mistaken you were. (The reason it's hard to learn new skills late in life is not just that one's brain is less malleable. Another probably even worse obstacle is that one has higher standards.) I realize we're on dangerous ground here. I'm not proposing the primary goal of education should be |
increase students' "self-esteem." That just breeds laziness. And in any case, it doesn't really fool the kids, not the smart ones. They can tell at a young age that a contest where everyone wins is a fraud. A teacher has to walk a narrow path: you want to encourage kids to come up with things on their own, but you can't simply applaud everything they produce. You have to be a good audience: appreciative, but not too easily impressed. And that's a lot of work. You have to have a good enough grasp of kids' capacities at different ages to know when to be surprised. That's the opposite of traditional recipes for education. Traditionally the student is the audience, not the teacher; the student's job is not to invent, but to absorb some prescribed body of material. (The use of the term "recitation" for sections in some colleges is a fossil of this.) The problem with these old traditions is that they're too much influenced by recipes for wisdom. **Different** I deliberately gave this essay a provocative title; of course it's worth being wise. But I think it's important to understand the relationship between intelligence and wisdom, and particularly what seems to be the growing gap between them. That way we can avoid applying rules and standards to intelligence that are really meant for wisdom. These two senses of "knowing what to do" are more different than most people realize. The path to wisdom is through discipline, and the path to intelligence through carefully selected self-indulgence. Wisdom is universal, and intelligence idiosyncratic. And while wisdom yields calmness, intelligence much of the time leads to discontentment. That's particularly worth remembering. A physicist friend recently told me half his department was on Prozac. Perhaps if we acknowledge that some amount of frustration is inevitable in certain kinds of work, we can mitigate its effects. Perhaps we can box it up and put it away some of the time, instead of letting it flow together with everyday sadness to produce what seems an alarmingly large pool. At the very least, we can avoid being discontented about being discontented. If you feel exhausted, it's not necessarily because there's something wrong with you. Maybe you're just running fast. ** |
| | **Want to start a startup?** Get funded by Y Combinator. --- March 2005 _(This essay is derived from a talk at the Harvard Computer Society.)_ You need three things to create a successful startup: to start with good people, to make something customers actually want, and to spend as little money as possible. Most startups that fail do it because they fail at one of these. A startup that does all three will probably succeed. And that's kind of exciting, when you think about it, because all three are doable. Hard, but doable. And since a startup that succeeds ordinarily makes its founders rich, that implies getting rich is doable too. Hard, but doable. If there is one message I'd like to get across about startups, that's it. There is no magically difficult step that requires brilliance to solve. **The Idea** In particular, you don't need a brilliant idea to start a startup around. The way a startup makes money is to offer people better technology than they have now. But what people have now is often so bad that it doesn't take brilliance to do better. Google's plan, for example, was simply to create a search site that didn't suck. They had three new ideas: index more of the Web, use links to rank search results, and have clean, simple web pages with unintrusive keyword- based ads. Above all, they were determined to make a site that was good to use. No doubt there are great technical tricks within Google, but the overall plan was straightforward. And while they probably have bigger ambitions now, this alone brings them a billion dollars a year. There are plenty of other areas that are just as backward as search was before Google. I can think of several heuristics for generating ideas for startups, but most reduce to this: look at something people are trying to do, and figure out how to do it in a way that doesn't suck. For example, dating sites currently suck far worse than search did before Google. They all use the same simple-minded model. They seem to have approached the problem by thinking about how to do database matches instead of how dating works in the real world. An undergrad could build something better as a class project. And yet there's a lot of money at stake. Online dating is a valuable business now, and it might be worth a hundred times as much if it worked. An idea for a startup, however, is only a beginning. A lot of would-be startup founders think the key to the whole process is the initial idea, and from that point all you have to do is execute. Venture capitalists know better. If you go to VC firms with a brilliant idea that you'll tell them about if they sign a nondisclosure agreement, most will tell you to get lost. That shows how much a mere idea is worth. The market price is less than the inconvenience of signing an NDA. Another sign of how little the initial idea is worth is the number of startups that change their plan en route. Microsoft's original plan was to make money selling programming languages, of all things. Their |
