Zero to One: Secrets and Opportunities PDF

8 SECRETS EVERY ONE OF TODAY’S most famous and familiar ideas was once unknown and unsuspected. The mathematical relationship between a triangle’s sides, for example, was secret for millennia. Pythagoras had to think hard to discover it. If you wanted in on Pythagoras’s new discovery, joining his strange vegetarian cult was the best way to learn about it. Today, his geometry has become a convention—a simple truth we teach to grade schoolers. A conventional truth can be important— it’s essential to learn elementary mathematics, for example—but it won’t give you an edge. It’s not a secret. Remember our contrarian question: what important truth do very few people agree with you on? If we already understand as much of the natural world as we ever will—if all of today’s conventional ideas are already enlightened, and if everything has already been done—then there are no good answers. Contrarian thinking doesn’t make any sense unless the world still has secrets left to give up. Of course, there are many things we don’t yet understand, but some of those things may be impossible to ﬁgure out—mysteries rather than secrets. For example, string theory describes the physics of the universe in terms of vibrating one-dimensional objects called “strings.” Is string theory true? You can’t really design experiments to test it. Very few people, if any, could ever understand all its implications. But is that just because it’s diﬃcult? Or is it an impossible mystery? The diﬀerence matters. You can achieve diﬃcult things, but you can’t achieve the impossible. Recall the business version of our contrarian question: what valuable company is nobody building? Every correct answer is necessarily a secret: something important and unknown, something hard to do but doable. If there are many secrets left in the world, there are probably many world-changing companies yet to be started. This chapter will help you think about secrets and how to ﬁnd them. WHY AREN’T PEOPLE LOOKING FOR SECRETS? Most people act as if there were no secrets left to ﬁnd. An extreme representative of this view is Ted Kaczynski, infamously known as the Unabomber. Kaczynski was a child prodigy who enrolled at Harvard at 16. He went on to get a PhD in math and become a professor at UC Berkeley. But you’ve only ever heard of him because of the 17-year terror campaign he waged with pipe bombs against professors, technologists, and businesspeople. In late 1995, the authorities didn’t know who or where the Unabomber was. The biggest clue was a 35,000-word manifesto that Kaczynski had written and anonymously mailed to the press. The FBI asked some prominent newspapers to publish it, hoping for a break in the case. It worked: Kaczynski’s brother recognized his writing style and turned him in. You might expect that writing style to have shown obvious signs of insanity, but the manifesto is eerily cogent. Kaczynski claimed that in order to be happy, every individual “needs to have goals whose attainment requires eﬀort, and needs to succeed in attaining at least some of his goals.” He divided human goals into three groups: 1. Goals that can be satisﬁed with minimal eﬀort; 2. Goals that can be satisﬁed with serious eﬀort; and 3. Goals that cannot be satisﬁed, no matter how much eﬀort one makes. This is the classic trichotomy of the easy, the hard, and the impossible. Kaczynski argued that modern people are depressed because all the world’s hard problems have already been solved. What’s left to do is either easy or impossible, and pursuing those tasks is deeply unsatisfying. What you can do, even a child can do; what you can’t do, even Einstein couldn’t have done. So Kaczynski’s idea was to destroy existing institutions, get rid of all technology, and let people start over and work on hard problems anew. Kaczynski’s methods were crazy, but his loss of faith in the technological frontier is all around us. Consider the trivial but revealing hallmarks of urban hipsterdom: faux vintage photography, the handlebar mustache, and vinyl record players all hark back to an earlier time when people were still optimistic about the future. If everything worth doing has already been done, you may as well feign an allergy to achievement and become a barista. Hipster or Unabomber? All fundamentalists think this way, not just terrorists and hipsters. Religious fundamentalism, for example, allows no middle ground for hard questions: there are easy truths that children are expected to rattle oﬀ, and then there are the mysteries of God, which can’t be explained. In between—the zone of hard truths—lies heresy. In the modern religion of environmentalism, the easy truth is that we must protect the environment. Beyond that, Mother Nature knows best, and she cannot be questioned. Free marketeers worship a similar logic. The value of things is set by the market. Even a child can look up stock quotes. But whether those prices make sense is not to be second- guessed; the market knows far more than you ever could. Why has so much of our society come to believe that there are no hard secrets left? It might start with geography. There are no blank spaces left on the map anymore. If you grew up in the 18th century, there were still new places to go. After hearing tales of foreign adventure, you could become an explorer yourself. This was probably true up through the 19th and early 20th centuries; after that point photography from National Geographic showed every Westerner what even the most exotic, underexplored places on earth look like. Today, explorers are found mostly in history books and children’s tales. Parents don’t expect their kids to become explorers any more than they expect them to become pirates or sultans. Perhaps there are a few dozen uncontacted tribes somewhere deep in the Amazon, and we know there remains one last earthly frontier in the depths of the oceans. But the unknown seems less accessible than ever. Along with the natural fact that physical frontiers have receded, four social trends have conspired to root out belief in secrets. First is incrementalism. From an early age, we are taught that the right way to do things is to proceed one very small step at a time, day by day, grade by grade. If you overachieve and end up learning something that’s not on the test, you won’t receive credit for it. But in exchange for doing exactly what’s asked of you (and for doing it just a bit better than your peers), you’ll get an A. This process extends all the way up through the tenure track, which is why academics usually chase large numbers of trivial publications instead of new frontiers. Second is risk aversion. People are scared of secrets because they are scared of being wrong. By deﬁnition, a secret hasn’t been vetted by the mainstream. If your goal is to never make a mistake in your life, you shouldn’t look for secrets. The prospect of being lonely but right— dedicating your life to something that no one else believes in—is already hard. The prospect of being lonely and wrong can be unbearable. Third is complacency. Social elites have the most freedom and ability to explore new thinking, but they seem to believe in secrets the least. Why search for a new secret if you can comfortably collect rents on everything that has already been done? Every fall, the deans at top law schools and business schools welcome the incoming class with the same implicit message: “You got into this elite institution. Your worries are over. You’re set for life.” But that’s probably the kind of thing that’s true only if you don’t believe it. Fourth is “flatness.” As globalization advances, people perceive the world as one homogeneous, highly competitive marketplace: the world is “ﬂat.” Given that assumption, anyone who might have had the ambition to look for a secret will ﬁrst ask himself: if it were possible to discover something new, wouldn’t someone from the faceless global talent pool of smarter and more creative people have found it already? This voice of doubt can dissuade people from even starting to look for secrets in a world that seems too big a place for any individual to contribute something unique. There’s an optimistic way to describe the result of these trends: today, you can’t start a cult. Forty years ago, people were more open to the idea that not all knowledge was widely known. From the Communist Party to the Hare Krishnas, large numbers of people thought they could join some enlightened vanguard that would show them the Way. Very few people take unorthodox ideas seriously today, and the mainstream sees that as a sign of progress. We can be glad that there are fewer crazy cults now, yet that gain has come at great cost: we have given up our sense of wonder at secrets left to be discovered. THE WORLD ACCORDING TO CONVENTION How must you see the world if you don’t believe in secrets? You’d have to believe we’ve already solved all great questions. If today’s conventions are correct, we can aﬀord to be smug and complacent: “God’s in His heaven, All’s right with the world.” For example, a world without secrets would enjoy a perfect understanding of justice. Every injustice necessarily involves a moral truth that very few people recognize early on: in a democratic society, a wrongful practice persists only when most people don’t perceive it to be unjust. At ﬁrst, only a small minority of abolitionists knew that slavery was evil; that view has rightly become conventional, but it was still a secret in the early 19th century. To say that there are no secrets left today would mean that we live in a society with no hidden injustices. In economics, disbelief in secrets leads to faith in eﬃcient markets. But the existence of financial bubbles shows that markets can have extraordinary ineﬃciencies. (And the more people believe in eﬃciency, the bigger the bubbles get.) In 1999, nobody wanted to believe that the internet was irrationally overvalued. The same was true of housing in 2005: Fed chairman Alan Greenspan had to acknowledge some “signs of froth in local markets” but stated that “a bubble in home prices for the nation as a whole does not appear likely.” The market reﬂected all knowable information and couldn’t be questioned. Then home prices fell across the country, and the ﬁnancial crisis of 2008 wiped out trillions. The future turned out to hold many secrets that economists could not make vanish simply by ignoring them. What happens when a company stops believing in secrets? The sad decline of Hewlett-Packard provides a cautionary tale. In 1990, the company was worth $9 billion. Then came a decade of invention. In 1991, HP released the DeskJet 500C, the world’s ﬁrst aﬀordable color printer. In 1993, it launched the OmniBook, one of the ﬁrst “superportable” laptops. The next year, HP released the OﬃceJet, the world’s ﬁrst all-in-one printer/fax/copier. This relentless product expansion paid oﬀ: by mid-2000, HP was worth $135 billion. But starting in late 1999, when HP introduced a new branding campaign around the imperative to “invent,” it stopped inventing things. In 2001, the company launched HP Services, a gloriﬁed consulting and support shop. In 2002, HP merged with Compaq, presumably because it didn’t know what else to do. By 2005, the company’s market cap had plunged to $70 billion—roughly half of what it had been just ﬁve years earlier. HP’s board was a microcosm of the dysfunction: it split into two factions, only one of which cared about new technology. That faction was led by Tom Perkins, an engineer who ﬁrst came to HP in 1963 to run the company’s research division at the personal request of Bill Hewlett and Dave Packard. At 73 years old in 2005, Perkins may as well have been a time-traveling visitor from a bygone age of optimism: he thought the board should identify the most promising new technologies and then have HP build them. But Perkins’s faction lost out to its rival, led by chairwoman Patricia Dunn. A banker by trade, Dunn argued that charting a plan for future technology was beyond the board’s