from 0 to 1



EVERY MOMENT IN BUSINESS happens only once. The next Bill Gates will not build an operating system. The next
Larry Page or Sergey Brin won’t make a search engine. And the next Mark Zuckerberg won’t create a
social network. If you are copying these guys, you aren’t learning from them.
Of course, it’s easier to copy a model than to make something new. Doing what we already know
how to do takes the world from 1 to n, adding more of something familiar. But every time we create
something new, we go from 0 to 1. The act of creation is singular, as is the moment of creation, and
the result is something fresh and strange.
Unless they invest in the difficult task of creating new things, American companies will fail in the
future no matter how big their profits remain today. What happens when we’ve gained everything to
be had from fine-tuning the old lines of business that we’ve inherited? Unlikely as it sounds, the
answer threatens to be far worse than the crisis of 2008. Today’s “best practices” lead to dead ends;
the best paths are new and untried.
In a world of gigantic administrative bureaucracies both public and private, searching for a new
path might seem like hoping for a miracle. Actually, if American business is going to succeed, we are
going to need hundreds, or even thousands, of miracles. This would be depressing but for one crucial
fact: humans are distinguished from other species by our ability to work miracles. We call these
miracles technology.
Technology is miraculous because it allows us to do more with less, ratcheting up our fundamental
capabilities to a higher level. Other animals are instinctively driven to build things like dams or
honeycombs, but we are the only ones that can invent new things and better ways of making them.
Humans don’t decide what to build by making choices from some cosmic catalog of options given in
advance; instead, by creating new technologies, we rewrite the plan of the world. These are the kind
of elementary truths we teach to second graders, but they are easy to forget in a world where so much
of what we do is repeat what has been done before.
Zero to One is about how to build companies that create new things. It draws on everything I’ve
learned directly as a co-founder of PayPal and Palantir and then an investor in hundreds of startups,
including Facebook and SpaceX. But while I have noticed many patterns, and I relate them here, this
book offers no formula for success. The paradox of teaching entrepreneurship is that such a formula
necessarily cannot exist; because every innovation is new and unique, no authority can prescribe in
concrete terms how to be innovative. Indeed, the single most powerful pattern I have noticed is that
successful people find value in unexpected places, and they do this by thinking about business from
first principles instead of formulas.
This book stems from a course about startups that I taught at Stanford in 2012. College students can
become extremely skilled at a few specialties, but many never learn what to do with those skills in
the wider world. My primary goal in teaching the class was to help my students see beyond the tracks
laid down by academic specialties to the broader future that is theirs to create. One of those students,

Blake Masters, took detailed class notes, which circulated far beyond the campus, and in Zero to One
I have worked with him to revise the notes for a wider audience. There’s no reason why the future
should happen only at Stanford, or in college, or in Silicon Valley.



WHENEVER I INTERVIEW someone for a job, I like to ask this question: “What important truth do very few
people agree with you on?”
This question sounds easy because it’s straightforward. Actually, it’s very hard to answer. It’s
intellectually difficult because the knowledge that everyone is taught in school is by definition agreed
upon. And it’s psychologically difficult because anyone trying to answer must say something she
knows to be unpopular. Brilliant thinking is rare, but courage is in even shorter supply than genius.
Most commonly, I hear answers like the following:
“Our educational system is broken and urgently needs to be fixed.”
“America is exceptional.”
“There is no God.”
Those are bad answers. The first and the second statements might be true, but many people already
agree with them. The third statement simply takes one side in a familiar debate. A good answer takes
the following form: “Most people believe in x, but the truth is the opposite of x.” I’ll give my own
answer later in this chapter.
What does this contrarian question have to do with the future? In the most minimal sense, the future
is simply the set of all moments yet to come. But what makes the future distinctive and important isn’t
that it hasn’t happened yet, but rather that it will be a time when the world looks different from today.
In this sense, if nothing about our society changes for the next 100 years, then the future is over 100
years away. If things change radically in the next decade, then the future is nearly at hand. No one can
predict the future exactly, but we know two things: it’s going to be different, and it must be rooted in
today’s world. Most answers to the contrarian question are different ways of seeing the present; good
answers are as close as we can come to looking into the future.


When we think about the future, we hope for a future of progress. That progress can take one of two
forms. Horizontal or extensive progress means copying things that work—going from 1 to n.
Horizontal progress is easy to imagine because we already know what it looks like. Vertical or
intensive progress means doing new things—going from 0 to 1. Vertical progress is harder to imagine
because it requires doing something nobody else has ever done. If you take one typewriter and build
100, you have made horizontal progress. If you have a typewriter and build a word processor, you
have made vertical progress.

At the macro level, the single word for horizontal progress is globalization—taking things that
work somewhere and making them work everywhere. China is the paradigmatic example of
globalization; its 20-year plan is to become like the United States is today. The Chinese have been
straightforwardly copying everything that has worked in the developed world: 19th-century railroads,
20th-century air conditioning, and even entire cities. They might skip a few steps along the way—
going straight to wireless without installing landlines, for instance—but they’re copying all the same.
The single word for vertical, 0 to 1 progress is technology. The rapid progress of information
technology in recent decades has made Silicon Valley the capital of “technology” in general. But
there is no reason why technology should be limited to computers. Properly understood, any new and
better way of doing things is technology.

Because globalization and technology are different modes of progress, it’s possible to have both,
either, or neither at the same time. For example, 1815 to 1914 was a period of both rapid
technological development and rapid globalization. Between the First World War and Kissinger’s
trip to reopen relations with China in 1971, there was rapid technological development but not much
globalization. Since 1971, we have seen rapid globalization along with limited technological
development, mostly confined to IT.
This age of globalization has made it easy to imagine that the decades ahead will bring more
convergence and more sameness. Even our everyday language suggests we believe in a kind of
technological end of history: the division of the world into the so-called developed and developing
nations implies that the “developed” world has already achieved the achievable, and that poorer
nations just need to catch up.
But I don’t think that’s true. My own answer to the contrarian question is that most people think the
future of the world will be defined by globalization, but the truth is that technology matters more.
Without technological change, if China doubles its energy production over the next two decades, it
will also double its air pollution. If every one of India’s hundreds of millions of households were to
live the way Americans already do—using only today’s tools—the result would be environmentally
catastrophic. Spreading old ways to create wealth around the world will result in devastation, not
riches. In a world of scarce resources, globalization without new technology is unsustainable.

New technology has never been an automatic feature of history. Our ancestors lived in static, zero-
sum societies where success meant seizing things from others. They created new sources of wealth

only rarely, and in the long run they could never create enough to save the average person from an
extremely hard life. Then, after 10,000 years of fitful advance from primitive agriculture to medieval
windmills and 16th-century astrolabes, the modern world suddenly experienced relentless
technological progress from the advent of the steam engine in the 1760s all the way up to about 1970.
As a result, we have inherited a richer society than any previous generation would have been able to
Any generation excepting our parents’ and grandparents’, that is: in the late 1960s, they expected

this progress to continue. They looked forward to a four-day workweek, energy too cheap to meter,
and vacations on the moon. But it didn’t happen. The smartphones that distract us from our
surroundings also distract us from the fact that our surroundings are strangely old: only computers and
communications have improved dramatically since midcentury. That doesn’t mean our parents were
wrong to imagine a better future—they were only wrong to expect it as something automatic. Today
our challenge is to both imagine and create the new technologies that can make the 21st century more
peaceful and prosperous than the 20th.


New technology tends to come from new ventures—startups. From the Founding Fathers in politics to
the Royal Society in science to Fairchild Semiconductor’s “traitorous eight” in business, small
groups of people bound together by a sense of mission have changed the world for the better. The
easiest explanation for this is negative: it’s hard to develop new things in big organizations, and it’s
even harder to do it by yourself. Bureaucratic hierarchies move slowly, and entrenched interests shy
away from risk. In the most dysfunctional organizations, signaling that work is being done becomes a
better strategy for career advancement than actually doing work (if this describes your company, you
should quit now). At the other extreme, a lone genius might create a classic work of art or literature,
but he could never create an entire industry. Startups operate on the principle that you need to work
with other people to get stuff done, but you also need to stay small enough so that you actually can.
Positively defined, a startup is the largest group of people you can convince of a plan to build a
different future. A new company’s most important strength is new thinking: even more important than
nimbleness, small size affords space to think. This book is about the questions you must ask and
answer to succeed in the business of doing new things: what follows is not a manual or a record of
knowledge but an exercise in thinking. Because that is what a startup has to do: question received
ideas and rethink business from scratch.



OUR CONTRARIAN QUESTION—What important truth do very few people agree with you on?—is difficult to
answer directly. It may be easier to start with a preliminary: what does everybody agree on?
“Madness is rare in individuals—but in groups, parties, nations, and ages it is the rule,” Nietzsche
wrote (before he went mad). If you can identify a delusional popular belief, you can find what lies
hidden behind it: the contrarian truth.
Consider an elementary proposition: companies exist to make money, not to lose it. This should be
obvious to any thinking person. But it wasn’t so obvious to many in the late 1990s, when no loss was
too big to be described as an investment in an even bigger, brighter future. The conventional wisdom
of the “New Economy” accepted page views as a more authoritative, forward-looking financial
metric than something as pedestrian as profit.
Conventional beliefs only ever come to appear arbitrary and wrong in retrospect; whenever one
collapses, we call the old belief a bubble. But the distortions caused by bubbles don’t disappear
when they pop. The internet craze of the ’90s was the biggest bubble since the crash of 1929, and the
lessons learned afterward define and distort almost all thinking about technology today. The first step
to thinking clearly is to question what we think we know about the past.


The 1990s have a good image. We tend to remember them as a prosperous, optimistic decade that
happened to end with the internet boom and bust. But many of those years were not as cheerful as our
nostalgia holds. We’ve long since forgotten the global context for the 18 months of dot-com mania at
decade’s end.
The ’90s started with a burst of euphoria when the Berlin Wall came down in November ’89. It
was short-lived. By mid-1990, the United States was in recession. Technically the downturn ended in
March ’91, but recovery was slow and unemployment continued to rise until July ’92. Manufacturing
never fully rebounded. The shift to a service economy was protracted and painful.
1992 through the end of 1994 was a time of general malaise. Images of dead American soldiers in
Mogadishu looped on cable news. Anxiety about globalization and U.S. competitiveness intensified
as jobs flowed to Mexico. This pessimistic undercurrent drove then-president Bush 41 out of office
and won Ross Perot nearly 20% of the popular vote in ’92—the best showing for a third-party
candidate since Theodore Roosevelt in 1912. And whatever the cultural fascination with Nirvana,
grunge, and heroin reflected, it wasn’t hope or confidence.
Silicon Valley felt sluggish, too. Japan seemed to be winning the semiconductor war. The internet
had yet to take off, partly because its commercial use was restricted until late 1992 and partly due to
the lack of user-friendly web browsers. It’s telling that when I arrived at Stanford in 1985,
economics, not computer science, was the most popular major. To most people on campus, the tech
sector seemed idiosyncratic or even provincial.
The internet changed all this. The Mosaic browser was officially released in November 1993,
giving regular people a way to get online. Mosaic became Netscape, which released its Navigator
browser in late 1994. Navigator’s adoption grew so quickly—from about 20% of the browser market
in January 1995 to almost 80% less than 12 months later—that Netscape was able to IPO in August
’95 even though it wasn’t yet profitable. Within five months, Netscape stock had shot up from $28 to
$174 per share. Other tech companies were booming, too. Yahoo! went public in April ’96 with an
$848 million valuation. Amazon followed suit in May ’97 at $438 million. By spring of ’98, each
company’s stock had more than quadrupled. Skeptics questioned earnings and revenue multiples
higher than those for any non-internet company. It was easy to conclude that the market had gone
This conclusion was understandable but misplaced. In December ’96—more than three years
before the bubble actually burst—Fed chairman Alan Greenspan warned that “irrational exuberance”
might have “unduly escalated asset values.” Tech investors were exuberant, but it’s not clear that they
were so irrational. It is too easy to forget that things weren’t going very well in the rest of the world
at the time.
The East Asian financial crises hit in July 1997. Crony capitalism and massive foreign debt
brought the Thai, Indonesian, and South Korean economies to their knees. The ruble crisis followed
in August ’98 when Russia, hamstrung by chronic fiscal deficits, devalued its currency and defaulted
on its debt. American investors grew nervous about a nation with 10,000 nukes and no money; the
Dow Jones Industrial Average plunged more than 10% in a matter of days.
People were right to worry. The ruble crisis set off a chain reaction that brought down Long-Term
Capital Management, a highly leveraged U.S. hedge fund. LTCM managed to lose $4.6 billion in the
latter half of 1998, and still had over $100 billion in liabilities when the Fed intervened with a
massive bailout and slashed interest rates in order to prevent systemic disaster. Europe wasn’t doing

that much better. The euro launched in January 1999 to great skepticism and apathy. It rose to $1.19
on its first day of trading but sank to $0.83 within two years. In mid-2000, G7 central bankers had to
prop it up with a multibillion-dollar intervention.
So the backdrop for the short-lived dot-com mania that started in September 1998 was a world in
which nothing else seemed to be working. The Old Economy couldn’t handle the challenges of
globalization. Something needed to work—and work in a big way—if the future was going to be
better at all. By indirect proof, the New Economy of the internet was the only way forward.