business model didn't occur to them until IBM dropped it in their lap five years later. Ideas for startups are worth something, certainly, but the trouble is, they're not transferrable. They're not something you could hand to someone else to execute. Their value is mainly as starting points: as questions for the people who had them to continue thinking about. What matters is not ideas, but the people who have them. Good people can fix bad ideas, but good ideas can't save bad people. **People** What do I mean by good people? One of the best tricks I learned during our startup was a rule for deciding who to hire. Could you describe the person as an animal? It might be hard to translate that into another language, but I think everyone in the US knows what it means. It means someone who takes their work a little too seriously; someone who does what they do so well that they pass right through professional and cross over into obsessive. What it means specifically depends on the job: a salesperson who just won't take no for an answer; a hacker who will stay up till 4:00 AM rather than go to bed leaving code with a bug in it; a PR person who will cold-call _New York Times_ reporters on their cell phones; a graphic designer who feels physical pain when something is two millimeters out of place. Almost everyone who worked for us was an animal at what they did. The woman in charge of sales was so tenacious that I used to feel sorry for potential customers on the phone with her. You could sense them squirming on the hook, but you knew there would be no rest for them till they'd signed up. If you think about people you know, you'll find the animal test is easy to apply. Call the person's image to mind and imagine the sentence "so-and-so is an animal." If you laugh, they're not. You don't need or perhaps even want this quality in big companies, but you need it in a startup. For programmers we had three additional tests. Was the person genuinely smart? If so, could they actually get things done? And finally, since a few good hackers have unbearable personalities, could we stand to have them around? That last test filters out surprisingly few people. We could bear any amount of nerdiness if someone was truly smart. What we couldn't stand were people with a lot of attitude. But most of those weren't truly smart, so our third test was largely a restatement of the first. When nerds are unbearable it's usually because they're trying too hard to seem smart. But the smarter they are, the less pressure they feel to act smart. So as a rule you can recognize genuinely smart people by their ability to say things like "I don't know," "Maybe you're right," and "I don't understand x well enough." This technique doesn't always work, because people can be influenced by their environment. In the MIT CS department, there seems to be a tradition of acting like a brusque know-it-all. I'm told it derives ultimately from Marvin Minsky, in the same way the classic airline pilot manner |
said to derive from Chuck Yeager. Even genuinely smart people start to act this way there, so you have to make allowances. It helped us to have Robert Morris, who is one of the readiest to say "I don't know" of anyone I've met. (At least, he was before he became a professor at MIT.) No one dared put on attitude around Robert, because he was obviously smarter than they were and yet had zero attitude himself. Like most startups, ours began with a group of friends, and it was through personal contacts that we got most of the people we hired. This is a crucial difference between startups and big companies. Being friends with someone for even a couple days will tell you more than companies could ever learn in interviews. It's no coincidence that startups start around universities, because that's where smart people meet. It's not what people learn in classes at MIT and Stanford that has made technology companies spring up around them. They could sing campfire songs in the classes so long as admissions worked the same. If you start a startup, there's a good chance it will be with people you know from college or grad school. So in theory you ought to try to make friends with as many smart people as you can in school, right? Well, no. Don't make a conscious effort to schmooze; that doesn't work well with hackers. What you should do in college is work on your own projects. Hackers should do this even if they don't plan to start startups, because it's the only real way to learn how to program. In some cases you may collaborate with other students, and this is the best way to get to know good hackers. The project may even grow into a startup. But once again, I wouldn't aim too directly at either target. Don't force things; just work on stuff you like with people you like. Ideally you want between two and four founders. It would be hard to start with just one. One person would find the moral weight of starting a company hard to bear. Even Bill Gates, who seems to be able to bear a good deal of moral weight, had to have a co-founder. But you don't want so many founders that the company starts to look like a group photo. Partly because you don't need a lot of people at first, but mainly because the more founders you have, the worse disagreements you'll have. When there are just two or three founders, you know you have to resolve disputes immediately or perish. If there are seven or eight, disagreements can linger and harden into factions. You don't want mere voting; you need unanimity. In a technology startup, which most startups are, the founders should include technical people. During the Internet Bubble there were a number of startups founded by business people who then went looking for hackers to create their product for them. This doesn't work well. Business people are bad at deciding what to do with technology, because they don't know what the options are, or which kinds of problems are hard and which are easy. And when business people try to hire hackers, |