competence. She thought the board should restrict itself to a night watchman’s role: Was everything proper in the accounting department? Were people following all the rules? Amid this inﬁghting, someone on the board started leaking information to the press. When it was exposed that Dunn arranged a series of illegal wiretaps to identify the source, the backlash was worse than the original dissension, and the board was disgraced. Having abandoned the search for technological secrets, HP obsessed over gossip. As a result, by late 2012 HP was worth just $23 billion—not much more than it was worth in 1990, adjusting for inﬂation. THE CASE FOR SECRETS You can’t ﬁnd secrets without looking for them. Andrew Wiles demonstrated this when he proved Fermat’s Last Theorem after 358 years of fruitless inquiry by other mathematicians—the kind of sustained failure that might have suggested an inherently impossible task. Pierre de Fermat had conjectured in 1637 that no integers a, b, and c could satisfy the equation an + bn = cn for any integer n greater than 2. He claimed to have a proof, but he died without writing it down, so his conjecture long remained a major unsolved problem in mathematics. Wiles started working on it in 1986, but he kept it a secret until 1993, when he knew he was nearing a solution. After nine years of hard work, Wiles proved the conjecture in 1995. He needed brilliance to succeed, but he also needed a faith in secrets. If you think something hard is impossible, you’ll never even start trying to achieve it. Belief in secrets is an eﬀective truth. The actual truth is that there are many more secrets left to ﬁnd, but they will yield only to relentless searchers. There is more to do in science, medicine, engineering, and in technology of all kinds. We are within reach not just of marginal goals set at the competitive edge of today’s conventional disciplines, but of ambitions so great that even the boldest minds of the Scientiﬁc Revolution hesitated to announce them directly. We could cure cancer, dementia, and all the diseases of age and metabolic decay. We can ﬁnd new ways to generate energy that free the world from conﬂict over fossil fuels. We can invent faster ways to travel from place to place over the surface of the planet; we can even learn how to escape it entirely and settle new frontiers. But we will never learn any of these secrets unless we demand to know them and force ourselves to look. The same is true of business. Great companies can be built on open but unsuspected secrets about how the world works. Consider the Silicon Valley startups that have harnessed the spare capacity that is all around us but often ignored. Before Airbnb, travelers had little choice but to pay high prices for a hotel room, and property owners couldn’t easily and reliably rent out their unoccupied space. Airbnb saw untapped supply and unaddressed demand where others saw nothing at all. The same is true of private car services Lyft and Uber. Few people imagined that it was possible to build a billion-dollar business by simply connecting people who want to go places with people willing to drive them there. We already had state-licensed taxicabs and private limousines; only by believing in and looking for secrets could you see beyond the convention to an opportunity hidden in plain sight. The same reason that so many internet companies, including Facebook, are often underestimated—their very simplicity—is itself an argument for secrets. If insights that look so elementary in retrospect can support important and valuable businesses, there must remain many great companies still to start. HOW TO FIND SECRETS There are two kinds of secrets: secrets of nature and secrets about people. Natural secrets exist all around us; to ﬁnd them, one must study some undiscovered aspect of the physical world. Secrets about people are diﬀerent: they are things that people don’t know about themselves or things they hide because they don’t want others to know. So when thinking about what kind of company to build, there are two distinct questions to ask: What secrets is nature not telling you? What secrets are people not telling you? It’s easy to assume that natural secrets are the most important: the people who look for them can sound intimidatingly authoritative. This is why physics PhDs are notoriously diﬃcult to work with—because they know the most fundamental truths, they think they know all truths. But does understanding electromagnetic theory automatically make you a great marriage counselor? Does a gravity theorist know more about your business than you do? At PayPal, I once interviewed a physics PhD for an engineering job. Halfway through my ﬁrst question, he shouted, “Stop! I already know what you’re going to ask!” But he was wrong. It was the easiest no-hire decision I’ve ever made. Secrets about people are relatively underappreciated. Maybe that’s because you don’t need a dozen years of higher education to ask the questions that uncover them: What are people not allowed to talk about? What is forbidden or taboo? Sometimes looking for natural secrets and looking for human secrets lead to the same truth. Consider the monopoly secret again: competition and capitalism are opposites. If you didn’t already know it, you could discover it the natural, empirical way: do a quantitative study of corporate proﬁts and you’ll see they’re eliminated by competition. But you could also take the human approach and ask: what are people running companies not allowed to say? You would notice that monopolists downplay their monopoly status to avoid scrutiny, while competitive ﬁrms strategically exaggerate their uniqueness. The diﬀerences between ﬁrms only seem small on the surface; in fact, they are enormous. The best place to look for secrets is where no one else is looking. Most people think only in terms of what they’ve been taught; schooling itself aims to impart conventional wisdom. So you might ask: are there any ﬁelds that matter but haven’t been standardized and institutionalized? Physics, for example, is a real major at all major universities, and it’s set in its ways. The opposite of physics might be astrology, but astrology doesn’t matter. What about something like nutrition? Nutrition matters for everybody, but you can’t major in it at Harvard. Most top scientists go into other ﬁelds. Most of the big studies were done 30 or 40 years ago, and most are seriously ﬂawed. The food pyramid that told us to eat low fat and enormous amounts of grains was probably more a product of lobbying by Big Food than real science; its chief impact has been to aggravate our obesity epidemic. There’s plenty more to learn: we know more about the physics of faraway stars than we know about human nutrition. It won’t be easy, but it’s not obviously impossible: exactly the kind of ﬁeld that could yield secrets. WHAT TO DO WITH SECRETS If you ﬁnd a secret, you face a choice: Do you tell anyone? Or do you keep it to yourself? It depends on the secret: some are more dangerous than others. As Faust tells Wagner: The few who knew what might be learned, Foolish enough to put their whole heart on show, And reveal their feelings to the crowd below, Mankind has always cruciﬁed and burned. Unless you have perfectly conventional beliefs, it’s rarely a good idea to tell everybody everything that you know. So who do you tell? Whoever you need to, and no more. In practice, there’s always a golden mean between telling nobody and telling everybody—and that’s a company. The best entrepreneurs know this: every great business is built around a secret that’s hidden from the outside. A great company is a conspiracy to change the world; when you share your secret, the recipient becomes a fellow conspirator. As Tolkien wrote in The Lord of the Rings: The Road goes ever on and on Down from the door where it began. Life is a long journey; the road marked out by the steps of previous travelers has no end in sight. But later on in the tale, another verse appears: Still round the corner there may wait A new road or a secret gate, And though we pass them by today, Tomorrow we may come this way And take the hidden paths that run Towards the Moon or to the Sun. The road doesn’t have to be inﬁnite after all. Take the hidden paths. 9 FOUNDATIONS EVERY GREAT COMPANY is unique, but there are a few things that every business must get right at the beginning. I stress this so often that friends have teasingly nicknamed it “Thiel’s law”: a startup messed up at its foundation cannot be ﬁxed. Beginnings are special. They are qualitatively diﬀerent from all that comes afterward. This was true 13.8 billion years ago, at the founding of our cosmos: in the earliest microseconds of its existence, the universe expanded by a factor of 1030—a million trillion trillion. As cosmogonic epochs came and went in those ﬁrst few moments, the very laws of physics were diﬀerent from those we know today. It was also true 227 years ago at the founding of our country: fundamental questions were open for debate by the Framers during the few months they spent together at the Constitutional Convention. How much power should the central government have? How should representation in Congress be apportioned? Whatever your views on the compromises reached that summer in Philadelphia, they’ve been hard to change ever since: after ratifying the Bill of Rights in 1791, we’ve amended the Constitution only 17 times. Today, California has the same representation in the Senate as Alaska, even though it has more than 50 times as many people. Maybe that’s a feature, not a bug. But we’re probably stuck with it as long as the United States exists. Another constitutional convention is unlikely; today we debate only smaller questions. Companies are like countries in this way. Bad decisions made early on—if you choose the wrong partners or hire the wrong people, for example—are very hard to correct after they are made. It may take a crisis on the order of bankruptcy before anybody will even try to correct them. As a founder, your ﬁrst job is to get the ﬁrst things right, because you cannot build a great company on a ﬂawed foundation. FOUNDING MATRIMONY When you start something, the ﬁrst and most crucial decision you make is whom to start it with. Choosing a co-founder is like getting married, and founder conﬂict is just as ugly as divorce. Optimism abounds at the start of every relationship. It’s unromantic to think soberly about what could go wrong, so people don’t. But if the founders develop irreconcilable diﬀerences, the company becomes the victim. In 1999, Luke Nosek was one of my co-founders at PayPal, and I still work with him today at Founders Fund. But a year before PayPal, I invested in a company Luke started with someone else. It was his ﬁrst startup; it was one of my ﬁrst investments. Neither of us realized it then, but the venture was doomed to fail from the beginning because Luke and his co-founder were a terrible match. Luke is a brilliant and eccentric thinker; his co-founder was an MBA type who didn’t want to miss out on the ’90s gold rush. They met at a networking event, talked for a while, and decided to start a company together. That’s no better than marrying the ﬁrst person you meet at the slot machines in Vegas: you might hit the jackpot, but it probably won’t work. Their company blew up and I lost my money. Now when I consider investing in a startup, I study the founding teams. Technical abilities and complementary skill sets matter, but how well the founders know each other and how well they work together matter just as much. Founders should share a prehistory before they start a company together—otherwise they’re just rolling dice. OWNERSHIP, POSSESSION, AND CONTROL It’s not just founders who need to get along. Everyone in your company needs to work well together. A Silicon Valley libertarian might say you could solve this problem by restricting yourself to a sole proprietorship. Freud, Jung, and every other psychologist has a theory about how every individual mind is divided