Dot-com mania was intense but short—18 months of insanity from September 1998 to March 2000. It
was a Silicon Valley gold rush: there was money everywhere, and no shortage of exuberant, often
sketchy people to chase it. Every week, dozens of new startups competed to throw the most lavish

launch party. (Landing parties were much more rare.) Paper millionaires would rack up thousand-
dollar dinner bills and try to pay with shares of their startup’s stock—sometimes it even worked.

Legions of people decamped from their well-paying jobs to found or join startups. One 40-something
grad student that I knew was running six different companies in 1999. (Usually, it’s considered weird
to be a 40-year-old graduate student. Usually, it’s considered insane to start a half-dozen companies
at once. But in the late ’90s, people could believe that was a winning combination.) Everybody
should have known that the mania was unsustainable; the most “successful” companies seemed to
embrace a sort of anti-business model where they lost money as they grew. But it’s hard to blame
people for dancing when the music was playing; irrationality was rational given that appending
“.com” to your name could double your value overnight.


When I was running PayPal in late 1999, I was scared out of my wits—not because I didn’t believe in
our company, but because it seemed like everyone else in the Valley was ready to believe anything at
all. Everywhere I looked, people were starting and flipping companies with alarming casualness. One
acquaintance told me how he had planned an IPO from his living room before he’d even incorporated
his company—and he didn’t think that was weird. In this kind of environment, acting sanely began to
seem eccentric.
At least PayPal had a suitably grand mission—the kind that post-bubble skeptics would later
describe as grandiose: we wanted to create a new internet currency to replace the U.S. dollar. Our
first product let people beam money from one PalmPilot to another. However, nobody had any use for
that product except the journalists who voted it one of the 10 worst business ideas of 1999.
PalmPilots were still too exotic then, but email was already commonplace, so we decided to create a
way to send and receive payments over email.
By the fall of ’99, our email payment product worked well—anyone could log in to our website
and easily transfer money. But we didn’t have enough customers, growth was slow, and expenses
mounted. For PayPal to work, we needed to attract a critical mass of at least a million users.
Advertising was too ineffective to justify the cost. Prospective deals with big banks kept falling
through. So we decided to pay people to sign up.
We gave new customers $10 for joining, and we gave them $10 more every time they referred a
friend. This got us hundreds of thousands of new customers and an exponential growth rate. Of
course, this customer acquisition strategy was unsustainable on its own—when you pay people to be
your customers, exponential growth means an exponentially growing cost structure. Crazy costs were
typical at that time in the Valley. But we thought our huge costs were sane: given a large user base,
PayPal had a clear path to profitability by taking a small fee on customers’ transactions.
We knew we’d need more funding to reach that goal. We also knew that the boom was going to
end. Since we didn’t expect investors’ faith in our mission to survive the coming crash, we moved
fast to raise funds while we could. On February 16, 2000, the Wall Street Journal ran a story lauding
our viral growth and suggesting that PayPal was worth $500 million. When we raised $100 million
the next month, our lead investor took the Journal’s back-of-the-envelope valuation as authoritative.
(Other investors were in even more of a hurry. A South Korean firm wired us $5 million without first
negotiating a deal or signing any documents. When I tried to return the money, they wouldn’t tell me
where to send it.) That March 2000 financing round bought us the time we needed to make PayPal a
success. Just as we closed the deal, the bubble popped.


’Cause they say 2,000 zero zero party over, oops! Out of time!

So tonight I’m gonna party like it’s 1999!


The NASDAQ reached 5,048 at its peak in the middle of March 2000 and then crashed to 3,321 in the
middle of April. By the time it bottomed out at 1,114 in October 2002, the country had long since
interpreted the market’s collapse as a kind of divine judgment against the technological optimism of
the ’90s. The era of cornucopian hope was relabeled as an era of crazed greed and declared to be
definitely over.
Everyone learned to treat the future as fundamentally indefinite, and to dismiss as an extremist
anyone with plans big enough to be measured in years instead of quarters. Globalization replaced
technology as the hope for the future. Since the ’90s migration “from bricks to clicks” didn’t work as
hoped, investors went back to bricks (housing) and BRICs (globalization). The result was another
bubble, this time in real estate.

The entrepreneurs who stuck with Silicon Valley learned four big lessons from the dot-com crash
that still guide business thinking today:

1. Make incremental advances
Grand visions inflated the bubble, so they should not be indulged. Anyone who claims to be able
to do something great is suspect, and anyone who wants to change the world should be more
humble. Small, incremental steps are the only safe path forward.
2. Stay lean and flexible
All companies must be “lean,” which is code for “unplanned.” You should not know what your
business will do; planning is arrogant and inflexible. Instead you should try things out, “iterate,”
and treat entrepreneurship as agnostic experimentation.
3. Improve on the competition
Don’t try to create a new market prematurely. The only way to know you have a real business is
to start with an already existing customer, so you should build your company by improving on
recognizable products already offered by successful competitors.
4. Focus on product, not sales
If your product requires advertising or salespeople to sell it, it’s not good enough: technology is
primarily about product development, not distribution. Bubble-era advertising was obviously
wasteful, so the only sustainable growth is viral growth.
These lessons have become dogma in the startup world; those who would ignore them are
presumed to invite the justified doom visited upon technology in the great crash of 2000. And yet the
opposite principles are probably more correct:
1. It is better to risk boldness than triviality.
2. A bad plan is better than no plan.
3. Competitive markets destroy profits.
4. Sales matters just as much as product.
It’s true that there was a bubble in technology. The late ’90s was a time of hubris: people believed
in going from 0 to 1. Too few startups were actually getting there, and many never went beyond
talking about it. But people understood that we had no choice but to find ways to do more with less.
The market high of March 2000 was obviously a peak of insanity; less obvious but more important, it
was also a peak of clarity. People looked far into the future, saw how much valuable new technology
we would need to get there safely, and judged themselves capable of creating it.
We still need new technology, and we may even need some 1999-style hubris and exuberance to
get it. To build the next generation of companies, we must abandon the dogmas created after the crash.
That doesn’t mean the opposite ideas are automatically true: you can’t escape the madness of crowds
by dogmatically rejecting them. Instead ask yourself: how much of what you know about business is
shaped by mistaken reactions to past mistakes? The most contrarian thing of all is not to oppose the
crowd but to think for yourself.



THE BUSINESS VERSION of our contrarian question is: what valuable company is nobody building? This
question is harder than it looks, because your company could create a lot of value without becoming
very valuable itself. Creating value is not enough—you also need to capture some of the value you
This means that even very big businesses can be bad businesses. For example, U.S. airline
companies serve millions of passengers and create hundreds of billions of dollars of value each year.
But in 2012, when the average airfare each way was $178, the airlines made only 37 cents per
passenger trip. Compare them to Google, which creates less value but captures far more. Google
brought in $50 billion in 2012 (versus $160 billion for the airlines), but it kept 21% of those revenues
as profits—more than 100 times the airline industry’s profit margin that year. Google makes so much
money that it’s now worth three times more than every U.S. airline combined.
The airlines compete with each other, but Google stands alone. Economists use two simplified
models to explain the difference: perfect competition and monopoly.

“Perfect competition” is considered both the ideal and the default state in Economics 101. So-
called perfectly competitive markets achieve equilibrium when producer supply meets consumer

demand. Every firm in a competitive market is undifferentiated and sells the same homogeneous
products. Since no firm has any market power, they must all sell at whatever price the market
determines. If there is money to be made, new firms will enter the market, increase supply, drive
prices down, and thereby eliminate the profits that attracted them in the first place. If too many firms
enter the market, they’ll suffer losses, some will fold, and prices will rise back to sustainable levels.
Under perfect competition, in the long run no company makes an economic profit.
The opposite of perfect competition is monopoly. Whereas a competitive firm must sell at the
market price, a monopoly owns its market, so it can set its own prices. Since it has no competition, it
produces at the quantity and price combination that maximizes its profits.
To an economist, every monopoly looks the same, whether it deviously eliminates rivals, secures a
license from the state, or innovates its way to the top. In this book, we’re not interested in illegal
bullies or government favorites: by “monopoly,” we mean the kind of company that’s so good at what
it does that no other firm can offer a close substitute. Google is a good example of a company that
went from 0 to 1: it hasn’t competed in search since the early 2000s, when it definitively distanced
itself from Microsoft and Yahoo!
Americans mythologize competition and credit it with saving us from socialist bread lines.
Actually, capitalism and competition are opposites. Capitalism is premised on the accumulation of
capital, but under perfect competition all profits get competed away. The lesson for entrepreneurs is
clear: if you want to create and capture lasting value, don’t build an undif erentiated commodity


How much of the world is actually monopolistic? How much is truly competitive? It’s hard to say,
because our common conversation about these matters is so confused. To the outside observer, all
businesses can seem reasonably alike, so it’s easy to perceive only small differences between them.

But the reality is much more binary than that. There’s an enormous difference between perfect
competition and monopoly, and most businesses are much closer to one extreme than we commonly

The confusion comes from a universal bias for describing market conditions in self-serving ways:
both monopolists and competitors are incentivized to bend the truth.

Monopoly Lies

Monopolists lie to protect themselves. They know that bragging about their great monopoly invites
being audited, scrutinized, and attacked. Since they very much want their monopoly profits to continue
unmolested, they tend to do whatever they can to conceal their monopoly—usually by exaggerating the
power of their (nonexistent) competition.
Think about how Google talks about its business. It certainly doesn’t claim to be a monopoly. But
is it one? Well, it depends: a monopoly in what? Let’s say that Google is primarily a search engine.
As of May 2014, it owns about 68% of the search market. (Its closest competitors, Microsoft and
Yahoo!, have about 19% and 10%, respectively.) If that doesn’t seem dominant enough, consider the
fact that the word “google” is now an official entry in the Oxford English Dictionary—as a verb.
Don’t hold your breath waiting for that to happen to Bing.
But suppose we say that Google is primarily an advertising company. That changes things. The U.S.
search engine advertising market is $17 billion annually. Online advertising is $37 billion annually.
The entire U.S. advertising market is $150 billion. And global advertising is a $495 billion market.
So even if Google completely monopolized U.S. search engine advertising, it would own just 3.4% of
the global advertising market. From this angle, Google looks like a small player in a competitive


What if we frame Google as a multifaceted technology company instead? This seems reasonable
enough; in addition to its search engine, Google makes dozens of other software products, not to
mention robotic cars, Android phones, and wearable computers. But 95% of Google’s revenue comes
from search advertising; its other products generated just $2.35 billion in 2012, and its consumer tech
products a mere fraction of that. Since consumer tech is a $964 billion market globally, Google owns
less than 0.24% of it—a far cry from relevance, let alone monopoly. Framing itself as just another
tech company allows Google to escape all sorts of unwanted attention.