can't tell which ones are good. Even other hackers have a hard time doing that. For business people it's roulette. Do the founders of a startup have to include business people? That depends. We thought so when we started ours, and we asked several people who were said to know about this mysterious thing called "business" if they would be the president. But they all said no, so I had to do it myself. And what I discovered was that business was no great mystery. It's not something like physics or medicine that requires extensive study. You just try to get people to pay you for stuff. I think the reason I made such a mystery of business was that I was disgusted by the idea of doing it. I wanted to work in the pure, intellectual world of software, not deal with customers' mundane problems. People who don't want to get dragged into some kind of work often develop a protective incompetence at it. Paul Erdos was particularly good at this. By seeming unable even to cut a grapefruit in half (let alone go to the store and buy one), he forced other people to do such things for him, leaving all his time free for math. Erdos was an extreme case, but most husbands use the same trick to some degree. Once I was forced to discard my protective incompetence, I found that business was neither so hard nor so boring as I feared. There are esoteric areas of business that are quite hard, like tax law or the pricing of derivatives, but you don't need to know about those in a startup. All you need to know about business to run a startup are commonsense things people knew before there were business schools, or even universities. If you work your way down the Forbes 400 making an x next to the name of each person with an MBA, you'll learn something important about business school. After Warren Buffett, you don't hit another MBA till number 22, Phil Knight, the CEO of Nike. There are only 5 MBAs in the top 50\. What you notice in the Forbes 400 are a lot of people with technical backgrounds. Bill Gates, Steve Jobs, Larry Ellison, Michael Dell, Jeff Bezos, Gordon Moore. The rulers of the technology business tend to come from technology, not business. So if you want to invest two years in something that will help you succeed in business, the evidence suggests you'd do better to learn how to hack than get an MBA. There is one reason you might want to include business people in a startup, though: because you have to have at least one person willing and able to focus on what customers want. Some believe only business people can do this-- that hackers can implement software, but not design it. That's nonsense. There's nothing about knowing how to program that prevents hackers from understanding users, or about not knowing how to program that magically enables business people to understand them. If you can't understand users, however, you should either learn how or find a co-founder who can. That is the single most important issue for technology startups, and the rock that sinks more |
them than anything else. **What Customers Want** It's not just startups that have to worry about this. I think most businesses that fail do it because they don't give customers what they want. Look at restaurants. A large percentage fail, about a quarter in the first year. But can you think of one restaurant that had really good food and went out of business? Restaurants with great food seem to prosper no matter what. A restaurant with great food can be expensive, crowded, noisy, dingy, out of the way, and even have bad service, and people will keep coming. It's true that a restaurant with mediocre food can sometimes attract customers through gimmicks. But that approach is very risky. It's more straightforward just to make the food good. It's the same with technology. You hear all kinds of reasons why startups fail. But can you think of one that had a massively popular product and still failed? In nearly every failed startup, the real problem was that customers didn't want the product. For most, the cause of death is listed as "ran out of funding," but that's only the immediate cause. Why couldn't they get more funding? Probably because the product was a dog, or never seemed likely to be done, or both. When I was trying to think of the things every startup needed to do, I almost included a fourth: get a version 1 out as soon as you can. But I decided not to, because that's implicit in making something customers want. The only way to make something customers want is to get a prototype in front of them and refine it based on their reactions. The other approach is what I call the "Hail Mary" strategy. You make elaborate plans for a product, hire a team of engineers to develop it (people who do this tend to use the term "engineer" for