against itself, but in business at least, working for yourself guarantees alignment. Unfortunately, it also limits what kind of company you can build. It’s very hard to go from 0 to 1 without a team. A Silicon Valley anarchist might say you could achieve perfect alignment as long as you hire just the right people, who will ﬂourish peacefully without any guiding structure. Serendipity and even free- form chaos at the workplace are supposed to help “disrupt” all the old rules made and obeyed by the rest of the world. And indeed, “if men were angels, no government would be necessary.” But anarchic companies miss what James Madison saw: men aren’t angels. That’s why executives who manage companies and directors who govern them have separate roles to play; it’s also why founders’ and investors’ claims on a company are formally deﬁned. You need good people who get along, but you also need a structure to help keep everyone aligned for the long term. To anticipate likely sources of misalignment in any company, it’s useful to distinguish between three concepts: Ownership: who legally owns a company’s equity? Possession: who actually runs the company on a day-to-day basis? Control: who formally governs the company’s aﬀairs? A typical startup allocates ownership among founders, employees, and investors. The managers and employees who operate the company enjoy possession. And a board of directors, usually comprising founders and investors, exercises control. In theory, this division works smoothly. Financial upside from part ownership attracts and rewards investors and workers. Eﬀective possession motivates and empowers founders and employees—it means they can get stuﬀ done. Oversight from the board places managers’ plans in a broader perspective. In practice, distributing these functions among diﬀerent people makes sense, but it also multiplies opportunities for misalignment. To see misalignment at its most extreme, just visit the DMV. Suppose you need a new driver’s license. Theoretically, it should be easy to get one. The DMV is a government agency, and we live in a democratic republic. All power resides in “the people,” who elect representatives to serve them in government. If you’re a citizen, you’re a part owner of the DMV and your representatives control it, so you should be able to walk in and get what you need. Of course, it doesn’t work like that. We the people may “own” the DMV’s resources, but that ownership is merely ﬁctional. The clerks and petty tyrants who operate the DMV, however, enjoy very real possession of their small-time powers. Even the governor and the legislature charged with nominal control over the DMV can’t change anything. The bureaucracy lurches ever sideways of its own inertia no matter what actions elected oﬃcials take. Accountable to nobody, the DMV is misaligned with everybody. Bureaucrats can make your licensing experience pleasurable or nightmarish at their sole discretion. You can try to bring up political theory and remind them that you are the boss, but that’s unlikely to get you better service. Big corporations do better than the DMV, but they’re still prone to misalignment, especially between ownership and possession. The CEO of a huge company like General Motors, for example, will own some of the company’s stock, but only a trivial portion of the total. Therefore he’s incentivized to reward himself through the power of possession rather than the value of ownership. Posting good quarterly results will be enough for him to keep his high salary and corporate jet. Misalignment can creep in even if he receives stock compensation in the name of “shareholder value.” If that stock comes as a reward for short-term performance, he will ﬁnd it more lucrative and much easier to cut costs instead of investing in a plan that might create more value for all shareholders far in the future. Unlike corporate giants, early-stage startups are small enough that founders usually have both ownership and possession. Most conﬂicts in a startup erupt between ownership and control—that is, between founders and investors on the board. The potential for conﬂict increases over time as interests diverge: a board member might want to take a company public as soon as possible to score a win for his venture ﬁrm, while the founders would prefer to stay private and grow the business. In the boardroom, less is more. The smaller the board, the easier it is for the directors to communicate, to reach consensus, and to exercise eﬀective oversight. However, that very eﬀectiveness means that a small board can forcefully oppose management in any conﬂict. This is why it’s crucial to choose wisely: every single member of your board matters. Even one problem director will cause you pain, and may even jeopardize your company’s future. A board of three is ideal. Your board should never exceed ﬁve people, unless your company is publicly held. (Government regulations eﬀectively mandate that public companies have larger boards—the average is nine members.) By far the worst you can do is to make your board extra large. When unsavvy observers see a nonproﬁt organization with dozens of people on its board, they think: “Look how many great people are committed to this organization! It must be extremely well run.” Actually, a huge board will exercise no eﬀective oversight at all; it merely provides cover for whatever microdictator actually runs the organization. If you want that kind of free rein from your board, blow it up to giant size. If you want an eﬀective board, keep it small. ON THE BUS OR OFF THE BUS As a general rule, everyone you involve with your company should be involved full-time. Sometimes you’ll have to break this rule; it usually makes sense to hire outside lawyers and accountants, for example. However, anyone who doesn’t own stock options or draw a regular salary from your company is fundamentally misaligned. At the margin, they’ll be biased to claim value in the near term, not help you create more in the future. That’s why hiring consultants doesn’t work. Part- time employees don’t work. Even working remotely should be avoided, because misalignment can creep in whenever colleagues aren’t together full-time, in the same place, every day. If you’re deciding whether to bring someone on board, the decision is binary. Ken Kesey was right: you’re either on the bus or oﬀ the bus. CASH IS NOT KING For people to be fully committed, they should be properly compensated. Whenever an entrepreneur asks me to invest in his company, I ask him how much he intends to pay himself. A company does better the less it pays the CEO—that’s one of the single clearest patterns I’ve noticed from investing in hundreds of startups. In no case should a CEO of an early-stage, venture-backed startup receive more than $150,000 per year in salary. It doesn’t matter if he got used to making much more than that at Google or if he has a large mortgage and hefty private school tuition bills. If a CEO collects $300,000 per year, he risks becoming more like a politician than a founder. High pay incentivizes him to defend the status quo along with his salary, not to work with everyone else to surface problems and ﬁx them aggressively. A cash-poor executive, by contrast, will focus on increasing the value of the company as a whole. Low CEO pay also sets the standard for everyone else. Aaron Levie, the CEO of Box, was always careful to pay himself less than everyone else in the company—four years after he started Box, he was still living two blocks away from HQ in a one-bedroom apartment with no furniture except a mattress. Every employee noticed his obvious commitment to the company’s mission and emulated it. If a CEO doesn’t set an example by taking the lowest salary in the company, he can do the same thing by drawing the highest salary. So long as that ﬁgure is still modest, it sets an eﬀective ceiling on cash compensation. Cash is attractive. It oﬀers pure optionality: once you get your paycheck, you can do anything you want with it. However, high cash compensation teaches workers to claim value from the company as it already exists instead of investing their time to create new value in the future. A cash bonus is slightly better than a cash salary—at least it’s contingent on a job well done. But even so-called incentive pay encourages short-term thinking and value grabbing. Any kind of cash is more about the present than the future. VESTED INTERESTS Startups don’t need to pay high salaries because they can oﬀer something better: part ownership of the company itself. Equity is the one form of compensation that can eﬀectively orient people toward creating value in the future. However, for equity to create commitment rather than conﬂict, you must allocate it very carefully. Giving everyone equal shares is usually a mistake: every individual has diﬀerent talents and responsibilities as well as diﬀerent opportunity costs, so equal amounts will seem arbitrary and unfair from the start. On the other hand, granting diﬀerent amounts up front is just as sure to seem unfair. Resentment at this stage can kill a company, but there’s no ownership formula to perfectly avoid it. This problem becomes even more acute over time as more people join the company. Early employees usually get the most equity because they take more risk, but some later employees might be even more crucial to a venture’s success. A secretary who joined eBay in 1996 might have made 200 times more than her industry-veteran boss who joined in 1999. The graﬃti artist who painted Facebook’s oﬃce walls in 2005 got stock that turned out to be worth $200 million, while a talented engineer who joined in 2010 might have made only $2 million. Since it’s impossible to achieve perfect fairness when distributing ownership, founders would do well to keep the details secret. Sending out a company-wide email that lists everyone’s ownership stake would be like dropping a nuclear bomb on your oﬃce. Most people don’t want equity at all. At PayPal, we once hired a consultant who promised to help us negotiate lucrative business development deals. The only thing he ever successfully negotiated was a $5,000 daily cash salary; he refused to accept stock options as payment. Stories of startup chefs becoming millionaires notwithstanding, people often ﬁnd equity unattractive. It’s not liquid like cash. It’s tied to one speciﬁc company. And if that company doesn’t succeed, it’s worthless. Equity is a powerful tool precisely because of these limitations. Anyone who prefers owning a part of your company to being paid in cash reveals a preference for the long term and a commitment to increasing your company’s value in the future. Equity can’t create perfect incentives, but it’s the best way for a founder to keep everyone in the company broadly aligned. EXTENDING THE FOUNDING Bob Dylan has said that he who is not busy being born is busy dying. If he’s right, being born doesn’t happen at just one moment—you might even continue to do it somehow, poetically at least. The founding moment of a company, however, really does happen just once: only at the very start do you have the opportunity to set the rules that will align people toward the creation of value in the future. The most valuable kind of company maintains an openness to invention that is most characteristic of beginnings. This leads to a second, less obvious understanding of the founding: it lasts as long as a company is creating new things, and it ends when creation stops. If you get the founding moment right, you can do more than create a valuable company: you can steer its distant future toward the creation of new things instead of the stewardship of inherited success. You might even extend its founding indeﬁnitely. 