Competitive Lies

Non-monopolists tell the opposite lie: “we’re in a league of our own.” Entrepreneurs are always
biased to understate the scale of competition, but that is the biggest mistake a startup can make. The
fatal temptation is to describe your market extremely narrowly so that you dominate it by definition.
Suppose you want to start a restaurant that serves British food in Palo Alto. “No one else is doing
it,” you might reason. “We’ll own the entire market.” But that’s only true if the relevant market is the
market for British food specifically. What if the actual market is the Palo Alto restaurant market in
general? And what if all the restaurants in nearby towns are part of the relevant market as well?
These are hard questions, but the bigger problem is that you have an incentive not to ask them at all.
When you hear that most new restaurants fail within one or two years, your instinct will be to come
up with a story about how yours is different. You’ll spend time trying to convince people that you are
exceptional instead of seriously considering whether that’s true. It would be better to pause and
consider whether there are people in Palo Alto who would rather eat British food above all else. It’s
very possible they don’t exist.
In 2001, my co-workers at PayPal and I would often get lunch on Castro Street in Mountain View.
We had our pick of restaurants, starting with obvious categories like Indian, sushi, and burgers. There
were more options once we settled on a type: North Indian or South Indian, cheaper or fancier, and so
on. In contrast to the competitive local restaurant market, PayPal was at that time the only email-

based payments company in the world. We employed fewer people than the restaurants on Castro
Street did, but our business was much more valuable than all of those restaurants combined. Starting a
new South Indian restaurant is a really hard way to make money. If you lose sight of competitive
reality and focus on trivial differentiating factors—maybe you think your naan is superior because of
your great-grandmother’s recipe—your business is unlikely to survive.
Creative industries work this way, too. No screenwriter wants to admit that her new movie script
simply rehashes what has already been done before. Rather, the pitch is: “This film will combine
various exciting elements in entirely new ways.” It could even be true. Suppose her idea is to have
Jay-Z star in a cross between Hackers and Jaws: rap star joins elite group of hackers to catch the
shark that killed his friend. That has definitely never been done before. But, like the lack of British
restaurants in Palo Alto, maybe that’s a good thing.

Non-monopolists exaggerate their distinction by defining their market as the intersection of various
smaller markets:
British food ∩ restaurant ∩ Palo Alto
Rap star ∩ hackers ∩ sharks
Monopolists, by contrast, disguise their monopoly by framing their market as the union of several
large markets:
search engine ∪ mobile phones ∪ wearable computers ∪ self-driving cars
What does a monopolist’s union story look like in practice? Consider a statement from Google
chairman Eric Schmidt’s testimony at a 2011 congressional hearing:
We face an extremely competitive landscape in which consumers have a multitude of options to

access information.
Or, translated from PR-speak to plain English:
Google is a small fish in a big pond. We could be swallowed whole at any time. We are not the
monopoly that the government is looking for.


The problem with a competitive business goes beyond lack of profits. Imagine you’re running one of
those restaurants in Mountain View. You’re not that different from dozens of your competitors, so
you’ve got to fight hard to survive. If you offer affordable food with low margins, you can probably
pay employees only minimum wage. And you’ll need to squeeze out every efficiency: that’s why
small restaurants put Grandma to work at the register and make the kids wash dishes in the back.
Restaurants aren’t much better even at the very highest rungs, where reviews and ratings like
Michelin’s star system enforce a culture of intense competition that can drive chefs crazy. (French
chef and winner of three Michelin stars Bernard Loiseau was quoted as saying, “If I lose a star, I will
commit suicide.” Michelin maintained his rating, but Loiseau killed himself anyway in 2003 when a
competing French dining guide downgraded his restaurant.) The competitive ecosystem pushes people
toward ruthlessness or death.
A monopoly like Google is different. Since it doesn’t have to worry about competing with anyone,
it has wider latitude to care about its workers, its products, and its impact on the wider world.
Google’s motto—“Don’t be evil”—is in part a branding ploy, but it’s also characteristic of a kind of
business that’s successful enough to take ethics seriously without jeopardizing its own existence. In
business, money is either an important thing or it is everything. Monopolists can afford to think
about things other than making money; non-monopolists can’t. In perfect competition, a business is so
focused on today’s margins that it can’t possibly plan for a long-term future. Only one thing can allow
a business to transcend the daily brute struggle for survival: monopoly profits.


So, a monopoly is good for everyone on the inside, but what about everyone on the outside? Do
outsized profits come at the expense of the rest of society? Actually, yes: profits come out of
customers’ wallets, and monopolies deserve their bad reputation—but only in a world where
nothing changes.
In a static world, a monopolist is just a rent collector. If you corner the market for something, you
can jack up the price; others will have no choice but to buy from you. Think of the famous board
game: deeds are shuffled around from player to player, but the board never changes. There’s no way
to win by inventing a better kind of real estate development. The relative values of the properties are
fixed for all time, so all you can do is try to buy them up.
But the world we live in is dynamic: it’s possible to invent new and better things. Creative
monopolists give customers more choices by adding entirely new categories of abundance to the
world. Creative monopolies aren’t just good for the rest of society; they’re powerful engines for
making it better.
Even the government knows this: that’s why one of its departments works hard to create
monopolies (by granting patents to new inventions) even though another part hunts them down (by
prosecuting antitrust cases). It’s possible to question whether anyone should really be awarded a
legally enforceable monopoly simply for having been the first to think of something like a mobile
software design. But it’s clear that something like Apple’s monopoly profits from designing,
producing, and marketing the iPhone were the reward for creating greater abundance, not artificial
scarcity: customers were happy to finally have the choice of paying high prices to get a smartphone
that actually works.
The dynamism of new monopolies itself explains why old monopolies don’t strangle innovation.
With Apple’s iOS at the forefront, the rise of mobile computing has dramatically reduced Microsoft’s
decades-long operating system dominance. Before that, IBM’s hardware monopoly of the ’60s and
’70s was overtaken by Microsoft’s software monopoly. AT&T had a monopoly on telephone service
for most of the 20th century, but now anyone can get a cheap cell phone plan from any number of
providers. If the tendency of monopoly businesses were to hold back progress, they would be
dangerous and we’d be right to oppose them. But the history of progress is a history of better
monopoly businesses replacing incumbents.
Monopolies drive progress because the promise of years or even decades of monopoly profits
provides a powerful incentive to innovate. Then monopolies can keep innovating because profits
enable them to make the long-term plans and to finance the ambitious research projects that firms
locked in competition can’t dream of.
So why are economists obsessed with competition as an ideal state? It’s a relic of history.
Economists copied their mathematics from the work of 19th-century physicists: they see individuals
and businesses as interchangeable atoms, not as unique creators. Their theories describe an
equilibrium state of perfect competition because that’s what’s easy to model, not because it
represents the best of business. But it’s worth recalling that the long-run equilibrium predicted by
19th-century physics was a state in which all energy is evenly distributed and everything comes to
rest—also known as the heat death of the universe. Whatever your views on thermodynamics, it’s a
powerful metaphor: in business, equilibrium means stasis, and stasis means death. If your industry is
in a competitive equilibrium, the death of your business won’t matter to the world; some other
undifferentiated competitor will always be ready to take your place.

Perfect equilibrium may describe the void that is most of the universe. It may even characterize
many businesses. But every new creation takes place far from equilibrium. In the real world outside
economic theory, every business is successful exactly to the extent that it does something others
cannot. Monopoly is therefore not a pathology or an exception. Monopoly is the condition of every
successful business.
Tolstoy opens Anna Karenina by observing: “All happy families are alike; each unhappy family is
unhappy in its own way.” Business is the opposite. All happy companies are different: each one earns
a monopoly by solving a unique problem. All failed companies are the same: they failed to escape



CREATIVE MONOPOLY means new products that benefit everybody and sustainable profits for the creator.
Competition means no profits for anybody, no meaningful differentiation, and a struggle for survival.
So why do people believe that competition is healthy? The answer is that competition is not just an
economic concept or a simple inconvenience that individuals and companies must deal with in the
marketplace. More than anything else, competition is an ideology—the ideology—that pervades our
society and distorts our thinking. We preach competition, internalize its necessity, and enact its
commandments; and as a result, we trap ourselves within it—even though the more we compete, the
less we gain.
This is a simple truth, but we’ve all been trained to ignore it. Our educational system both drives
and reflects our obsession with competition. Grades themselves allow precise measurement of each
student’s competitiveness; pupils with the highest marks receive status and credentials. We teach
every young person the same subjects in mostly the same ways, irrespective of individual talents and
preferences. Students who don’t learn best by sitting still at a desk are made to feel somehow
inferior, while children who excel on conventional measures like tests and assignments end up
defining their identities in terms of this weirdly contrived academic parallel reality.
And it gets worse as students ascend to higher levels of the tournament. Elite students climb
confidently until they reach a level of competition sufficiently intense to beat their dreams out of them.
Higher education is the place where people who had big plans in high school get stuck in fierce
rivalries with equally smart peers over conventional careers like management consulting and
investment banking. For the privilege of being turned into conformists, students (or their families) pay
hundreds of thousands of dollars in skyrocketing tuition that continues to outpace inflation. Why are
we doing this to ourselves?
I wish I had asked myself when I was younger. My path was so tracked that in my 8th-grade
yearbook, one of my friends predicted—accurately—that four years later I would enter Stanford as a
sophomore. And after a conventionally successful undergraduate career, I enrolled at Stanford Law
School, where I competed even harder for the standard badges of success.
The highest prize in a law student’s world is unambiguous: out of tens of thousands of graduates
each year, only a few dozen get a Supreme Court clerkship. After clerking on a federal appeals court
for a year, I was invited to interview for clerkships with Justices Kennedy and Scalia. My meetings
with the Justices went well. I was so close to winning this last competition. If only I got the clerkship,
I thought, I would be set for life. But I didn’t. At the time, I was devastated.
In 2004, after I had built and sold PayPal, I ran into an old friend from law school who had helped
me prepare my failed clerkship applications. We hadn’t spoken in nearly a decade. His first question
wasn’t “How are you doing?” or “Can you believe it’s been so long?” Instead, he grinned and asked:
“So, Peter, aren’t you glad you didn’t get that clerkship?” With the benefit of hindsight, we both knew
that winning that ultimate competition would have changed my life for the worse. Had I actually
clerked on the Supreme Court, I probably would have spent my entire career taking depositions or
drafting other people’s business deals instead of creating anything new. It’s hard to say how much
would be different, but the opportunity costs were enormous. All Rhodes Scholars had a great future
in their past.