hackers), and then find after a year that you've spent two million dollars to develop something no one wants. This was not uncommon during the Bubble, especially in companies run by business types, who thought of software development as something terrifying that therefore had to be carefully planned. We never even considered that approach. As a Lisp hacker, I come from the tradition of rapid prototyping. I would not claim (at least, not here) that this is the right way to write every program, but it's certainly the right way to write software for a startup. In a startup, your initial plans are almost certain to be wrong in some way, and your first priority should be to figure out where. The only way to do that is to try implementing them. Like most startups, we changed our plan on the fly. At first we expected our customers to be Web consultants. But it turned out they didn't like us, because our software was easy to use and we hosted the site. It would be too easy for clients to fire them. We also thought we'd be able to sign up a lot of catalog companies, because selling online was a natural extension of their existing business. But in 1996 that was a hard sell. The middle managers we talked to at catalog companies saw |
Web not as an opportunity, but as something that meant more work for them. We did get a few of the more adventurous catalog companies. Among them was Frederick's of Hollywood, which gave us valuable experience dealing with heavy loads on our servers. But most of our users were small, individual merchants who saw the Web as an opportunity to build a business. Some had retail stores, but many only existed online. And so we changed direction to focus on these users. Instead of concentrating on the features Web consultants and catalog companies would want, we worked to make the software easy to use. I learned something valuable from that. It's worth trying very, very hard to make technology easy to use. Hackers are so used to computers that they have no idea how horrifying software seems to normal people. Stephen Hawking's editor told him that every equation he included in his book would cut sales in half. When you work on making technology easier to use, you're riding that curve up instead of down. A 10% improvement in ease of use doesn't just increase your sales 10%. It's more likely to double your sales. How do you figure out what customers want? Watch them. One of the best places to do this was at trade shows. Trade shows didn't pay as a way of getting new customers, but they were worth it as market research. We didn't just give canned presentations at trade shows. We used to show people how to build real, working stores. Which meant we got to watch as they used our software, and talk to them about what they needed. No matter what kind of startup you start, it will probably be a stretch for you, the founders, to understand what users want. The only kind of software you can build without studying users is the sort for which you are the typical user. But this is just the kind that tends to be open source: operating systems, programming languages, editors, and so on. So if you're developing technology for money, you're probably not going to be developing it for people like you. Indeed, you can use this as a way to generate ideas for startups: what do people who are not like you want from technology? When most people think of startups, they think of companies like Apple or Google. Everyone knows these, because they're big consumer brands. But for every startup like that, there are twenty more that operate in niche markets or live quietly down in the infrastructure. So if you start a successful startup, odds are you'll start one of those. Another way to say that is, if you try to start the kind of startup that has to be a big consumer brand, the odds against succeeding are steeper. The best odds are in niche markets. Since startups make money by offering people something better than they had before, the best opportunities are where things suck most. And it would be hard to find a place where things suck more than in corporate IT departments. You would not believe the amount of money companies spend on software, and the crap they get in return. This imbalance |
opportunity. If you want ideas for startups, one of the most valuable things you could do is find a middle-sized non-technology company and spend a couple weeks just watching what they do with computers. Most good hackers have no more idea of the horrors perpetrated in these places than rich Americans do of what goes on in Brazilian slums. Start by writing software for smaller companies, because it's easier to sell to them. It's worth so much to sell stuff to big companies that the people selling them the crap they currently use spend a lot of time and money to do it. And while you can outhack Oracle with one frontal lobe tied behind your back, you can't outsell an Oracle salesman. So if you want to win through better technology, aim at smaller customers. They're the more strategically valuable part of the market anyway. In technology, the low end always eats the high end. It's easier to make an inexpensive product more powerful than to make a powerful product cheaper. So the products that start as cheap, simple options tend to gradually grow more powerful till, like water rising in a room, they squash the "high-end" products against the ceiling. Sun did this to