10 THE MECHANICS OF MAFIA START WITH A THOUGHT EXPERIMENT: what would the ideal company culture look like? Employees should love their work. They should enjoy going to the oﬃce so much that formal business hours become obsolete and nobody watches the clock. The workspace should be open, not cubicled, and workers should feel at home: beanbag chairs and Ping-Pong tables might outnumber ﬁle cabinets. Free massages, on-site sushi chefs, and maybe even yoga classes would sweeten the scene. Pets should be welcome, too: perhaps employees’ dogs and cats could come and join the oﬃce’s tankful of tropical ﬁsh as unoﬃcial company mascots. What’s wrong with this picture? It includes some of the absurd perks Silicon Valley has made famous, but none of the substance—and without substance perks don’t work. You can’t accomplish anything meaningful by hiring an interior decorator to beautify your oﬃce, a “human resources” consultant to ﬁx your policies, or a branding specialist to hone your buzzwords. “Company culture” doesn’t exist apart from the company itself: no company has a culture; every company is a culture. A startup is a team of people on a mission, and a good culture is just what that looks like on the inside. BEYOND PROFESSIONALISM The ﬁrst team that I built has become known in Silicon Valley as the “PayPal Maﬁa” because so many of my former colleagues have gone on to help each other start and invest in successful tech companies. We sold PayPal to eBay for $1.5 billion in 2002. Since then, Elon Musk has founded SpaceX and co-founded Tesla Motors; Reid Hoﬀman co- founded LinkedIn; Steve Chen, Chad Hurley, and Jawed Karim together founded YouTube; Jeremy Stoppelman and Russel Simmons founded Yelp; David Sacks co-founded Yammer; and I co-founded Palantir. Today all seven of those companies are worth more than $1 billion each. PayPal’s oﬃce amenities never got much press, but the team has done extraordinarily well, both together and individually: the culture was strong enough to transcend the original company. We didn’t assemble a maﬁa by sorting through résumés and simply hiring the most talented people. I had seen the mixed results of that approach ﬁrsthand when I worked at a New York law ﬁrm. The lawyers I worked with ran a valuable business, and they were impressive individuals one by one. But the relationships between them were oddly thin. They spent all day together, but few of them seemed to have much to say to each other outside the oﬃce. Why work with a group of people who don’t even like each other? Many seem to think it’s a sacriﬁce necessary for making money. But taking a merely professional view of the workplace, in which free agents check in and out on a transactional basis, is worse than cold: it’s not even rational. Since time is your most valuable asset, it’s odd to spend it working with people who don’t envision any long-term future together. If you can’t count durable relationships among the fruits of your time at work, you haven’t invested your time well—even in purely ﬁnancial terms. From the start, I wanted PayPal to be tightly knit instead of transactional. I thought stronger relationships would make us not just happier and better at work but also more successful in our careers even beyond PayPal. So we set out to hire people who would actually enjoy working together. They had to be talented, but even more than that they had to be excited about working speciﬁcally with us. That was the start of the PayPal Maﬁa. RECRUITING CONSPIRATORS Recruiting is a core competency for any company. It should never be outsourced. You need people who are not just skilled on paper but who will work together cohesively after they’re hired. The ﬁrst four or ﬁve might be attracted by large equity stakes or high-proﬁle responsibilities. More important than those obvious oﬀerings is your answer to this question: Why should the 20th employee join your company? Talented people don’t need to work for you; they have plenty of options. You should ask yourself a more pointed version of the question: Why would someone join your company as its 20th engineer when she could go work at Google for more money and more prestige? Here are some bad answers: “Your stock options will be worth more here than elsewhere.” “You’ll get to work with the smartest people in the world.” “You can help solve the world’s most challenging problems.” What’s wrong with valuable stock, smart people, or pressing problems? Nothing—but every company makes these same claims, so they won’t help you stand out. General and undiﬀerentiated pitches don’t say anything about why a recruit should join your company instead of many others. The only good answers are speciﬁc to your company, so you won’t ﬁnd them in this book. But there are two general kinds of good answers: answers about your mission and answers about your team. You’ll attract the employees you need if you can explain why your mission is compelling: not why it’s important in general, but why you’re doing something important that no one else is going to get done. That’s the only thing that can make its importance unique. At PayPal, if you were excited by the idea of creating a new digital currency to replace the U.S. dollar, we wanted to talk to you; if not, you weren’t the right ﬁt. However, even a great mission is not enough. The kind of recruit who would be most engaged as an employee will also wonder: “Are these the kind of people I want to work with?” You should be able to explain why your company is a unique match for him personally. And if you can’t do that, he’s probably not the right match. Above all, don’t ﬁght the perk war. Anybody who would be more powerfully swayed by free laundry pickup or pet day care would be a bad addition to your team. Just cover the basics like health insurance and then promise what no others can: the opportunity to do irreplaceable work on a unique problem alongside great people. You probably can’t be the Google of 2014 in terms of compensation or perks, but you can be like the Google of 1999 if you already have good answers about your mission and team. WHAT’S UNDER SILICON VALLEY’S HOODIES From the outside, everyone in your company should be diﬀerent in the same way. Unlike people on the East Coast, who all wear the same skinny jeans or pinstripe suits depending on their industry, young people in Mountain View and Palo Alto go to work wearing T-shirts. It’s a cliché that tech workers don’t care about what they wear, but if you look closely at those T-shirts, you’ll see the logos of the wearers’ companies —and tech workers care about those very much. What makes a startup employee instantly distinguishable to outsiders is the branded T-shirt or hoodie that makes him look the same as his co-workers. The startup uniform encapsulates a simple but essential principle: everyone at your company should be diﬀerent in the same way—a tribe of like-minded people ﬁercely devoted to the company’s mission. Max Levchin, my co-founder at PayPal, says that startups should make their early staﬀ as personally similar as possible. Startups have limited resources and small teams. They must work quickly and eﬃciently in order to survive, and that’s easier to do when everyone shares an understanding of the world. The early PayPal team worked well together because we were all the same kind of nerd. We all loved science ﬁction: Cryptonomicon was required reading, and we preferred the capitalist Star Wars to the communist Star Trek. Most important, we were all obsessed with creating a digital currency that would be controlled by individuals instead of governments. For the company to work, it didn’t matter what people looked like or which country they came from, but we needed every new hire to be equally obsessed. DO ONE THING On the inside, every individual should be sharply distinguished by her work. When assigning responsibilities to employees in a startup, you could start by treating it as a simple optimization problem to eﬃciently match talents with tasks. But even if you could somehow get this perfectly right, any given solution would quickly break down. Partly that’s because startups have to move fast, so individual roles can’t remain static for long. But it’s also because job assignments aren’t just about the relationships between workers and tasks; they’re also about relationships between employees. The best thing I did as a manager at PayPal was to make every person in the company responsible for doing just one thing. Every employee’s one thing was unique, and everyone knew I would evaluate him only on that one thing. I had started doing this just to simplify the task of managing people. But then I noticed a deeper result: deﬁning roles reduced conﬂict. Most ﬁghts inside a company happen when colleagues compete for the same responsibilities. Startups face an especially high risk of this since job roles are ﬂuid at the early stages. Eliminating competition makes it easier for everyone to build the kinds of long-term relationships that transcend mere professionalism. More than that, internal peace is what enables a startup to survive at all. When a startup fails, we often imagine it succumbing to predatory rivals in a competitive ecosystem. But every company is also its own ecosystem, and factional strife makes it vulnerable to outside threats. Internal conﬂict is like an autoimmune disease: the technical cause of death may be pneumonia, but the real cause remains hidden from plain view. OF CULTS AND CONSULTANTS In the most intense kind of organization, members hang out only with other members. They ignore their families and abandon the outside world. In exchange, they experience strong feelings of belonging, and maybe get access to esoteric “truths” denied to ordinary people. We have a word for such organizations: cults. Cultures of total dedication look crazy from the outside, partly because the most notorious cults were homicidal: Jim Jones and Charles Manson did not make good exits. But entrepreneurs should take cultures of extreme dedication seriously. Is a lukewarm attitude to one’s work a sign of mental health? Is a merely professional attitude the only sane approach? The extreme opposite of a cult is a consulting ﬁrm like Accenture: not only does it lack a distinctive mission of its own, but individual consultants are regularly dropping in and out of companies to which they have no long-term connection whatsoever. Every company culture can be plotted on a linear spectrum: The best startups might be considered slightly less extreme kinds of cults. The biggest diﬀerence is that cults tend to be fanatically wrong about something important. People at a successful startup are fanatically right about something those outside it have missed. You’re not going to learn those kinds of secrets from consultants, and you don’t need to worry if your company doesn’t make sense to conventional professionals. Better to be called a cult—or even a maﬁa. 11 IF YOU BUILD IT, WILL THEY COME? EVEN THOUGH SALES is everywhere, most people underrate its importance. Silicon Valley underrates it more than most. The geek classic The Hitchhiker’s Guide to the Galaxy even explains the founding of our planet as a reaction against salesmen. When an imminent catastrophe requires the evacuation of humanity’s original home, the population escapes on three giant ships. The thinkers, leaders, and achievers take the A Ship; the salespeople and consultants get the B Ship; and the workers and artisans take the C Ship. The B Ship leaves ﬁrst, and all its passengers rejoice vainly. But the salespeople don’t realize they are caught in a ruse: the A Ship and C Ship people had always thought that the B Ship people were useless, so they conspired to get rid of them. And it was the B Ship that landed on Earth. Distribution may not matter in ﬁctional worlds, but it matters in ours. We underestimate the importance of distribution—a catchall term for everything it takes to sell a product—because we share the same bias the A Ship and C Ship people had: salespeople and other “middlemen” supposedly get in the way, and distribution should ﬂow magically from the creation of a good product. The Field of Dreams conceit is especially popular in Silicon Valley, where engineers are biased toward building cool stuﬀ rather than selling it. But customers will not come just because you build