Professors downplay the cutthroat culture of academia, but managers never tire of comparing business
to war. MBA students carry around copies of Clausewitz and Sun Tzu. War metaphors invade our
everyday business language: we use headhunters to build up a sales force that will enable us to take
a captive market and make a killing. But really it’s competition, not business, that is like war:
allegedly necessary, supposedly valiant, but ultimately destructive.
Why do people compete with each other? Marx and Shakespeare provide two models for
understanding almost every kind of conflict.
According to Marx, people fight because they are different. The proletariat fights the bourgeoisie
because they have completely different ideas and goals (generated, for Marx, by their very different
material circumstances). The greater the differences, the greater the conflict.
To Shakespeare, by contrast, all combatants look more or less alike. It’s not at all clear why they
should be fighting, since they have nothing to fight about. Consider the opening line from Romeo and
Juliet: “Two households, both alike in dignity.” The two houses are alike, yet they hate each other.
They grow even more similar as the feud escalates. Eventually, they lose sight of why they started
fighting in the first place.
In the world of business, at least, Shakespeare proves the superior guide. Inside a firm, people
become obsessed with their competitors for career advancement. Then the firms themselves become
obsessed with their competitors in the marketplace. Amid all the human drama, people lose sight of
what matters and focus on their rivals instead.
Let’s test the Shakespearean model in the real world. Imagine a production called Gates and
Schmidt, based on Romeo and Juliet. Montague is Microsoft. Capulet is Google. Two great families,
run by alpha nerds, sure to clash on account of their sameness.
As with all good tragedy, the conflict seems inevitable only in retrospect. In fact it was entirely
avoidable. These families came from very different places. The House of Montague built operating
systems and office applications. The House of Capulet wrote a search engine. What was there to fight
Lots, apparently. As a startup, each clan had been content to leave the other alone and prosper
independently. But as they grew, they began to focus on each other. Montagues obsessed about
Capulets obsessed about Montagues. The result? Windows vs. Chrome OS, Bing vs. Google Search,
Explorer vs. Chrome, Office vs. Docs, and Surface vs. Nexus.
Just as war cost the Montagues and Capulets their children, it cost Microsoft and Google their
dominance: Apple came along and overtook them all. In January 2013, Apple’s market capitalization
was $500 billion, while Google and Microsoft combined were worth $467 billion. Just three years
before, Microsoft and Google were each more valuable than Apple. War is costly business.
Rivalry causes us to overemphasize old opportunities and slavishly copy what has worked in the
past. Consider the recent proliferation of mobile credit card readers. In October 2010, a startup
called Square released a small, white, square-shaped product that let anyone with an iPhone swipe
and accept credit cards. It was the first good payment processing solution for mobile handsets.
Imitators promptly sprang into action. A Canadian company called NetSecure launched its own card
reader in a half-moon shape. Intuit brought a cylindrical reader to the geometric battle. In March
2012, eBay’s PayPal unit launched its own copycat card reader. It was shaped like a triangle—a
clear jab at Square, as three sides are simpler than four. One gets the sense that this Shakespearean
saga won’t end until the apes run out of shapes.

The hazards of imitative competition may partially explain why individuals with an Asperger’s-
like social ineptitude seem to be at an advantage in Silicon Valley today. If you’re less sensitive to

social cues, you’re less likely to do the same things as everyone else around you. If you’re interested

in making things or programming computers, you’ll be less afraid to pursue those activities single-
mindedly and thereby become incredibly good at them. Then when you apply your skills, you’re a

little less likely than others to give up your own convictions: this can save you from getting caught up
in crowds competing for obvious prizes.
Competition can make people hallucinate opportunities where none exist. The crazy ’90s version
of this was the fierce battle for the online pet store market. It was vs. vs. vs. what seemed like dozens of others. Each company was obsessed with defeating its
rivals, precisely because there were no substantive differences to focus on. Amid all the tactical
questions—Who could price chewy dog toys most aggressively? Who could create the best Super
Bowl ads?—these companies totally lost sight of the wider question of whether the online pet supply
market was the right space to be in. Winning is better than losing, but everybody loses when the war
isn’t one worth fighting. When folded after the dot-com crash, $300 million of investment
capital disappeared with it.
Other times, rivalry is just weird and distracting. Consider the Shakespearean conflict between
Larry Ellison, co-founder and CEO of Oracle, and Tom Siebel, a top salesman at Oracle and
Ellison’s protégé before he went on to found Siebel Systems in 1993. Ellison was livid at what he
thought was Siebel’s betrayal. Siebel hated being in the shadow of his former boss. The two men
were basically identical—hard-charging Chicagoans who loved to sell and hated to lose—so their
hatred ran deep. Ellison and Siebel spent the second half of the ’90s trying to sabotage each other. At
one point, Ellison sent truckloads of ice cream sandwiches to Siebel’s headquarters to try to convince
Siebel employees to jump ship. The copy on the wrappers? “Summer is near. Oracle is here. To
brighten your day and your career.”
Strangely, Oracle intentionally accumulated enemies. Ellison’s theory was that it’s always good to
have an enemy, so long as it was large enough to appear threatening (and thus motivational to
employees) but not so large as to actually threaten the company. So Ellison was probably thrilled
when in 1996 a small database company called Informix put up a billboard near Oracle’s Redwood
Shores headquarters that read: CAUTION: DINOSAUR CROSSING. Another Informix billboard on northbound Highway
Oracle shot back with a billboard that implied that Informix’s software was slower than snails.

Then Informix CEO Phil White decided to make things personal. When White learned that Larry
Ellison enjoyed Japanese samurai culture, he commissioned a new billboard depicting the Oracle
logo along with a broken samurai sword. The ad wasn’t even really aimed at Oracle as an entity, let
alone the consuming public; it was a personal attack on Ellison. But perhaps White spent a little too
much time worrying about the competition: while he was busy creating billboards, Informix imploded
in a massive accounting scandal and White soon found himself in federal prison for securities fraud.
If you can’t beat a rival, it may be better to merge. I started Confinity with my co-founder Max
Levchin in 1998. When we released the PayPal product in late 1999, Elon Musk’s was right
on our heels: our companies’ offices were four blocks apart on University Avenue in Palo Alto, and
X’s product mirrored ours feature-for-feature. By late 1999, we were in all-out war. Many of us at
PayPal logged 100-hour workweeks. No doubt that was counterproductive, but the focus wasn’t on
objective productivity; the focus was defeating One of our engineers actually designed a
bomb for this purpose; when he presented the schematic at a team meeting, calmer heads prevailed
and the proposal was attributed to extreme sleep deprivation.
But in February 2000, Elon and I were more scared about the rapidly inflating tech bubble than we
were about each other: a financial crash would ruin us both before we could finish our fight. So in
early March we met on neutral ground—a café almost exactly equidistant to our offices—and
negotiated a 50-50 merger. De-escalating the rivalry post-merger wasn’t easy, but as far as problems
go, it was a good one to have. As a unified team, we were able to ride out the dot-com crash and then
build a successful business.
Sometimes you do have to fight. Where that’s true, you should fight and win. There is no middle
ground: either don’t throw any punches, or strike hard and end it quickly.
This advice can be hard to follow because pride and honor can get in the way. Hence Hamlet:
Exposing what is mortal and unsure
To all that fortune, death, and danger dare,
Even for an eggshell. Rightly to be great
Is not to stir without great argument,
But greatly to find quarrel in a straw
When honor’s at the stake.
For Hamlet, greatness means willingness to fight for reasons as thin as an eggshell: anyone would
fight for things that matter; true heroes take their personal honor so seriously they will fight for things
that don’t matter. This twisted logic is part of human nature, but it’s disastrous in business. If you can
recognize competition as a destructive force instead of a sign of value, you’re already more sane than
most. The next chapter is about how to use a clear head to build a monopoly business.



ESCAPING COMPETITION will give you a monopoly, but even a monopoly is only a great business if it can
endure in the future. Compare the value of the New York Times Company with Twitter. Each employs
a few thousand people, and each gives millions of people a way to get news. But when Twitter went
public in 2013, it was valued at $24 billion—more than 12 times the Times’s market capitalization
—even though the Times earned $133 million in 2012 while Twitter lost money. What explains the
huge premium for Twitter?
The answer is cash flow. This sounds bizarre at first, since the Times was profitable while Twitter
wasn’t. But a great business is defined by its ability to generate cash flows in the future. Investors
expect Twitter will be able to capture monopoly profits over the next decade, while newspapers’
monopoly days are over.
Simply stated, the value of a business today is the sum of all the money it will make in the future.
(To properly value a business, you also have to discount those future cash flows to their present
worth, since a given amount of money today is worth more than the same amount in the future.)

Comparing discounted cash flows shows the difference between low-growth businesses and high-
growth startups at its starkest. Most of the value of low-growth businesses is in the near term. An Old

Economy business (like a newspaper) might hold its value if it can maintain its current cash flows for
five or six years. However, any firm with close substitutes will see its profits competed away.
Nightclubs or restaurants are extreme examples: successful ones might collect healthy amounts today,
but their cash flows will probably dwindle over the next few years when customers move on to
newer and trendier alternatives.
Technology companies follow the opposite trajectory. They often lose money for the first few
years: it takes time to build valuable things, and that means delayed revenue. Most of a tech
company’s value will come at least 10 to 15 years in the future.

In March 2001, PayPal had yet to make a profit but our revenues were growing 100% year-over-
year. When I projected our future cash flows, I found that 75% of the company’s present value would

come from profits generated in 2011 and beyond—hard to believe for a company that had been in
business for only 27 months. But even that turned out to be an underestimation. Today, PayPal
continues to grow at about 15% annually, and the discount rate is lower than a decade ago. It now
appears that most of the company’s value will come from 2020 and beyond.
LinkedIn is another good example of a company whose value exists in the far future. As of early
2014, its market capitalization was $24.5 billion—very high for a company with less than $1 billion
in revenue and only $21.6 million in net income for 2012. You might look at these numbers and
conclude that investors have gone insane. But this valuation makes sense when you consider
LinkedIn’s projected future cash flows.

The overwhelming importance of future profits is counterintuitive even in Silicon Valley. For a
company to be valuable it must grow and endure, but many entrepreneurs focus only on short-term
growth. They have an excuse: growth is easy to measure, but durability isn’t. Those who succumb to
measurement mania obsess about weekly active user statistics, monthly revenue targets, and quarterly
earnings reports. However, you can hit those numbers and still overlook deeper, harder-to-measure
problems that threaten the durability of your business.
For example, rapid short-term growth at both Zynga and Groupon distracted managers and
investors from long-term challenges. Zynga scored early wins with games like Farmville and claimed
to have a “psychometric engine” to rigorously gauge the appeal of new releases. But they ended up
with the same problem as every Hollywood studio: how can you reliably produce a constant stream
of popular entertainment for a fickle audience? (Nobody knows.) Groupon posted fast growth as
hundreds of thousands of local businesses tried their product. But persuading those businesses to
become repeat customers was harder than they thought.
If you focus on near-term growth above all else, you miss the most important question you should
be asking: will this business still be around a decade from now? Numbers alone won’t tell you the
answer; instead you must think critically about the qualitative characteristics of your business.


What does a company with large cash flows far into the future look like? Every monopoly is unique,
but they usually share some combination of the following characteristics: proprietary technology,
network effects, economies of scale, and branding.
This isn’t a list of boxes to check as you build your business—there’s no shortcut to monopoly.
However, analyzing your business according to these characteristics can help you think about how to
make it durable.