mainframes, and Intel is doing it to Sun. Microsoft Word did it to desktop publishing software like Interleaf and Framemaker. Mass-market digital cameras are doing it to the expensive models made for professionals. Avid did it to the manufacturers of specialized video editing systems, and now Apple is doing it to Avid. _Henry Ford_ did it to the car makers that preceded him. If you build the simple, inexpensive option, you'll not only find it easier to sell at first, but you'll also be in the best position to conquer the rest of the market. It's very dangerous to let anyone fly under you. If you have the cheapest, easiest product, you'll own the low end. And if you don't, you're in the crosshairs of whoever does. **Raising Money** To make all this happen, you're going to need money. Some startups have been self-funding-- Microsoft for example-- but most aren't. I think it's wise to take money from investors. To be self-funding, you have to start as a consulting company, and it's hard to switch from that to a product company. Financially, a startup is like a pass/fail course. The way to get rich from a startup is to maximize the company's chances of succeeding, not to maximize the amount of stock you retain. So if you can trade stock for something that improves your odds, it's probably a smart move. To most hackers, getting investors seems like a terrifying and mysterious process. Actually it's merely tedious. I'll try to give an outline of how it works. The first thing you'll need is a few tens of thousands of dollars to pay your expenses while you develop a prototype. This is called seed capital. Because so little money is involved, raising seed capital is comparatively easy-- at least in the sense of getting a quick yes or no. Usually you get seed money from individual rich people called |
Often they're people who themselves got rich from technology. At the seed stage, investors don't expect you to have an elaborate business plan. Most know that they're supposed to decide quickly. It's not unusual to get a check within a week based on a half-page agreement. We started Viaweb with $10,000 of seed money from our friend Julian. But he gave us a lot more than money. He's a former CEO and also a corporate lawyer, so he gave us a lot of valuable advice about business, and also did all the legal work of getting us set up as a company. Plus he introduced us to one of the two angel investors who supplied our next round of funding. Some angels, especially those with technology backgrounds, may be satisfied with a demo and a verbal description of what you plan to do. But many will want a copy of your business plan, if only to remind themselves what they invested in. Our angels asked for one, and looking back, I'm amazed how much worry it caused me. "Business plan" has that word "business" in it, so I figured it had to be something I'd have to read a book about business plans to write. Well, it doesn't. At this stage, all most investors expect is a brief description of what you plan to do and how you're going to make money from it, and the resumes of the founders. If you just sit down and write out what you've been saying to one another, that should be fine. It shouldn't take more than a couple hours, and you'll probably find that writing it all down gives you more ideas about what to do. For the angel to have someone to make the check out to, you're going to have to have some kind of company. Merely incorporating yourselves isn't hard. The problem is, for the company to exist, you have to decide who the founders are, and how much stock they each have. If there are two founders with the same qualifications who are both equally committed to the business, that's easy. But if you have a number of people who are expected to contribute in varying degrees, arranging the proportions of stock can be hard. And once you've done it, it tends to be set in stone. I have no tricks for dealing with this problem. All I can say is, try hard to do it right. I do have a rule of thumb for recognizing when you have, though. When everyone feels they're getting a slightly bad deal, that they're doing more than they should for the amount of stock they have, the stock is optimally apportioned. There is more to setting up a company than incorporating it, of course: insurance, business license, unemployment compensation, various things with the IRS. I'm not even sure what the list is, because we, ah, skipped all that. When we got real funding near the end of 1996, we hired a great CFO, who fixed everything retroactively. It turns out that no one comes and arrests you if you don't do everything you're supposed to when starting a company. And a good thing too, or a lot of startups would never get started. It can be dangerous to delay turning yourself into a company, because |