it. You have to make that happen, and it’s harder than it looks. NERDS VS. SALESMEN The U.S. advertising industry collects annual revenues of $150 billion and employs more than 600,000 people. At $450 billion annually, the U.S. sales industry is even bigger. When they hear that 3.2 million Americans work in sales, seasoned executives will suspect the number is low, but engineers may sigh in bewilderment. What could that many salespeople possibly be doing? In Silicon Valley, nerds are skeptical of advertising, marketing, and sales because they seem superﬁcial and irrational. But advertising matters because it works. It works on nerds, and it works on you. You may think that you’re an exception; that your preferences are authentic, and advertising only works on other people. It’s easy to resist the most obvious sales pitches, so we entertain a false conﬁdence in our own independence of mind. But advertising doesn’t exist to make you buy a product right away; it exists to embed subtle impressions that will drive sales later. Anyone who can’t acknowledge its likely eﬀect on himself is doubly deceived. Nerds are used to transparency. They add value by becoming expert at a technical skill like computer programming. In engineering disciplines, a solution either works or it fails. You can evaluate someone else’s work with relative ease, as surface appearances don’t matter much. Sales is the opposite: an orchestrated campaign to change surface appearances without changing the underlying reality. This strikes engineers as trivial if not fundamentally dishonest. They know their own jobs are hard, so when they look at salespeople laughing on the phone with a customer or going to two-hour lunches, they suspect that no real work is being done. If anything, people overestimate the relative diﬃculty of science and engineering, because the challenges of those ﬁelds are obvious. What nerds miss is that it takes hard work to make sales look easy. SALES IS HIDDEN All salesmen are actors: their priority is persuasion, not sincerity. That’s why the word “salesman” can be a slur and the used car dealer is our archetype of shadiness. But we only react negatively to awkward, obvious salesmen—that is, the bad ones. There’s a wide range of sales ability: there are many gradations between novices, experts, and masters. There are even sales grandmasters. If you don’t know any grandmasters, it’s not because you haven’t encountered them, but rather because their art is hidden in plain sight. Tom Sawyer managed to persuade his neighborhood friends to whitewash the fence for him— a masterful move. But convincing them to actually pay him for the privilege of doing his chores was the move of a grandmaster, and his friends were none the wiser. Not much has changed since Twain wrote in 1876. Like acting, sales works best when hidden. This explains why almost everyone whose job involves distribution—whether they’re in sales, marketing, or advertising—has a job title that has nothing to do with those things. People who sell advertising are called “account executives.” People who sell customers work in “business development.” People who sell companies are “investment bankers.” And people who sell themselves are called “politicians.” There’s a reason for these redescriptions: none of us wants to be reminded when we’re being sold. Whatever the career, sales ability distinguishes superstars from also- rans. On Wall Street, a new hire starts as an “analyst” wielding technical expertise, but his goal is to become a dealmaker. A lawyer prides himself on professional credentials, but law ﬁrms are led by the rainmakers who bring in big clients. Even university professors, who claim authority from scholarly achievement, are envious of the self- promoters who deﬁne their ﬁelds. Academic ideas about history or English don’t just sell themselves on their intellectual merits. Even the agenda of fundamental physics and the future path of cancer research are results of persuasion. The most fundamental reason that even businesspeople underestimate the importance of sales is the systematic eﬀort to hide it at every level of every ﬁeld in a world secretly driven by it. The engineer’s grail is a product great enough that “it sells itself.” But anyone who would actually say this about a real product must be lying: either he’s delusional (lying to himself) or he’s selling something (and thereby contradicting himself). The polar opposite business cliché warns that “the best product doesn’t always win.” Economists attribute this to “path dependence”: speciﬁc historical circumstances independent of objective quality can determine which products enjoy widespread adoption. That’s true, but it doesn’t mean the operating systems we use today and the keyboard layouts on which we type were imposed by mere chance. It’s better to think of distribution as something essential to the design of your product. If you’ve invented something new but you haven’t invented an eﬀective way to sell it, you have a bad business—no matter how good the product. HOW TO SELL A PRODUCT Superior sales and distribution by itself can create a monopoly, even with no product diﬀerentiation. The converse is not true. No matter how strong your product—even if it easily ﬁts into already established habits and anybody who tries it likes it immediately—you must still support it with a strong distribution plan. Two metrics set the limits for eﬀective distribution. The total net proﬁt that you earn on average over the course of your relationship with a customer (Customer Lifetime Value, or CLV) must exceed the amount you spend on average to acquire a new customer (Customer Acquisition Cost, or CAC). In general, the higher the price of your product, the more you have to spend to make a sale—and the more it makes sense to spend it. Distribution methods can be plotted on a continuum: Complex Sales If your average sale is seven ﬁgures or more, every detail of every deal requires close personal attention. It might take months to develop the right relationships. You might make a sale only once every year or two. Then you’ll usually have to follow up during installation and service the product long after the deal is done. It’s hard to do, but this kind of “complex sales” is the only way to sell some of the most valuable products. SpaceX shows that it can be done. Within just a few years of launching his rocket startup, Elon Musk persuaded NASA to sign billion-dollar contracts to replace the decommissioned space shuttle with a newly designed vessel from SpaceX. Politics matters in big deals just as much as technological ingenuity, so this wasn’t easy. SpaceX employs more than 3,000 people, mostly in California. The traditional U.S. aerospace industry employs more than 500,000 people, spread throughout all 50 states. Unsurprisingly, members of Congress don’t want to give up federal funds going to their home districts. But since complex sales requires making just a few deals each year, a sales grandmaster like Elon Musk can use that time to focus on the most crucial people—and even to overcome political inertia. Complex sales works best when you don’t have “salesmen” at all. Palantir, the data analytics company I co-founded with my law school classmate Alex Karp, doesn’t employ anyone separately tasked with selling its product. Instead, Alex, who is Palantir’s CEO, spends 25 days a month on the road, meeting with clients and potential clients. Our deal sizes range from $1 million to $100 million. At that price point, buyers want to talk to the CEO, not the VP of Sales. Businesses with complex sales models succeed if they achieve 50% to 100% year-over-year growth over the course of a decade. This will seem slow to any entrepreneur dreaming of viral growth. You might expect revenue to increase 10x as soon as customers learn about an obviously superior product, but that almost never happens. Good enterprise sales strategy starts small, as it must: a new customer might agree to become your biggest customer, but they’ll rarely be comfortable signing a deal completely out of scale with what you’ve sold before. Once you have a pool of reference customers who are successfully using your product, then you can begin the long and methodical work of hustling toward ever bigger deals. Personal Sales Most sales are not particularly complex: average deal sizes might range between $10,000 and $100,000, and usually the CEO won’t have to do all the selling himself. The challenge here isn’t about how to make any particular sale, but how to establish a process by which a sales team of modest size can move the product to a wide audience. In 2008, Box had a good way for companies to store their data safely and accessibly in the cloud. But people didn’t know they needed such a thing—cloud computing hadn’t caught on yet. That summer, Blake was hired as Box’s third salesperson to help change that. Starting with small groups of users who had the most acute ﬁle sharing problems, Box’s sales reps built relationships with more and more users in each client company. In 2009, Blake sold a small Box account to the Stanford Sleep Clinic, where researchers needed an easy, secure way to store experimental data logs. Today the university oﬀers a Stanford-branded Box account to every one of its students and faculty members, and Stanford Hospital runs on Box. If it had started oﬀ by trying to sell the president of the university on an enterprise-wide solution, Box would have sold nothing. A complex sales approach would have made Box a forgotten startup failure; instead, personal sales made it a multibillion- dollar business. Sometimes the product itself is a kind of distribution. ZocDoc is a Founders Fund portfolio company that helps people ﬁnd and book medical appointments online. The company charges doctors a few hundred dollars per month to be included in its network. With an average deal size of just a few thousand dollars, ZocDoc needs lots of salespeople—so many that they have an internal recruiting team to do nothing but hire more. But making personal sales to doctors doesn’t just bring in revenue; by adding doctors to the network, salespeople make the product more valuable to consumers (and more consumer users increases its appeal to doctors). More than 5 million people already use the service each month, and if it can continue to scale its network to include a majority of practitioners, it will become a fundamental utility for the U.S. health care industry. Distribution Doldrums In between personal sales (salespeople obviously required) and traditional advertising (no salespeople required) there is a dead zone. Suppose you create a software service that helps convenience store owners track their inventory and manage ordering. For a product priced around $1,000, there might be no good distribution channel to reach the small businesses that might buy it. Even if you have a clear value proposition, how do you get people to hear it? Advertising would either be too broad (there’s no TV channel that only convenience store owners watch) or too ineﬃcient (on its own, an ad in Convenience Store News probably won’t convince any owner to part with $1,000 a year). The product needs a personal sales eﬀort, but at that price point, you simply don’t have the resources to send an actual person to talk to every prospective customer. This is why so many small and medium-sized businesses don’t use tools that bigger ﬁrms take for granted. It’s not that small business proprietors are unusually backward or that good tools don’t exist: distribution is the hidden bottleneck. Marketing and Advertising Marketing and advertising work for relatively low-priced products that have mass appeal but lack any method of viral distribution. Procter & Gamble can’t aﬀord to pay salespeople to go door-to-door selling laundry detergent. (P&G does employ salespeople to talk to grocery chains and large retail outlets, since one detergent sale made to these buyers might mean 100,000 one-gallon bottles.) To reach its end user, a packaged goods company