1. Proprietary Technology

Proprietary technology is the most substantive advantage a company can have because it makes your
product difficult or impossible to replicate. Google’s search algorithms, for example, return results
better than anyone else’s. Proprietary technologies for extremely short page load times and highly
accurate query autocompletion add to the core search product’s robustness and defensibility. It would
be very hard for anyone to do to Google what Google did to all the other search engine companies in
the early 2000s.
As a good rule of thumb, proprietary technology must be at least 10 times better than its closest
substitute in some important dimension to lead to a real monopolistic advantage. Anything less than an
order of magnitude better will probably be perceived as a marginal improvement and will be hard to
sell, especially in an already crowded market.
The clearest way to make a 10x improvement is to invent something completely new. If you build
something valuable where there was nothing before, the increase in value is theoretically infinite. A
drug to safely eliminate the need for sleep, or a cure for baldness, for example, would certainly
support a monopoly business.
Or you can radically improve an existing solution: once you’re 10x better, you escape competition.
PayPal, for instance, made buying and selling on eBay at least 10 times better. Instead of mailing a
check that would take 7 to 10 days to arrive, PayPal let buyers pay as soon as an auction ended.
Sellers received their proceeds right away, and unlike with a check, they knew the funds were good.
Amazon made its first 10x improvement in a particularly visible way: they offered at least 10 times
as many books as any other bookstore. When it launched in 1995, Amazon could claim to be “Earth’s
largest bookstore” because, unlike a retail bookstore that might stock 100,000 books, Amazon didn’t
need to physically store any inventory—it simply requested the title from its supplier whenever a
customer made an order. This quantum improvement was so effective that a very unhappy Barnes &
Noble filed a lawsuit three days before Amazon’s IPO, claiming that Amazon was unfairly calling
itself a “bookstore” when really it was a “book broker.”
You can also make a 10x improvement through superior integrated design. Before 2010, tablet
computing was so poor that for all practical purposes the market didn’t even exist. “Microsoft
Windows XP Tablet PC Edition” products first shipped in 2002, and Nokia released its own
“Internet Tablet” in 2005, but they were a pain to use. Then Apple released the iPad. Design
improvements are hard to measure, but it seems clear that Apple improved on anything that had come
before by at least an order of magnitude: tablets went from unusable to useful.

2. Network Ef ects

Network effects make a product more useful as more people use it. For example, if all your friends
are on Facebook, it makes sense for you to join Facebook, too. Unilaterally choosing a different
social network would only make you an eccentric.
Network effects can be powerful, but you’ll never reap them unless your product is valuable to its
very first users when the network is necessarily small. For example, in 1960 a quixotic company
called Xanadu set out to build a two-way communication network between all computers—a sort of
early, synchronous version of the World Wide Web. After more than three decades of futile effort,
Xanadu folded just as the web was becoming commonplace. Their technology probably would have
worked at scale, but it could have worked only at scale: it required every computer to join the
network at the same time, and that was never going to happen.
Paradoxically, then, network effects businesses must start with especially small markets. Facebook
started with just Harvard students—Mark Zuckerberg’s first product was designed to get all his
classmates signed up, not to attract all people of Earth. This is why successful network businesses
rarely get started by MBA types: the initial markets are so small that they often don’t even appear to
be business opportunities at all.

3. Economies of Scale

A monopoly business gets stronger as it gets bigger: the fixed costs of creating a product (engineering,
management, office space) can be spread out over ever greater quantities of sales. Software startups
can enjoy especially dramatic economies of scale because the marginal cost of producing another
copy of the product is close to zero.
Many businesses gain only limited advantages as they grow to large scale. Service businesses
especially are difficult to make monopolies. If you own a yoga studio, for example, you’ll only be
able to serve a certain number of customers. You can hire more instructors and expand to more
locations, but your margins will remain fairly low and you’ll never reach a point where a core group
of talented people can provide something of value to millions of separate clients, as software
engineers are able to do.
A good startup should have the potential for great scale built into its first design. Twitter already
has more than 250 million users today. It doesn’t need to add too many customized features in order to
acquire more, and there’s no inherent reason why it should ever stop growing.

4. Branding

A company has a monopoly on its own brand by definition, so creating a strong brand is a powerful
way to claim a monopoly. Today’s strongest tech brand is Apple: the attractive looks and carefully
chosen materials of products like the iPhone and MacBook, the Apple Stores’ sleek minimalist design
and close control over the consumer experience, the omnipresent advertising campaigns, the price
positioning as a maker of premium goods, and the lingering nimbus of Steve Jobs’s personal charisma
all contribute to a perception that Apple offers products so good as to constitute a category of their
Many have tried to learn from Apple’s success: paid advertising, branded stores, luxurious

materials, playful keynote speeches, high prices, and even minimalist design are all susceptible to
imitation. But these techniques for polishing the surface don’t work without a strong underlying
substance. Apple has a complex suite of proprietary technologies, both in hardware (like superior
touchscreen materials) and software (like touchscreen interfaces purpose-designed for specific
materials). It manufactures products at a scale large enough to dominate pricing for the materials it
buys. And it enjoys strong network effects from its content ecosystem: thousands of developers write
software for Apple devices because that’s where hundreds of millions of users are, and those users
stay on the platform because it’s where the apps are. These other monopolistic advantages are less
obvious than Apple’s sparkling brand, but they are the fundamentals that let the branding effectively
reinforce Apple’s monopoly.
Beginning with brand rather than substance is dangerous. Ever since Marissa Mayer became CEO
of Yahoo! in mid-2012, she has worked to revive the once-popular internet giant by making it cool
again. In a single tweet, Yahoo! summarized Mayer’s plan as a chain reaction of “people then
products then traffic then revenue.” The people are supposed to come for the coolness: Yahoo!
demonstrated design awareness by overhauling its logo, it asserted youthful relevance by acquiring
hot startups like Tumblr, and it has gained media attention for Mayer’s own star power. But the big
question is what products Yahoo! will actually create. When Steve Jobs returned to Apple, he didn’t
just make Apple a cool place to work; he slashed product lines to focus on the handful of
opportunities for 10x improvements. No technology company can be built on branding alone.


Brand, scale, network effects, and technology in some combination define a monopoly; but to get them
to work, you need to choose your market carefully and expand deliberately.

Start Small and Monopolize

Every startup is small at the start. Every monopoly dominates a large share of its market. Therefore,
every startup should start with a very small market. Always err on the side of starting too small.
The reason is simple: it’s easier to dominate a small market than a large one. If you think your initial
market might be too big, it almost certainly is.
Small doesn’t mean nonexistent. We made this mistake early on at PayPal. Our first product let
people beam money to each other via PalmPilots. It was interesting technology and no one else was
doing it. However, the world’s millions of PalmPilot users weren’t concentrated in a particular
place, they had little in common, and they used their devices only episodically. Nobody needed our
product, so we had no customers.
With that lesson learned, we set our sights on eBay auctions, where we found our first success. In
late 1999, eBay had a few thousand high-volume “PowerSellers,” and after only three months of
dedicated effort, we were serving 25% of them. It was much easier to reach a few thousand people
who really needed our product than to try to compete for the attention of millions of scattered
The perfect target market for a startup is a small group of particular people concentrated together
and served by few or no competitors. Any big market is a bad choice, and a big market already
served by competing companies is even worse. This is why it’s always a red flag when entrepreneurs
talk about getting 1% of a $100 billion market. In practice, a large market will either lack a good
starting point or it will be open to competition, so it’s hard to ever reach that 1%. And even if you do
succeed in gaining a small foothold, you’ll have to be satisfied with keeping the lights on: cutthroat
competition means your profits will be zero.

Scaling Up

Once you create and dominate a niche market, then you should gradually expand into related and
slightly broader markets. Amazon shows how it can be done. Jeff Bezos’s founding vision was to
dominate all of online retail, but he very deliberately started with books. There were millions of
books to catalog, but they all had roughly the same shape, they were easy to ship, and some of the
most rarely sold books—those least profitable for any retail store to keep in stock—also drew the
most enthusiastic customers. Amazon became the dominant solution for anyone located far from a
bookstore or seeking something unusual. Amazon then had two options: expand the number of people
who read books, or expand to adjacent markets. They chose the latter, starting with the most similar
markets: CDs, videos, and software. Amazon continued to add categories gradually until it had
become the world’s general store. The name itself brilliantly encapsulated the company’s scaling
strategy. The biodiversity of the Amazon rain forest reflected Amazon’s first goal of cataloging every
book in the world, and now it stands for every kind of thing in the world, period.
eBay also started by dominating small niche markets. When it launched its auction marketplace in

1995, it didn’t need the whole world to adopt it at once; the product worked well for intense interest
groups, like Beanie Baby obsessives. Once it monopolized the Beanie Baby trade, eBay didn’t jump
straight to listing sports cars or industrial surplus: it continued to cater to small-time hobbyists until it
became the most reliable marketplace for people trading online no matter what the item.
Sometimes there are hidden obstacles to scaling—a lesson that eBay has learned in recent years.
Like all marketplaces, the auction marketplace lent itself to natural monopoly because buyers go
where the sellers are and vice versa. But eBay found that the auction model works best for
individually distinctive products like coins and stamps. It works less well for commodity products:
people don’t want to bid on pencils or Kleenex, so it’s more convenient just to buy them from
Amazon. eBay is still a valuable monopoly; it’s just smaller than people in 2004 expected it to be.
Sequencing markets correctly is underrated, and it takes discipline to expand gradually. The most
successful companies make the core progression—to first dominate a specific niche and then scale to
adjacent markets—a part of their founding narrative.

Don’t Disrupt

Silicon Valley has become obsessed with “disruption.” Originally, “disruption” was a term of art to
describe how a firm can use new technology to introduce a low-end product at low prices, improve
the product over time, and eventually overtake even the premium products offered by incumbent
companies using older technology. This is roughly what happened when the advent of PCs disrupted
the market for mainframe computers: at first PCs seemed irrelevant, then they became dominant.
Today mobile devices may be doing the same thing to PCs.
However, disruption has recently transmogrified into a self-congratulatory buzzword for anything
posing as trendy and new. This seemingly trivial fad matters because it distorts an entrepreneur’s
self-understanding in an inherently competitive way. The concept was coined to describe threats to
incumbent companies, so startups’ obsession with disruption means they see themselves through older
firms’ eyes. If you think of yourself as an insurgent battling dark forces, it’s easy to become unduly
fixated on the obstacles in your path. But if you truly want to make something new, the act of creation
is far more important than the old industries that might not like what you create. Indeed, if your
company can be summed up by its opposition to already existing firms, it can’t be completely new
and it’s probably not going to become a monopoly.
Disruption also attracts attention: disruptors are people who look for trouble and find it. Disruptive
kids get sent to the principal’s office. Disruptive companies often pick fights they can’t win. Think of
Napster: the name itself meant trouble. What kinds of things can one “nap”? Music … Kids … and
perhaps not much else. Shawn Fanning and Sean Parker, Napster’s then-teenage founders, credibly
threatened to disrupt the powerful music recording industry in 1999. The next year, they made the
cover of Time magazine. A year and a half after that, they ended up in bankruptcy court.
PayPal could be seen as disruptive, but we didn’t try to directly challenge any large competitor.
It’s true that we took some business away from Visa when we popularized internet payments: you
might use PayPal to buy something online instead of using your Visa card to buy it in a store. But
since we expanded the market for payments overall, we gave Visa far more business than we took.
The overall dynamic was net positive, unlike Napster’s negative-sum struggle with the U.S. recording
industry. As you craft a plan to expand to adjacent markets, don’t disrupt: avoid competition as much
as possible.


You’ve probably heard about “first mover advantage”: if you’re the first entrant into a market, you
can capture significant market share while competitors scramble to get started. But moving first is a
tactic, not a goal. What really matters is generating cash flows in the future, so being the first mover
doesn’t do you any good if someone else comes along and unseats you. It’s much better to be the last
mover—that is, to make the last great development in a specific market and enjoy years or even
decades of monopoly profits. The way to do that is to dominate a small niche and scale up from there,
toward your ambitious long-term vision. In this one particular at least, business is like chess.
Grandmaster José Raúl Capablanca put it well: to succeed, “you must study the endgame before
everything else.”