or more of the founders might decide to split off and start another company doing the same thing. This does happen. So when you set up the company, as well as as apportioning the stock, you should get all the founders to sign something agreeing that everyone's ideas belong to this company, and that this company is going to be everyone's only job. [If this were a movie, ominous music would begin here.] While you're at it, you should ask what else they've signed. One of the worst things that can happen to a startup is to run into intellectual property problems. We did, and it came closer to killing us than any competitor ever did. As we were in the middle of getting bought, we discovered that one of our people had, early on, been bound by an agreement that said all his ideas belonged to the giant company that was paying for him to go to grad school. In theory, that could have meant someone else owned big chunks of our software. So the acquisition came to a screeching halt while we tried to sort this out. The problem was, since we'd been about to be acquired, we'd allowed ourselves to run low on cash. Now we needed to raise more to keep going. But it's hard to raise money with an IP cloud over your head, because investors can't judge how serious it is. Our existing investors, knowing that we needed money and had nowhere else to get it, at this point attempted certain gambits which I will not describe in detail, except to remind readers that the word "angel" is a metaphor. The founders thereupon proposed to walk away from the company, after giving the investors a brief tutorial on how to administer the servers themselves. And while this was happening, the acquirers used the delay as an excuse to welch on the deal. Miraculously it all turned out ok. The investors backed down; we did another round of funding at a reasonable valuation; the giant company finally gave us a piece of paper saying they didn't own our software; and six months later we were bought by Yahoo for much more than the earlier acquirer had agreed to pay. So we were happy in the end, though the experience probably took several years off my life. Don't do what we did. Before you consummate a startup, ask everyone about their previous IP history. Once you've got a company set up, it may seem presumptuous to go knocking on the doors of rich people and asking them to invest tens of thousands of dollars in something that is really just a bunch of guys with some ideas. But when you look at it from the rich people's point of view, the picture is more encouraging. Most rich people are looking for good investments. If you really think you have a chance of succeeding, you're doing them a favor by letting them invest. Mixed with any annoyance they might feel about being approached will be the thought: are these guys the next Google? Usually angels are financially equivalent to founders. They get the same kind of stock and get diluted the same amount in future rounds. How much stock should they get? |
depends on how ambitious you feel. When you offer x percent of your company for y dollars, you're implicitly claiming a certain value for the whole company. Venture investments are usually described in terms of that number. If you give an investor new shares equal to 5% of those already outstanding in return for $100,000, then you've done the deal at a pre-money valuation of $2 million. How do you decide what the value of the company should be? There is no rational way. At this stage the company is just a bet. I didn't realize that when we were raising money. Julian thought we ought to value the company at several million dollars. I thought it was preposterous to claim that a couple thousand lines of code, which was all we had at the time, were worth several million dollars. Eventually we settled on one million, because Julian said no one would invest in a company with a valuation any lower. What I didn't grasp at the time was that the valuation wasn't just the value of the code we'd written so far. It was also the value of our ideas, which turned out to be right, and of all the future work we'd do, which turned out to be a lot. The next round of funding is the one in which you might deal with actual venture capital firms. But don't wait till you've burned through your last round of funding to start approaching them. VCs are slow to make up their minds. They can take months. You don't want to be running out of money while you're trying to negotiate with them. Getting money from an actual VC firm is a bigger deal than getting money from angels. The amounts of money involved are larger, millions usually. So the deals take longer, dilute you more, and impose more onerous conditions. Sometimes the VCs want to install a new CEO of their own choosing. Usually the claim is that you need someone mature and experienced, with a business background. Maybe in some cases this is true. And yet Bill Gates was young and inexperienced and had no business background, and he seems to have done ok. Steve Jobs got booted out of his own company by someone mature and experienced, with a business background, who then proceeded to ruin the company. So I think people who are mature and experienced, with a business background, may be overrated. We used to call these guys "newscasters," because they had neat hair and spoke in deep, confident voices, and generally didn't know much more than they read on the teleprompter. We talked to a number of VCs, but eventually we ended up financing our startup entirely with angel money. The main reason was that we feared a brand-name VC firm would stick us with a newscaster as part of the deal. That might have been ok if he was content to limit himself to talking to the press, but what if he wanted to have a say in running the company? That would have led to disaster, because our software was so complex. We were a company whose whole m.o. was to win through better technology. The strategic decisions were mostly decisions about technology, |
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