has to produce television commercials, print coupons in newspapers, and design its product boxes to attract attention. Advertising can work for startups, too, but only when your customer acquisition costs and customer lifetime value make every other distribution channel uneconomical. Consider e-commerce startup Warby Parker, which designs and sells fashionable prescription eyeglasses online instead of contracting sales out to retail eyewear distributors. Each pair starts at around $100, so assuming the average customer buys a few pairs in her lifetime, the company’s CLV is a few hundred dollars. That’s too little to justify personal attention on every transaction, but at the other extreme, hundred-dollar physical products don’t exactly go viral. By running advertisements and creating quirky TV commercials, Warby is able to get its better, less expensive oﬀerings in front of millions of eyeglass-wearing customers. The company states plainly on its website that “TV is a great big megaphone,” and when you can only aﬀord to spend dozens of dollars acquiring a new customer, you need the biggest megaphone you can ﬁnd. Every entrepreneur envies a recognizable ad campaign, but startups should resist the temptation to compete with bigger companies in the endless contest to put on the most memorable TV spots or the most elaborate PR stunts. I know this from experience. At PayPal we hired James Doohan, who played Scotty on Star Trek, to be our oﬃcial spokesman. When we released our ﬁrst software for the PalmPilot, we invited journalists to an event where they could hear James recite this immortal line: “I’ve been beaming people up my whole career, but this is the ﬁrst time I’ve ever been able to beam money!” It ﬂopped—the few who actually came to cover the event weren’t impressed. We were all nerds, so we had thought Scotty the Chief Engineer could speak with more authority than, say, Captain Kirk. (Just like a salesman, Kirk was always showboating out in some exotic locale and leaving it up to the engineers to bail him out of his own mistakes.) We were wrong: when Priceline.com cast William Shatner (the actor who played Kirk) in a famous series of TV spots, it worked for them. But by then Priceline was a major player. No early-stage startup can match big companies’ advertising budgets. Captain Kirk truly is in a league of his own. Viral Marketing A product is viral if its core functionality encourages users to invite their friends to become users too. This is how Facebook and PayPal both grew quickly: every time someone shares with a friend or makes a payment, they naturally invite more and more people into the network. This isn’t just cheap—it’s fast, too. If every new user leads to more than one additional user, you can achieve a chain reaction of exponential growth. The ideal viral loop should be as quick and frictionless as possible. Funny YouTube videos or internet memes get millions of views very quickly because they have extremely short cycle times: people see the kitten, feel warm inside, and forward it to their friends in a matter of seconds. At PayPal, our initial user base was 24 people, all of whom worked at PayPal. Acquiring customers through banner advertising proved too expensive. However, by directly paying people to sign up and then paying them more to refer friends, we achieved extraordinary growth. This strategy cost us $20 per customer, but it also led to 7% daily growth, which meant that our user base nearly doubled every 10 days. After four or ﬁve months, we had hundreds of thousands of users and a viable opportunity to build a great company by servicing money transfers for small fees that ended up greatly exceeding our customer acquisition cost. Whoever is ﬁrst to dominate the most important segment of a market with viral potential will be the last mover in the whole market. At PayPal we didn’t want to acquire more users at random; we wanted to get the most valuable users ﬁrst. The most obvious market segment in email-based payments was the millions of emigrants still using Western Union to wire money to their families back home. Our product made that eﬀortless, but the transactions were too infrequent. We needed a smaller niche market segment with a higher velocity of money—a segment we found in eBay “PowerSellers,” the professional vendors who sold goods online through eBay’s auction marketplace. There were 20,000 of them. Most had multiple auctions ending each day, and they bought almost as much as they sold, which meant a constant stream of payments. And because eBay’s own solution to the payment problem was terrible, these merchants were extremely enthusiastic early adopters. Once PayPal dominated this segment and became the payments platform for eBay, there was no catching up—on eBay or anywhere else. The Power Law of Distribution One of these methods is likely to be far more powerful than every other for any given business: distribution follows a power law of its own. This is counterintuitive for most entrepreneurs, who assume that more is more. But the kitchen sink approach—employ a few salespeople, place some magazine ads, and try to add some kind of viral functionality to the product as an afterthought—doesn’t work. Most businesses get zero distribution channels to work: poor sales rather than bad product is the most common cause of failure. If you can get just one distribution channel to work, you have a great business. If you try for several but don’t nail one, you’re ﬁnished. Selling to Non-Customers Your company needs to sell more than its product. You must also sell your company to employees and investors. There is a “human resources” version of the lie that great products sell themselves: “This company is so good that people will be clamoring to join it.” And there’s a fundraising version too: “This company is so great that investors will be banging down our door to invest.” Clamor and frenzy are very real, but they rarely happen without calculated recruiting and pitching beneath the surface. Selling your company to the media is a necessary part of selling it to everyone else. Nerds who instinctively mistrust the media often make the mistake of trying to ignore it. But just as you can never expect people to buy a superior product merely on its obvious merits without any distribution strategy, you should never assume that people will admire your company without a public relations strategy. Even if your particular product doesn’t need media exposure to acquire customers because you have a viral distribution strategy, the press can help attract investors and employees. Any prospective employee worth hiring will do his own diligence; what he ﬁnds or doesn’t ﬁnd when he googles you will be critical to the success of your company. EVERYBODY SELLS Nerds might wish that distribution could be ignored and salesmen banished to another planet. All of us want to believe that we make up our own minds, that sales doesn’t work on us. But it’s not true. Everybody has a product to sell—no matter whether you’re an employee, a founder, or an investor. It’s true even if your company consists of just you and your computer. Look around. If you don’t see any salespeople, you’re the salesperson. 12 MAN AND MACHINE AS MATURE INDUSTRIES stagnate, information technology has advanced so rapidly that it has now become synonymous with “technology” itself. Today, more than 1.5 billion people enjoy instant access to the world’s knowledge using pocket-sized devices. Every one of today’s smartphones has thousands of times more processing power than the computers that guided astronauts to the moon. And if Moore’s law continues apace, tomorrow’s computers will be even more powerful. Computers already have enough power to outperform people in activities we used to think of as distinctively human. In 1997, IBM’s Deep Blue defeated world chess champion Garry Kasparov. Jeopardy!’s best-ever contestant, Ken Jennings, succumbed to IBM’s Watson in 2011. And Google’s self-driving cars are already on California roads today. Dale Earnhardt Jr. needn’t feel threatened by them, but the Guardian worries (on behalf of the millions of chauﬀeurs and cabbies in the world) that self-driving cars “could drive the next wave of unemployment.” Everyone expects computers to do more in the future—so much more that some wonder: 30 years from now, will there be anything left for people to do? “Software is eating the world,” venture capitalist Marc Andreessen has announced with a tone of inevitability. VC Andy Kessler sounds almost gleeful when he explains that the best way to create productivity is “to get rid of people.” Forbes captured a more anxious attitude when it asked readers: Will a machine replace you? Futurists can seem like they hope the answer is yes. Luddites are so worried about being replaced that they would rather we stop building new technology altogether. Neither side questions the premise that better computers will necessarily replace human workers. But that premise is wrong: computers are complements for humans, not substitutes. The most valuable businesses of coming decades will be built by entrepreneurs who seek to empower people rather than try to make them obsolete. SUBSTITUTION VS. COMPLEMENTARITY Fifteen years ago, American workers were worried about competition from cheaper Mexican substitutes. And that made sense, because humans really can substitute for each other. Today people think they can hear Ross Perot’s “giant sucking sound” once more, but they trace it back to server farms somewhere in Texas instead of cut-rate factories in Tijuana. Americans fear technology in the near future because they see it as a replay of the globalization of the near past. But the situations are very diﬀerent: people compete for jobs and for resources; computers compete for neither. Globalization Means Substitution When Perot warned about foreign competition, both George H. W. Bush and Bill Clinton preached the gospel of free trade: since every person has a relative strength at some particular job, in theory the economy maximizes wealth when people specialize according to their advantages and then trade with each other. In practice, it’s not unambiguously clear how well free trade has worked, for many workers at least. Gains from trade are greatest when there’s a big discrepancy in comparative advantage, but the global supply of workers willing to do repetitive tasks for an extremely small wage is extremely large. People don’t just compete to supply labor; they also demand the same resources. While American consumers have beneﬁted from access to cheap toys and textiles from China, they’ve had to pay higher prices for the gasoline newly desired by millions of Chinese motorists. Whether people eat shark ﬁns in Shanghai or ﬁsh tacos in San Diego, they all need food and they all need shelter. And desire doesn’t stop at subsistence—people will demand ever more as globalization continues. Now that millions of Chinese peasants can ﬁnally enjoy a secure supply of basic calories, they want more of them to come from pork instead of just grain. The convergence of desire is even more obvious at the top: all oligarchs have the same taste in Cristal, from Petersburg to Pyongyang. Technology Means Complementarity Now think about the prospect of competition from computers instead of competition from human workers. On the supply side, computers are far more diﬀerent from people than any two people are diﬀerent from each other: men and machines are good at fundamentally diﬀerent things. People have intentionality—we form plans and make decisions in complicated situations. We’re less good at making sense of enormous amounts of data. Computers are exactly the opposite: they excel at eﬃcient data processing, but they struggle to make basic judgments that would be simple for any human. To understand the scale of this variance, consider another of Google’s computer-for-human substitution projects. In 2012, one of their supercomputers made headlines when, after scanning 10 million thumbnails of YouTube