THE MOST CONTENTIOUS question in business is whether success comes from luck or skill.
What do successful people say? Malcolm Gladwell, a successful author who writes about
successful people, declares in Outliers that success results from a “patchwork of lucky breaks and
arbitrary advantages.” Warren Buffett famously considers himself a “member of the lucky sperm
club” and a winner of the “ovarian lottery.” Jeff Bezos attributes Amazon’s success to an “incredible
planetary alignment” and jokes that it was “half luck, half good timing, and the rest brains.” Bill Gates
even goes so far as to claim that he “was lucky to be born with certain skills,” though it’s not clear
whether that’s actually possible.
Perhaps these guys are being strategically humble. However, the phenomenon of serial
entrepreneurship would seem to call into question our tendency to explain success as the product of
chance. Hundreds of people have started multiple multimillion-dollar businesses. A few, like Steve
Jobs, Jack Dorsey, and Elon Musk, have created several multibillion-dollar companies. If success
were mostly a matter of luck, these kinds of serial entrepreneurs probably wouldn’t exist.
In January 2013, Jack Dorsey, founder of Twitter and Square, tweeted to his 2 million followers:
“Success is never accidental.”
Most of the replies were unambiguously negative. Referencing the tweet in The Atlantic, reporter
Alexis Madrigal wrote that his instinct was to reply: “ ‘Success is never accidental,’ said all
multimillionaire white men.” It’s true that already successful people have an easier time doing new
things, whether due to their networks, wealth, or experience. But perhaps we’ve become too quick to
dismiss anyone who claims to have succeeded according to plan.
Is there a way to settle this debate objectively? Unfortunately not, because companies are not
experiments. To get a scientific answer about Facebook, for example, we’d have to rewind to 2004,
create 1,000 copies of the world, and start Facebook in each copy to see how many times it would
succeed. But that experiment is impossible. Every company starts in unique circumstances, and every
company starts only once. Statistics doesn’t work when the sample size is one.
From the Renaissance and the Enlightenment to the mid-20th century, luck was something to be
mastered, dominated, and controlled; everyone agreed that you should do what you could, not focus
on what you couldn’t. Ralph Waldo Emerson captured this ethos when he wrote: “Shallow men
believe in luck, believe in circumstances…. Strong men believe in cause and effect.” In 1912, after he
became the first explorer to reach the South Pole, Roald Amundsen wrote: “Victory awaits him who
has everything in order—luck, people call it.” No one pretended that misfortune didn’t exist, but prior
generations believed in making their own luck by working hard.
If you believe your life is mainly a matter of chance, why read this book? Learning about startups is
worthless if you’re just reading stories about people who won the lottery. Slot Machines for
Dummies can purport to tell you which kind of rabbit’s foot to rub or how to tell which machines are
“hot,” but it can’t tell you how to win.
Did Bill Gates simply win the intelligence lottery? Was Sheryl Sandberg born with a silver spoon,
or did she “lean in”? When we debate historical questions like these, luck is in the past tense. Far
more important are questions about the future: is it a matter of chance or design?


You can expect the future to take a definite form or you can treat it as hazily uncertain. If you treat the
future as something definite, it makes sense to understand it in advance and to work to shape it. But if
you expect an indefinite future ruled by randomness, you’ll give up on trying to master it.
Indefinite attitudes to the future explain what’s most dysfunctional in our world today. Process
trumps substance: when people lack concrete plans to carry out, they use formal rules to assemble a
portfolio of various options. This describes Americans today. In middle school, we’re encouraged to
start hoarding “extracurricular activities.” In high school, ambitious students compete even harder to
appear omnicompetent. By the time a student gets to college, he’s spent a decade curating a
bewilderingly diverse résumé to prepare for a completely unknowable future. Come what may, he’s
ready—for nothing in particular.
A definite view, by contrast, favors firm convictions. Instead of pursuing many-sided mediocrity
and calling it “well-roundedness,” a definite person determines the one best thing to do and then does
it. Instead of working tirelessly to make herself indistinguishable, she strives to be great at something
substantive—to be a monopoly of one. This is not what young people do today, because everyone
around them has long since lost faith in a definite world. No one gets into Stanford by excelling at just
one thing, unless that thing happens to involve throwing or catching a leather ball.

You can also expect the future to be either better or worse than the present. Optimists welcome the
future; pessimists fear it. Combining these possibilities yields four views:

Indefinite Pessimism

Every culture has a myth of decline from some golden age, and almost all peoples throughout history

have been pessimists. Even today pessimism still dominates huge parts of the world. An indefinite
pessimist looks out onto a bleak future, but he has no idea what to do about it. This describes Europe
since the early 1970s, when the continent succumbed to undirected bureaucratic drift. Today the
whole Eurozone is in slow-motion crisis, and nobody is in charge. The European Central Bank
doesn’t stand for anything but improvisation: the U.S. Treasury prints “In God We Trust” on the
dollar; the ECB might as well print “Kick the Can Down the Road” on the euro. Europeans just react
to events as they happen and hope things don’t get worse. The indefinite pessimist can’t know
whether the inevitable decline will be fast or slow, catastrophic or gradual. All he can do is wait for
it to happen, so he might as well eat, drink, and be merry in the meantime: hence Europe’s famous
vacation mania.

Definite Pessimism

A definite pessimist believes the future can be known, but since it will be bleak, he must prepare for
it. Perhaps surprisingly, China is probably the most definitely pessimistic place in the world today.
When Americans see the Chinese economy grow ferociously fast (10% per year since 2000), we
imagine a confident country mastering its future. But that’s because Americans are still optimists, and
we project our optimism onto China. From China’s viewpoint, economic growth cannot come fast
enough. Every other country is afraid that China is going to take over the world; China is the only
country afraid that it won’t.
China can grow so fast only because its starting base is so low. The easiest way for China to grow
is to relentlessly copy what has already worked in the West. And that’s exactly what it’s doing:
executing definite plans by burning ever more coal to build ever more factories and skyscrapers. But
with a huge population pushing resource prices higher, there’s no way Chinese living standards can
ever actually catch up to those of the richest countries, and the Chinese know it.
This is why the Chinese leadership is obsessed with the way in which things threaten to get worse.
Every senior Chinese leader experienced famine as a child, so when the Politburo looks to the future,
disaster is not an abstraction. The Chinese public, too, knows that winter is coming. Outsiders are
fascinated by the great fortunes being made inside China, but they pay less attention to the wealthy
Chinese trying hard to get their money out of the country. Poorer Chinese just save everything they can
and hope it will be enough. Every class of people in China takes the future deadly seriously.

Definite Optimism

To a definite optimist, the future will be better than the present if he plans and works to make it
better. From the 17th century through the 1950s and ’60s, definite optimists led the Western world.
Scientists, engineers, doctors, and businessmen made the world richer, healthier, and more long-lived
than previously imaginable. As Karl Marx and Friedrich Engels saw clearly, the 19th-century
business class
created more massive and more colossal productive forces than all preceding generations
together. Subjection of Nature’s forces to man, machinery, application of chemistry to industry
and agriculture, steam-navigation, railways, electric telegraphs, clearing of whole continents for
cultivation, canalisation of rivers, whole populations conjured out of the ground—what earlier

century had even a presentiment that such productive forces slumbered in the lap of social labor?
Each generation’s inventors and visionaries surpassed their predecessors. In 1843, the London
public was invited to make its first crossing underneath the River Thames by a newly dug tunnel. In
1869, the Suez Canal saved Eurasian shipping traffic from rounding the Cape of Good Hope. In 1914
the Panama Canal cut short the route from Atlantic to Pacific. Even the Great Depression failed to

impede relentless progress in the United States, which has always been home to the world’s most far-
seeing definite optimists. The Empire State Building was started in 1929 and finished in 1931. The

Golden Gate Bridge was started in 1933 and completed in 1937. The Manhattan Project was started
in 1941 and had already produced the world’s first nuclear bomb by 1945. Americans continued to
remake the face of the world in peacetime: the Interstate Highway System began construction in 1956,
and the first 20,000 miles of road were open for driving by 1965. Definite planning even went beyond
the surface of this planet: NASA’s Apollo Program began in 1961 and put 12 men on the moon before
it finished in 1972.
Bold plans were not reserved just for political leaders or government scientists. In the late 1940s,
a Californian named John Reber set out to reinvent the physical geography of the whole San
Francisco Bay Area. Reber was a schoolteacher, an amateur theater producer, and a self-taught
engineer. Undaunted by his lack of credentials, he publicly proposed to build two huge dams in the
Bay, construct massive freshwater lakes for drinking water and irrigation, and reclaim 20,000 acres
of land for development. Even though he had no personal authority, people took the Reber Plan
seriously. It was endorsed by newspaper editorial boards across California. The U.S. Congress held
hearings on its feasibility. The Army Corps of Engineers even constructed a 1.5-acre scale model of
the Bay in a cavernous Sausalito warehouse to simulate it. These tests revealed technical
shortcomings, so the plan wasn’t executed.
But would anybody today take such a vision seriously in the first place? In the 1950s, people
welcomed big plans and asked whether they would work. Today a grand plan coming from a
schoolteacher would be dismissed as crankery, and a long-range vision coming from anyone more
powerful would be derided as hubris. You can still visit the Bay Model in that Sausalito warehouse,
but today it’s just a tourist attraction: big plans for the future have become archaic curiosities.

In the 1950s, Americans thought big plans for the future were too important to be left to experts.

Indefinite Optimism

After a brief pessimistic phase in the 1970s, indefinite optimism has dominated American thinking
ever since 1982, when a long bull market began and finance eclipsed engineering as the way to
approach the future. To an indefinite optimist, the future will be better, but he doesn’t know how
exactly, so he won’t make any specific plans. He expects to profit from the future but sees no reason
to design it concretely.

Instead of working for years to build a new product, indefinite optimists rearrange already-
invented ones. Bankers make money by rearranging the capital structures of already existing

companies. Lawyers resolve disputes over old things or help other people structure their affairs. And
private equity investors and management consultants don’t start new businesses; they squeeze extra
efficiency from old ones with incessant procedural optimizations. It’s no surprise that these fields all
attract disproportionate numbers of high-achieving Ivy League optionality chasers; what could be a

more appropriate reward for two decades of résumé-building than a seemingly elite, process-oriented
career that promises to “keep options open”?
Recent graduates’ parents often cheer them on the established path. The strange history of the Baby
Boom produced a generation of indefinite optimists so used to effortless progress that they feel
entitled to it. Whether you were born in 1945 or 1950 or 1955, things got better every year for the
first 18 years of your life, and it had nothing to do with you. Technological advance seemed to
accelerate automatically, so the Boomers grew up with great expectations but few specific plans for
how to fulfill them. Then, when technological progress stalled in the 1970s, increasing income
inequality came to the rescue of the most elite Boomers. Every year of adulthood continued to get
automatically better and better for the rich and successful. The rest of their generation was left
behind, but the wealthy Boomers who shape public opinion today see little reason to question their
naïve optimism. Since tracked careers worked for them, they can’t imagine that they won’t work for
their kids, too.
Malcolm Gladwell says you can’t understand Bill Gates’s success without understanding his
fortunate personal context: he grew up in a good family, went to a private school equipped with a
computer lab, and counted Paul Allen as a childhood friend. But perhaps you can’t understand
Malcolm Gladwell without understanding his historical context as a Boomer (born in 1963). When
Baby Boomers grow up and write books to explain why one or another individual is successful, they
point to the power of a particular individual’s context as determined by chance. But they miss the
even bigger social context for their own preferred explanations: a whole generation learned from
childhood to overrate the power of chance and underrate the importance of planning. Gladwell at first
appears to be making a contrarian critique of the myth of the self-made businessman, but actually his
own account encapsulates the conventional view of a generation.


