 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. +[1] 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 pt. 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 +the 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. +[2] 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. +[3] 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 returns +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. +[4] A principle for taking advantage of thresholds has to include a +test to ensure the game is worth playing. Here's one that does: if +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. +[5] 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. +[6] 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 will 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. +[7] 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. [8] +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. +[9] +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 the 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. +[10] 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. +[11] 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. +[12] 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 rate, 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. Notes There's a limit to how sharply you can distinguish between effort, +performance, and return, because they're not sharply distinguished +in fact. What counts as return to one person might be performance +to another. But though the borders of these concepts are blurry, +they're not meaningless. I've tried to write about them as precisely +as I could without crossing into error. [1] +Evolution itself is probably the most pervasive example of +superlinear returns for performance. But this is hard for us to +empathize with because we're not the recipients; we're the returns. [2] +Knowledge did of course have a practical effect before the +Industrial Revolution. The development of agriculture changed human +life completely. But this kind of change was the result of broad, +gradual improvements in technique, not the discoveries of a few +exceptionally learned people. [3] +It's not mathematically correct to describe a step function as +superlinear, but a step function starting from zero works like a +superlinear function when it describes the reward curve for effort +by a rational actor. If it starts at zero then the part before the +step is below any linearly increasing return, and the part after +the step must be above the necessary return at that point or no one +would bother. [4] +Seeking competition could be a good heuristic in the sense that +some people find it motivating. It's also somewhat of a guide to +promising problems, because it's a sign that other people find them +promising. But it's a very imperfect sign: often there's a clamoring +crowd chasing some problem, and they all end up being trumped by +someone quietly working on another one. [5] +Not always, though. You have to be careful with this rule. When +something is popular despite being mediocre, there's often a hidden +reason why. Perhaps monopoly or regulation make it hard to compete. +Perhaps customers have bad taste or have broken procedures for +deciding what to buy. There are huge swathes of mediocre things +that exist for such reasons. [6] +In my twenties I wanted to be an artist +and even went to art +school to study painting. Mostly because I liked art, but a nontrivial +part of my motivation came from the fact that artists seemed least +at the mercy of organizations. [7] +In principle everyone is getting superlinear returns. Learning +compounds, and everyone learns in the course of their life. But in +practice few push this kind of everyday learning to the point where +the return curve gets really steep. [8] +It's unclear exactly what advocates of "equity" mean by it. +They seem to disagree among themselves. But whatever they mean is +probably at odds with a world in which institutions have less power +to control outcomes, and a handful of outliers do much better than +everyone else. It may seem like bad luck for this concept that it arose at just +the moment when the world was shifting in the opposite direction, +but I don't think this was a coincidence. I think one reason it +arose now is because its adherents feel threatened by rapidly +increasing variation in performance. [9] +Corollary: Parents who pressure their kids to work on something +prestigious, like medicine, even though they have no interest in +it, will be hosing them even more than they have in the past. [10] +The original version of this paragraph was the first draft of +"How to Do Great Work." +As soon as I wrote it I realized it was a more important topic than superlinear +returns, so I paused the present essay to expand this paragraph into its +own. Practically nothing remains of the original version, because +after I finished "How to Do Great Work" I rewrote it based on that. [11] +Before the Industrial Revolution, people who got rich usually +did it like emperors: capturing some resource made them more powerful +and enabled them to capture more. Now it can be done like a scientist, +by discovering or building something uniquely valuable. Most people +who get rich use a mix of the old and the new ways, but in the most +advanced economies the ratio has shifted dramatically toward discovery +just in the last half century. [12] +It's not surprising that conventional-minded people would +dislike inequality if independent-mindedness is one of the biggest +drivers of it. But it's not simply that they don't want anyone to +have what they can't. The conventional-minded literally can't imagine +what it's like to have novel ideas. So the whole phenomenon of great +variation in performance seems unnatural to them, and when they +encounter it they assume it must be due to cheating or to some +malign external influence. Thanks +to Trevor Blackwell, Patrick Collusion, Tyler Cowen, +Jessica Livingston, Harj Taggar, and Garry Tan for reading drafts +of this. |