videos, it learned to identify a cat with 75% accuracy. That seems impressive—until you remember that an average four-year-old can do it ﬂawlessly. When a cheap laptop beats the smartest mathematicians at some tasks but even a supercomputer with 16,000 CPUs can’t beat a child at others, you can tell that humans and computers are not just more or less powerful than each other—they’re categorically diﬀerent. The stark diﬀerences between man and machine mean that gains from working with computers are much higher than gains from trade with other people. We don’t trade with computers any more than we trade with livestock or lamps. And that’s the point: computers are tools, not rivals. The diﬀerences are even deeper on the demand side. Unlike people in industrializing countries, computers don’t yearn for more luxurious foods or beachfront villas in Cap Ferrat; all they require is a nominal amount of electricity, which they’re not even smart enough to want. When we design new computer technology to help solve problems, we get all the eﬃciency gains of a hyperspecialized trading partner without having to compete with it for resources. Properly understood, technology is the one way for us to escape competition in a globalizing world. As computers become more and more powerful, they won’t be substitutes for humans: they’ll be complements. COMPLEMENTARY BUSINESSES Complementarity between computers and humans isn’t just a macro- scale fact. It’s also the path to building a great business. I came to understand this from my experience at PayPal. In mid-2000, we had survived the dot-com crash and we were growing fast, but we faced one huge problem: we were losing upwards of $10 million to credit card fraud every month. Since we were processing hundreds or even thousands of transactions per minute, we couldn’t possibly review each one—no human quality control team could work that fast. So we did what any group of engineers would do: we tried to automate a solution. First, Max Levchin assembled an elite team of mathematicians to study the fraudulent transfers in detail. Then we took what we learned and wrote software to automatically identify and cancel bogus transactions in real time. But it quickly became clear that this approach wouldn’t work either: after an hour or two, the thieves would catch on and change their tactics. We were dealing with an adaptive enemy, and our software couldn’t adapt in response. The fraudsters’ adaptive evasions fooled our automatic detection algorithms, but we found that they didn’t fool our human analysts as easily. So Max and his engineers rewrote the software to take a hybrid approach: the computer would ﬂag the most suspicious transactions on a well-designed user interface, and human operators would make the ﬁnal judgment as to their legitimacy. Thanks to this hybrid system— we named it “Igor,” after the Russian fraudster who bragged that we’d never be able to stop him—we turned our ﬁrst quarterly proﬁt in the ﬁrst quarter of 2002 (as opposed to a quarterly loss of $29.3 million one year before). The FBI asked us if we’d let them use Igor to help detect ﬁnancial crime. And Max was able to boast, grandiosely but truthfully, that he was “the Sherlock Holmes of the Internet Underground.” This kind of man-machine symbiosis enabled PayPal to stay in business, which in turn enabled hundreds of thousands of small businesses to accept the payments they needed to thrive on the internet. None of it would have been possible without the man-machine solution —even though most people would never see it or even hear about it. I continued to think about this after we sold PayPal in 2002: if humans and computers together could achieve dramatically better results than either could attain alone, what other valuable businesses could be built on this core principle? The next year, I pitched Alex Karp, an old Stanford classmate, and Stephen Cohen, a software engineer, on a new startup idea: we would use the human-computer hybrid approach from PayPal’s security system to identify terrorist networks and ﬁnancial fraud. We already knew the FBI was interested, and in 2004 we founded Palantir, a software company that helps people extract insight from divergent sources of information. The company is on track to book sales of $1 billion in 2014, and Forbes has called Palantir’s software the “killer app” for its rumored role in helping the government locate Osama bin Laden. We have no details to share from that operation, but we can say that neither human intelligence by itself nor computers alone will be able to make us safe. America’s two biggest spy agencies take opposite approaches: The Central Intelligence Agency is run by spies who privilege humans. The National Security Agency is run by generals who prioritize computers. CIA analysts have to wade through so much noise that it’s very diﬃcult to identify the most serious threats. NSA computers can process huge quantities of data, but machines alone cannot authoritatively determine whether someone is plotting a terrorist act. Palantir aims to transcend these opposing biases: its software analyzes the data the government feeds it—phone records of radical clerics in Yemen or bank accounts linked to terror cell activity, for instance—and ﬂags suspicious activities for a trained analyst to review. In addition to helping ﬁnd terrorists, analysts using Palantir’s software have been able to predict where insurgents plant IEDs in Afghanistan; prosecute high-proﬁle insider trading cases; take down the largest child pornography ring in the world; support the Centers for Disease Control and Prevention in ﬁghting foodborne disease outbreaks; and save both commercial banks and the government hundreds of millions of dollars annually through advanced fraud detection. Advanced software made this possible, but even more important were the human analysts, prosecutors, scientists, and ﬁnancial professionals without whose active engagement the software would have been useless. Think of what professionals do in their jobs today. Lawyers must be able to articulate solutions to thorny problems in several diﬀerent ways —the pitch changes depending on whether you’re talking to a client, opposing counsel, or a judge. Doctors need to marry clinical understanding with an ability to communicate it to non-expert patients. And good teachers aren’t just experts in their disciplines: they must also understand how to tailor their instruction to diﬀerent individuals’ interests and learning styles. Computers might be able to do some of these tasks, but they can’t combine them eﬀectively. Better technology in law, medicine, and education won’t replace professionals; it will allow them to do even more. LinkedIn has done exactly this for recruiters. When LinkedIn was founded in 2003, they didn’t poll recruiters to ﬁnd discrete pain points in need of relief. And they didn’t try to write software that would replace recruiters outright. Recruiting is part detective work and part sales: you have to scrutinize applicants’ history, assess their motives and compatibility, and persuade the most promising ones to join you. Eﬀectively replacing all those functions with a computer would be impossible. Instead, LinkedIn set out to transform how recruiters did their jobs. Today, more than 97% of recruiters use LinkedIn and its powerful search and ﬁltering functionality to source job candidates, and the network also creates value for the hundreds of millions of professionals who use it to manage their personal brands. If LinkedIn had tried to simply replace recruiters with technology, they wouldn’t have a business today. The Ideology of Computer Science Why do so many people miss the power of complementarity? It starts in school. Software engineers tend to work on projects that replace human eﬀorts because that’s what they’re trained to do. Academics make their reputations through specialized research; their primary goal is to publish papers, and publication means respecting the limits of a particular discipline. For computer scientists, that means reducing human capabilities into specialized tasks that computers can be trained to conquer one by one. Just look at the trendiest ﬁelds in computer science today. The very term “machine learning” evokes imagery of replacement, and its boosters seem to believe that computers can be taught to perform almost any task, so long as we feed them enough training data. Any user of Netﬂix or Amazon has experienced the results of machine learning ﬁrsthand: both companies use algorithms to recommend products based on your viewing and purchase history. Feed them more data and the recommendations get ever better. Google Translate works the same way, providing rough but serviceable translations into any of the 80 languages it supports—not because the software understands human language, but because it has extracted patterns through statistical analysis of a huge corpus of text. The other buzzword that epitomizes a bias toward substitution is “big data.” Today’s companies have an insatiable appetite for data, mistakenly believing that more data always creates more value. But big data is usually dumb data. Computers can ﬁnd patterns that elude humans, but they don’t know how to compare patterns from diﬀerent sources or how to interpret complex behaviors. Actionable insights can only come from a human analyst (or the kind of generalized artiﬁcial intelligence that exists only in science ﬁction). We have let ourselves become enchanted by big data only because we exoticize technology. We’re impressed with small feats accomplished by computers alone, but we ignore big achievements from complementarity because the human contribution makes them less uncanny. Watson, Deep Blue, and ever-better machine learning algorithms are cool. But the most valuable companies in the future won’t ask what problems can be solved with computers alone. Instead, they’ll ask: how can computers help humans solve hard problems? EVER-SMARTER COMPUTERS: FRIEND OR FOE? The future of computing is necessarily full of unknowns. It’s become conventional to see ever-smarter anthropomorphized robot intelligences like Siri and Watson as harbingers of things to come; once computers can answer all our questions, perhaps they’ll ask why they should remain subservient to us at all. The logical endpoint to this substitutionist thinking is called “strong AI”: computers that eclipse humans on every important dimension. Of course, the Luddites are terriﬁed by the possibility. It even makes the futurists a little uneasy; it’s not clear whether strong AI would save humanity or doom it. Technology is supposed to increase our mastery over nature and reduce the role of chance in our lives; building smarter- than-human computers could actually bring chance back with a vengeance. Strong AI is like a cosmic lottery ticket: if we win, we get utopia; if we lose, Skynet substitutes us out of existence. But even if strong AI is a real possibility rather than an imponderable mystery, it won’t happen anytime soon: replacement by computers is a worry for the 22nd century. Indeﬁnite fears about the far future shouldn’t stop us from making deﬁnite plans today. Luddites claim that we shouldn’t build the computers that might replace people someday; crazed futurists argue that we should. These two positions are mutually exclusive but they are not exhaustive: there is room in between for sane people to build a vastly better world in the decades ahead. As we ﬁnd new ways to use computers, they won’t just get better at the kinds of things people already do; they’ll help us to do what was previously unimaginable. 