Indefinite Finance

While a definitely optimistic future would need engineers to design underwater cities and settlements
in space, an indefinitely optimistic future calls for more bankers and lawyers. Finance epitomizes
indefinite thinking because it’s the only way to make money when you have no idea how to create
wealth. If they don’t go to law school, bright college graduates head to Wall Street precisely because
they have no real plan for their careers. And once they arrive at Goldman, they find that even inside
finance, everything is indefinite. It’s still optimistic—you wouldn’t play in the markets if you
expected to lose—but the fundamental tenet is that the market is random; you can’t know anything
specific or substantive; diversification becomes supremely important.
The indefiniteness of finance can be bizarre. Think about what happens when successful
entrepreneurs sell their company. What do they do with the money? In a financialized world, it
unfolds like this:
• The founders don’t know what to do with it, so they give it to a large bank.
• The bankers don’t know what to do with it, so they diversify by spreading it across a portfolio
of institutional investors.
• Institutional investors don’t know what to do with their managed capital, so they diversify by
amassing a portfolio of stocks.
• Companies try to increase their share price by generating free cash flows. If they do, they issue
dividends or buy back shares and the cycle repeats.
At no point does anyone in the chain know what to do with money in the real economy. But in an
indefinite world, people actually prefer unlimited optionality; money is more valuable than anything
you could possibly do with it. Only in a definite future is money a means to an end, not the end itself.

Indefinite Politics

Politicians have always been officially accountable to the public at election time, but today they are
attuned to what the public thinks at every moment. Modern polling enables politicians to tailor their
image to match preexisting public opinion exactly, so for the most part, they do. Nate Silver’s
election predictions are remarkably accurate, but even more remarkable is how big a story they
become every four years. We are more fascinated today by statistical predictions of what the country
will be thinking in a few weeks’ time than by visionary predictions of what the country will look like
10 or 20 years from now.
And it’s not just the electoral process—the very character of government has become indefinite,
too. The government used to be able to coordinate complex solutions to problems like atomic
weaponry and lunar exploration. But today, after 40 years of indefinite creep, the government mainly
just provides insurance; our solutions to big problems are Medicare, Social Security, and a dizzying
array of other transfer payment programs. It’s no surprise that entitlement spending has eclipsed
discretionary spending every year since 1975. To increase discretionary spending we’d need definite
plans to solve specific problems. But according to the indefinite logic of entitlement spending, we can

make things better just by sending out more checks.

Indefinite Philosophy

You can see the shift to an indefinite attitude not just in politics but in the political philosophers
whose ideas underpin both left and right.
The philosophy of the ancient world was pessimistic: Plato, Aristotle, Epicurus, and Lucretius all
accepted strict limits on human potential. The only question was how best to cope with our tragic
fate. Modern philosophers have been mostly optimistic. From Herbert Spencer on the right and Hegel
in the center to Marx on the left, the 19th century shared a belief in progress. (Remember Marx and
Engels’s encomium to the technological triumphs of capitalism from this page.) These thinkers
expected material advances to fundamentally change human life for the better: they were definite
In the late 20th century, indefinite philosophies came to the fore. The two dominant political
thinkers, John Rawls and Robert Nozick, are usually seen as stark opposites: on the egalitarian left,
Rawls was concerned with questions of fairness and distribution; on the libertarian right, Nozick
focused on maximizing individual freedom. They both believed that people could get along with each
other peacefully, so unlike the ancients, they were optimistic. But unlike Spencer or Marx, Rawls and
Nozick were indefinite optimists: they didn’t have any specific vision of the future.

Their indefiniteness took different forms. Rawls begins A Theory of Justice with the famous “veil
of ignorance”: fair political reasoning is supposed to be impossible for anyone with knowledge of the
world as it concretely exists. Instead of trying to change our actual world of unique people and real
technologies, Rawls fantasized about an “inherently stable” society with lots of fairness but little
dynamism. Nozick opposed Rawls’s “patterned” concept of justice. To Nozick, any voluntary
exchange must be allowed, and no social pattern could be noble enough to justify maintenance by

coercion. He didn’t have any more concrete ideas about the good society than Rawls: both of them
focused on process. Today, we exaggerate the differences between left-liberal egalitarianism and
libertarian individualism because almost everyone shares their common indefinite attitude. In
philosophy, politics, and business, too, arguing over process has become a way to endlessly defer
making concrete plans for a better future.

Indefinite Life

Our ancestors sought to understand and extend the human lifespan. In the 16th century, conquistadors
searched the jungles of Florida for a Fountain of Youth. Francis Bacon wrote that “the prolongation of
life” should be considered its own branch of medicine—and the noblest. In the 1660s, Robert Boyle
placed life extension (along with “the Recovery of Youth”) atop his famous wish list for the future of
science. Whether through geographic exploration or laboratory research, the best minds of the
Renaissance thought of death as something to defeat. (Some resisters were killed in action: Bacon
caught pneumonia and died in 1626 while experimenting to see if he could extend a chicken’s life by
freezing it in the snow.)
We haven’t yet uncovered the secrets of life, but insurers and statisticians in the 19th century
successfully revealed a secret about death that still governs our thinking today: they discovered how
to reduce it to a mathematical probability. “Life tables” tell us our chances of dying in any given year,
something previous generations didn’t know. However, in exchange for better insurance contracts, we
seem to have given up the search for secrets about longevity. Systematic knowledge of the current
range of human lifespans has made that range seem natural. Today our society is permeated by the
twin ideas that death is both inevitable and random.
Meanwhile, probabilistic attitudes have come to shape the agenda of biology itself. In 1928,
Scottish scientist Alexander Fleming found that a mysterious antibacterial fungus had grown on a petri
dish he’d forgotten to cover in his laboratory: he discovered penicillin by accident. Scientists have
sought to harness the power of chance ever since. Modern drug discovery aims to amplify Fleming’s
serendipitous circumstances a millionfold: pharmaceutical companies search through combinations of
molecular compounds at random, hoping to find a hit.
But it’s not working as well as it used to. Despite dramatic advances over the past two centuries,
in recent decades biotechnology hasn’t met the expectations of investors—or patients. Eroom’s law—
that’s Moore’s law backward—observes that the number of new drugs approved per billion dollars
spent on R&D has halved every nine years since 1950. Since information technology accelerated
faster than ever during those same years, the big question for biotech today is whether it will ever see
similar progress. Compare biotech startups to their counterparts in computer software:

Biotech startups are an extreme example of indefinite thinking. Researchers experiment with things
that just might work instead of refining definite theories about how the body’s systems operate.
Biologists say they need to work this way because the underlying biology is hard. According to them,
IT startups work because we created computers ourselves and designed them to reliably obey our
commands. Biotech is difficult because we didn’t design our bodies, and the more we learn about
them, the more complex they turn out to be.
But today it’s possible to wonder whether the genuine difficulty of biology has become an excuse
for biotech startups’ indefinite approach to business in general. Most of the people involved expect
some things to work eventually, but few want to commit to a specific company with the level of
intensity necessary for success. It starts with the professors who often become part-time consultants
instead of full-time employees—even for the biotech startups that begin from their own research.
Then everyone else imitates the professors’ indefinite attitude. It’s easy for libertarians to claim that
heavy regulation holds biotech back—and it does—but indefinite optimism may pose an even greater
challenge for the future of biotech.


What kind of future will our indefinitely optimistic decisions bring about? If American households
were saving, at least they could expect to have money to spend later. And if American companies
were investing, they could expect to reap the rewards of new wealth in the future. But U.S.
households are saving almost nothing. And U.S. companies are letting cash pile up on their balance
sheets without investing in new projects because they don’t have any concrete plans for the future.

The other three views of the future can work. Definite optimism works when you build the future
you envision. Definite pessimism works by building what can be copied without expecting anything
new. Indefinite pessimism works because it’s self-fulfilling: if you’re a slacker with low
expectations, they’ll probably be met. But indefinite optimism seems inherently unsustainable: how
can the future get better if no one plans for it?
Actually, most everybody in the modern world has already heard an answer to this question:
progress without planning is what we call “evolution.” Darwin himself wrote that life tends to
“progress” without anybody intending it. Every living thing is just a random iteration on some other
organism, and the best iterations win.
Darwin’s theory explains the origin of trilobites and dinosaurs, but can it be extended to domains
that are far removed? Just as Newtonian physics can’t explain black holes or the Big Bang, it’s not
clear that Darwinian biology should explain how to build a better society or how to create a new
business out of nothing. Yet in recent years Darwinian (or pseudo-Darwinian) metaphors have
become common in business. Journalists analogize literal survival in competitive ecosystems to

corporate survival in competitive markets. Hence all the headlines like “Digital Darwinism,” “Dot-
com Darwinism,” and “Survival of the Clickiest.”

Even in engineering-driven Silicon Valley, the buzzwords of the moment call for building a “lean
startup” that can “adapt” and “evolve” to an ever-changing environment. Would-be entrepreneurs are
told that nothing can be known in advance: we’re supposed to listen to what customers say they want,
make nothing more than a “minimum viable product,” and iterate our way to success.

But leanness is a methodology, not a goal. Making small changes to things that already exist might
lead you to a local maximum, but it won’t help you find the global maximum. You could build the best
version of an app that lets people order toilet paper from their iPhone. But iteration without a bold
plan won’t take you from 0 to 1. A company is the strangest place of all for an indefinite optimist:
why should you expect your own business to succeed without a plan to make it happen? Darwinism
may be a fine theory in other contexts, but in startups, intelligent design works best.


What would it mean to prioritize design over chance? Today, “good design” is an aesthetic
imperative, and everybody from slackers to yuppies carefully “curates” their outward appearance.
It’s true that every great entrepreneur is first and foremost a designer. Anyone who has held an
iDevice or a smoothly machined MacBook has felt the result of Steve Jobs’s obsession with visual
and experiential perfection. But the most important lesson to learn from Jobs has nothing to do with
aesthetics. The greatest thing Jobs designed was his business. Apple imagined and executed definite
multi-year plans to create new products and distribute them effectively. Forget “minimum viable
products”—ever since he started Apple in 1976, Jobs saw that you can change the world through
careful planning, not by listening to focus group feedback or copying others’ successes.
Long-term planning is often undervalued by our indefinite short-term world. When the first iPod
was released in October 2001, industry analysts couldn’t see much more than “a nice feature for
Macintosh users” that “doesn’t make any difference” to the rest of the world. Jobs planned the iPod to
be the first of a new generation of portable post-PC devices, but that secret was invisible to most
people. One look at the company’s stock chart shows the harvest of this multi-year plan:

The power of planning explains the difficulty of valuing private companies. When a big company
makes an offer to acquire a successful startup, it almost always offers too much or too little: founders
only sell when they have no more concrete visions for the company, in which case the acquirer
probably overpaid; definite founders with robust plans don’t sell, which means the offer wasn’t high
enough. When Yahoo! offered to buy Facebook for $1 billion in July 2006, I thought we should at
least consider it. But Mark Zuckerberg walked into the board meeting and announced: “Okay, guys,
this is just a formality, it shouldn’t take more than 10 minutes. We’re obviously not going to sell
here.” Mark saw where he could take the company, and Yahoo! didn’t. A business with a good
definite plan will always be underrated in a world where people see the future as random.


Venture capitalists aim to identify, fund, and profit from promising early-stage companies. They raise
money from institutions and wealthy people, pool it into a fund, and invest in technology companies
that they believe will become more valuable. If they turn out to be right, they take a cut of the returns
—usually 20%. A venture fund makes money when the companies in its portfolio become more
valuable and either go public or get bought by larger companies. Venture funds usually have a 10-year
lifespan since it takes time for successful companies to grow and “exit.”
But most venture-backed companies don’t IPO or get acquired; most fail, usually soon after they
start. Due to these early failures, a venture fund typically loses money at first. VCs hope the value of
the fund will increase dramatically in a few years’ time, to break-even and beyond, when the
successful portfolio companies hit their exponential growth spurts and start to scale.
The big question is when this takeoff will happen. For most funds, the answer is never. Most
startups fail, and most funds fail with them. Every VC knows that his task is to find the companies that
will succeed. However, even seasoned investors understand this phenomenon only superficially.
They know companies are different, but they underestimate the degree of difference.