13 SEEING GREEN AT THE START of the 21st century, everyone agreed that the next big thing was clean technology. It had to be: in Beijing, the smog had gotten so bad that people couldn’t see from building to building—even breathing was a health risk. Bangladesh, with its arsenic-laden water wells, was suﬀering what the New York Times called “the biggest mass poisoning in history.” In the U.S., Hurricanes Ivan and Katrina were said to be harbingers of the coming devastation from global warming. Al Gore implored us to attack these problems “with the urgency and resolve that has previously been seen only when nations mobilized for war.” People got busy: entrepreneurs started thousands of cleantech companies, and investors poured more than $50 billion into them. So began the quest to cleanse the world. It didn’t work. Instead of a healthier planet, we got a massive cleantech bubble. Solyndra is the most famous green ghost, but most cleantech companies met similarly disastrous ends—more than 40 solar manufacturers went out of business or ﬁled for bankruptcy in 2012 alone. The leading index of alternative energy companies shows the bubble’s dramatic deﬂation: Why did cleantech fail? Conservatives think they already know the answer: as soon as green energy became a priority for the government, it was poisoned. But there really were (and there still are) good reasons for making energy a priority. And the truth about cleantech is more complex and more important than government failure. Most cleantech companies crashed because they neglected one or more of the seven questions that every business must answer: 1. The Engineering Question Can you create breakthrough technology instead of incremental improvements? 2. The Timing Question Is now the right time to start your particular business? 3. The Monopoly Question Are you starting with a big share of a small market? 4. The People Question Do you have the right team? 5. The Distribution Question Do you have a way to not just create but deliver your product? 6. The Durability Question Will your market position be defensible 10 and 20 years into the future? 7. The Secret Question Have you identiﬁed a unique opportunity that others don’t see? We’ve discussed these elements before. Whatever your industry, any great business plan must address every one of them. If you don’t have good answers to these questions, you’ll run into lots of “bad luck” and your business will fail. If you nail all seven, you’ll master fortune and succeed. Even getting ﬁve or six correct might work. But the striking thing about the cleantech bubble was that people were starting companies with zero good answers—and that meant hoping for a miracle. It’s hard to know exactly why any particular cleantech company failed, since almost all of them made several serious mistakes. But since any one of those mistakes is enough to doom your company, it’s worth reviewing cleantech’s losing scorecard in more detail. THE ENGINEERING QUESTION A great technology company should have proprietary technology an order of magnitude better than its nearest substitute. But cleantech companies rarely produced 2x, let alone 10x, improvements. Sometimes their oﬀerings were actually worse than the products they sought to replace. Solyndra developed novel, cylindrical solar cells, but to a ﬁrst approximation, cylindrical cells are only 1/π as eﬃcient as ﬂat ones— they simply don’t receive as much direct sunlight. The company tried to correct for this deﬁciency by using mirrors to reﬂect more sunlight to hit the bottoms of the panels, but it’s hard to recover from a radically inferior starting point. Companies must strive for 10x better because merely incremental improvements often end up meaning no improvement at all for the end user. Suppose you develop a new wind turbine that’s 20% more eﬃcient than any existing technology—when you test it in the laboratory. That sounds good at ﬁrst, but the lab result won’t begin to compensate for the expenses and risks faced by any new product in the real world. And even if your system really is 20% better on net for the customer who buys it, people are so used to exaggerated claims that you’ll be met with skepticism when you try to sell it. Only when your product is 10x better can you oﬀer the customer transparent superiority. THE TIMING QUESTION Cleantech entrepreneurs worked hard to convince themselves that their appointed hour had arrived. When he announced his new company in 2008, SpectraWatt CEO Andrew Wilson stated that “[t]he solar industry is akin to where the microprocessor industry was in the late 1970s. There is a lot to be ﬁgured out and improved.” The second part was right, but the microprocessor analogy was way oﬀ. Ever since the ﬁrst microprocessor was built in 1970, computing advanced not just rapidly but exponentially. Look at Intel’s early product release history: The ﬁrst silicon solar cell, by contrast, was created by Bell Labs in 1954—more than a half century before Wilson’s press release. Photovoltaic eﬃciency improved in the intervening decades, but slowly and linearly: Bell’s ﬁrst solar cell had about 6% eﬃciency; neither today’s crystalline silicon cells nor modern thin-ﬁlm cells have exceeded 25% eﬃciency in the ﬁeld. There were few engineering developments in the mid-2000s to suggest impending liftoﬀ. Entering a slow-moving market can be a good strategy, but only if you have a deﬁnite and realistic plan to take it over. The failed cleantech companies had none. THE MONOPOLY QUESTION In 2006, billionaire technology investor John Doerr announced that “green is the new red, white and blue.” He could have stopped at “red.” As Doerr himself said, “Internet-sized markets are in the billions of dollars; the energy markets are in the trillions.” What he didn’t say is that huge, trillion-dollar markets mean ruthless, bloody competition. Others echoed Doerr over and over: in the 2000s, I listened to dozens of cleantech entrepreneurs begin fantastically rosy PowerPoint presentations with all-too-true tales of trillion-dollar markets—as if that were a good thing. Cleantech executives emphasized the bounty of an energy market big enough for all comers, but each one typically believed that his own company had an edge. In 2006, Dave Pearce, CEO of solar manufacturer MiaSolé, admitted to a congressional panel that his company was just one of several “very strong” startups working on one particular kind of thin-ﬁlm solar cell development. Minutes later, Pearce predicted that MiaSolé would become “the largest producer of thin-ﬁlm solar cells in the world” within a year’s time. That didn’t happen, but it might not have helped them anyway: thin-ﬁlm is just one of more than a dozen kinds of solar cells. Customers won’t care about any particular technology unless it solves a particular problem in a superior way. And if you can’t monopolize a unique solution for a small market, you’ll be stuck with vicious competition. That’s what happened to MiaSolé, which was acquired in 2013 for hundreds of millions of dollars less than its investors had put into the company. Exaggerating your own uniqueness is an easy way to botch the monopoly question. Suppose you’re running a solar company that’s successfully installed hundreds of solar panel systems with a combined power generation capacity of 100 megawatts. Since total U.S. solar energy production capacity is 950 megawatts, you own 10.53% of the market. Congratulations, you tell yourself: you’re a player. But what if the U.S. solar energy market isn’t the relevant market? What if the relevant market is the global solar market, with a production capacity of 18 gigawatts? Your 100 megawatts now makes you a very small ﬁsh indeed: suddenly you own less than 1% of the market. And what if the appropriate measure isn’t global solar, but rather renewable energy in general? Annual production capacity from renewables is 420 gigawatts globally; you just shrank to 0.02% of the market. And compared to the total global power generation capacity of 15,000 gigawatts, your 100 megawatts is just a drop in the ocean. Cleantech entrepreneurs’ thinking about markets was hopelessly confused. They would rhetorically shrink their market in order to seem diﬀerentiated, only to turn around and ask to be valued based on huge, supposedly lucrative markets. But you can’t dominate a submarket if it’s ﬁctional, and huge markets are highly competitive, not highly attainable. Most cleantech founders would have been better oﬀ opening a new British restaurant in downtown Palo Alto. THE PEOPLE QUESTION Energy problems are engineering problems, so you would expect to ﬁnd nerds running cleantech companies. You’d be wrong: the ones that failed were run by shockingly nontechnical teams. These salesman- executives were good at raising capital and securing government subsidies, but they were less good at building products that customers wanted to buy. At Founders Fund, we saw this coming. The most obvious clue was sartorial: cleantech executives were running around wearing suits and ties. This was a huge red ﬂag, because real technologists wear T-shirts and jeans. So we instituted a blanket rule: pass on any company whose founders dressed up for pitch meetings. Maybe we still would have avoided these bad investments if we had taken the time to evaluate each company’s technology in detail. But the team insight—never invest in a tech CEO that wears a suit—got us to the truth a lot faster. The best sales is hidden. There’s nothing wrong with a CEO who can sell, but if he actually looks like a salesman, he’s probably bad at sales and worse at tech. Solyndra CEO Brian Harrison; Tesla Motors CEO Elon Musk THE DISTRIBUTION QUESTION Cleantech companies eﬀectively courted government and investors, but they often forgot about customers. They learned the hard way that the world is not a laboratory: selling and delivering a product is at least as important as the product itself. Just ask Israeli electric vehicle startup Better Place, which from 2007 to 2012 raised and spent more than $800 million to build swappable battery packs and charging stations for electric cars. The company sought to “create a green alternative that would lessen our dependence on highly polluting transportation technologies.” And it did just that— at least by 1,000 cars, the number it sold before ﬁling for bankruptcy. Even selling that many was an achievement, because each of those cars was very hard for customers to buy. For starters, it was never clear what you were actually buying. Better Place bought sedans from Renault and reﬁtted them with electric batteries and electric motors. So, were you buying an electric Renault, or were you buying a Better Place? In any case, if you decided to buy one, you had to jump through a series of hoops. First, you needed to seek approval from Better Place. To get that, you had to prove that you lived close enough to a Better Place battery swapping station and promise to follow predictable routes. If you passed that test, you had to sign up for a fueling subscription in order to recharge your car. Only then could you get started learning the new behavior of stopping to swap out battery packs on the road. Better Place thought its technology spoke for itself, so they didn’t bother to market it clearly. Reﬂecting on the company’s failure, one frustrated customer asked, “Why wasn’t there a billboard in Tel Aviv showing a picture of a Toyota Prius for 160,000 shekels and a picture of this car, for 160,000 plus fuel for four years?” He still bought one of the cars, but unlike most people, he was a hobbyist who “would do anything to keep driving it.” Unfortunately, he can’t: as the Better Place board of directors stated upon selling the company’s assets for a meager $12 million in 2013, “The technical challenges we overcame successfully, but the other obstacles we were not able to overcome.” THE DURABILITY QUESTION Every entrepreneur should plan to be the last mover in her particular market. That starts with asking yourself: what will the world look like 10 and 20 years from now, and how will my business ﬁt in? Few cleantech companies had a good answer. As a result, all their obituaries resemble each other. A few months before it ﬁled for bankruptcy in 2011, Evergreen Solar explained its decision to close one of its U.S. factories: Solar manufacturers in China have received considerable government

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