The error lies in expecting that venture returns will be normally distributed: that is, bad companies
will fail, mediocre ones will stay flat, and good ones will return 2x or even 4x. Assuming this bland
pattern, investors assemble a diversified portfolio and hope that winners counterbalance losers.
But this “spray and pray” approach usually produces an entire portfolio of flops, with no hits at all.
This is because venture returns don’t follow a normal distribution overall. Rather, they follow a
power law: a small handful of companies radically outperform all others. If you focus on
diversification instead of single-minded pursuit of the very few companies that can become
overwhelmingly valuable, you’ll miss those rare companies in the first place.

This graph shows the stark reality versus the perceived relative homogeneity:

Our results at Founders Fund illustrate this skewed pattern: Facebook, the best investment in our
2005 fund, returned more than all the others combined. Palantir, the second-best investment, is set to
return more than the sum of every other investment aside from Facebook. This highly uneven pattern is
not unusual: we see it in all our other funds as well. The biggest secret in venture capital is that the
best investment in a successful fund equals or outperforms the entire rest of the fund combined.
This implies two very strange rules for VCs. First, only invest in companies that have the potential
to return the value of the entire fund. This is a scary rule, because it eliminates the vast majority of
possible investments. (Even quite successful companies usually succeed on a more humble scale.)
This leads to rule number two: because rule number one is so restrictive, there can’t be any other
Consider what happens when you break the first rule. Andreessen Horowitz invested $250,000 in
Instagram in 2010. When Facebook bought Instagram just two years later for $1 billion, Andreessen
netted $78 million—a 312x return in less than two years. That’s a phenomenal return, befitting the
firm’s reputation as one of the Valley’s best. But in a weird way it’s not nearly enough, because
Andreessen Horowitz has a $1.5 billion fund: if they only wrote $250,000 checks, they would need to
find 19 Instagrams just to break even. This is why investors typically put a lot more money into any
company worth funding. (And to be fair, Andreessen would have invested more in Instagram’s later
rounds had it not been conflicted out by a previous investment.) VCs must find the handful of
companies that will successfully go from 0 to 1 and then back them with every resource.
Of course, no one can know with certainty ex ante which companies will succeed, so even the best
VC firms have a “portfolio.” However, every single company in a good venture portfolio must have
the potential to succeed at vast scale. At Founders Fund, we focus on five to seven companies in a
fund, each of which we think could become a multibillion-dollar business based on its unique
fundamentals. Whenever you shift from the substance of a business to the financial question of
whether or not it fits into a diversified hedging strategy, venture investing starts to look a lot like
buying lottery tickets. And once you think that you’re playing the lottery, you’ve already
psychologically prepared yourself to lose.


Why would professional VCs, of all people, fail to see the power law? For one thing, it only becomes
clear over time, and even technology investors too often live in the present. Imagine a firm invests in
10 companies with the potential to become monopolies—already an unusually disciplined portfolio.
Those companies will look very similar in the early stages before exponential growth.

Over the next few years, some companies will fail while others begin to succeed; valuations will
diverge, but the difference between exponential growth and linear growth will be unclear.

After 10 years, however, the portfolio won’t be divided between winners and losers; it will be
split between one dominant investment and everything else.
But no matter how unambiguous the end result of the power law, it doesn’t reflect daily experience.
Since investors spend most of their time making new investments and attending to companies in their
early stages, most of the companies they work with are by definition average. Most of the differences
that investors and entrepreneurs perceive every day are between relative levels of success, not
between exponential dominance and failure. And since nobody wants to give up on an investment,
VCs usually spend even more time on the most problematic companies than they do on the most
obviously successful.

If even investors specializing in exponentially growing startups miss the power law, it’s not
surprising that most everyone else misses it, too. Power law distributions are so big that they hide in
plain sight. For example, when most people outside Silicon Valley think of venture capital, they might
picture a small and quirky coterie—like ABC’s Shark Tank, only without commercials. After all,
less than 1% of new businesses started each year in the U.S. receive venture funding, and total VC
investment accounts for less than 0.2% of GDP. But the results of those investments
disproportionately propel the entire economy. Venture-backed companies create 11% of all private
sector jobs. They generate annual revenues equivalent to an astounding 21% of GDP. Indeed, the
dozen largest tech companies were all venture-backed. Together those 12 companies are worth more
than $2 trillion, more than all other tech companies combined.


The power law is not just important to investors; rather, it’s important to everybody because
everybody is an investor. An entrepreneur makes a major investment just by spending her time
working on a startup. Therefore every entrepreneur must think about whether her company is going to
succeed and become valuable. Every individual is unavoidably an investor, too. When you choose a
career, you act on your belief that the kind of work you do will be valuable decades from now.
The most common answer to the question of future value is a diversified portfolio: “Don’t put all
your eggs in one basket,” everyone has been told. As we said, even the best venture investors have a
portfolio, but investors who understand the power law make as few investments as possible. The kind
of portfolio thinking embraced by both folk wisdom and financial convention, by contrast, regards
diversified betting as a source of strength. The more you dabble, the more you are supposed to have
hedged against the uncertainty of the future.
But life is not a portfolio: not for a startup founder, and not for any individual. An entrepreneur
cannot “diversify” herself: you cannot run dozens of companies at the same time and then hope that
one of them works out well. Less obvious but just as important, an individual cannot diversify his
own life by keeping dozens of equally possible careers in ready reserve.
Our schools teach the opposite: institutionalized education traffics in a kind of homogenized,
generic knowledge. Everybody who passes through the American school system learns not to think in
power law terms. Every high school course period lasts 45 minutes whatever the subject. Every
student proceeds at a similar pace. At college, model students obsessively hedge their futures by

assembling a suite of exotic and minor skills. Every university believes in “excellence,” and hundred-
page course catalogs arranged alphabetically according to arbitrary departments of knowledge seem

designed to reassure you that “it doesn’t matter what you do, as long as you do it well.” That is
completely false. It does matter what you do. You should focus relentlessly on something you’re good
at doing, but before that you must think hard about whether it will be valuable in the future.
For the startup world, this means you should not necessarily start your own company, even if you
are extraordinarily talented. If anything, too many people are starting their own companies today.
People who understand the power law will hesitate more than others when it comes to founding a
new venture: they know how tremendously successful they could become by joining the very best
company while it’s growing fast. The power law means that differences between companies will
dwarf the differences in roles inside companies. You could have 100% of the equity if you fully fund
your own venture, but if it fails you’ll have 100% of nothing. Owning just 0.01% of Google, by
contrast, is incredibly valuable (more than $35 million as of this writing).
If you do start your own company, you must remember the power law to operate it well. The most
important things are singular: One market will probably be better than all others, as we discussed in
Chapter 5. One distribution strategy usually dominates all others, too—for that see Chapter 11. Time
and decision-making themselves follow a power law, and some moments matter far more than others
—see Chapter 9. However, you can’t trust a world that denies the power law to accurately frame
your decisions for you, so what’s most important is rarely obvious. It might even be secret. But in a
power law world, you can’t afford not to think hard about where your actions will fall on the curve.



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
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



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.


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.


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 a
n + b
n = c
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.


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
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.


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
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.



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 10

30—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


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.


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.


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.


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
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.


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.


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



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.


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 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
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.

From the outside, everyone in your company should be dif erent 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.


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.


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.



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.


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.


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.


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 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.
A t 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.


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.



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.


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.


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?


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.



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.


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
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.


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.


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.


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


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


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 and financial support….
Although [our] production costs … are now below originally planned levels and lower than
most western manufacturers, they are still much higher than those of our low cost competitors in
But it wasn’t until 2012 that the “blame China” chorus really exploded. Discussing its bankruptcy
filing, U.S. Department of Energy–backed Abound Solar blamed “aggressive pricing actions from
Chinese solar panel companies” that “made it very difficult for an early stage startup company … to
scale in current market conditions.” When solar panel maker Energy Conversion Devices failed in
February 2012, it went beyond blaming China in a press release and filed a $950 million lawsuit
against three prominent Chinese solar manufacturers—the same companies that Solyndra’s trustees in
bankruptcy sued later that year on the grounds of attempted monopolization, conspiracy, and predatory
pricing. But was competition from Chinese manufacturers really impossible to predict? Cleantech
entrepreneurs would have done well to rephrase the durability question and ask: what will stop China
from wiping out my business? Without an answer, the result shouldn’t have come as a surprise.
Beyond the failure to anticipate competition in manufacturing the same green products, cleantech
embraced misguided assumptions about the energy market as a whole. An industry premised on the
supposed twilight of fossil fuels was blindsided by the rise of fracking. In 2000, just 1.7% of
America’s natural gas came from fracked shale. Five years later, that figure had climbed to 4.1%.
Nevertheless, nobody in cleantech took this trend seriously: renewables were the only way forward;
fossil fuels couldn’t possibly get cheaper or cleaner in the future. But they did. By 2013, shale gas
accounted for 34% of America’s natural gas, and gas prices had fallen more than 70% since 2008,
devastating most renewable energy business models. Fracking may not be a durable energy solution,
either, but it was enough to doom cleantech companies that didn’t see it coming.


Every cleantech company justified itself with conventional truths about the need for a cleaner world.
They deluded themselves into believing that an overwhelming social need for alternative energy
solutions implied an overwhelming business opportunity for cleantech companies of all kinds.
Consider how conventional it had become by 2006 to be bullish on solar. That year, President
George W. Bush heralded a future of “solar roofs that will enable the American family to be able to
generate their own electricity.” Investor and cleantech executive Bill Gross declared that the
“potential for solar is enormous.” Suvi Sharma, then-CEO of solar manufacturer Solaria, admitted
that while “there is a gold rush feeling” to solar, “there’s also real gold here—or, in our case,
sunshine.” But rushing to embrace the convention sent scores of solar panel companies—Q-Cells,
Evergreen Solar, SpectraWatt, and even Gross’s own Energy Innovations, to name just a few—from
promising beginnings to bankruptcy court very quickly. Each of the casualties had described their
bright futures using broad conventions on which everybody agreed. Great companies have secrets:
specific reasons for success that other people don’t see.


Cleantech entrepreneurs aimed for more than just success as most businesses define it. The cleantech
bubble was the biggest phenomenon—and the biggest flop—in the history of “social
entrepreneurship.” This philanthropic approach to business starts with the idea that corporations and
nonprofits have until now been polar opposites: corporations have great power, but they’re shackled
to the profit motive; nonprofits pursue the public interest, but they’re weak players in the wider
economy. Social entrepreneurs aim to combine the best of both worlds and “do well by doing good.”
Usually they end up doing neither.
The ambiguity between social and financial goals doesn’t help. But the ambiguity in the word
“social” is even more of a problem: if something is “socially good,” is it good for society, or merely
seen as good by society? Whatever is good enough to receive applause from all audiences can only
be conventional, like the general idea of green energy.
Progress isn’t held back by some difference between corporate greed and nonprofit goodness;
instead, we’re held back by the sameness of both. Just as corporations tend to copy each other,
nonprofits all tend to push the same priorities. Cleantech shows the result: hundreds of
undifferentiated products all in the name of one overbroad goal.
Doing something dif erent is what’s truly good for society—and it’s also what allows a business to
profit by monopolizing a new market. The best projects are likely to be overlooked, not trumpeted by
a crowd; the best problems to work on are often the ones nobody else even tries to solve.


Tesla is one of the few cleantech companies started last decade to be thriving today. They rode the
social buzz of cleantech better than anyone, but they got the seven questions right, so their success is
TECHNOLOGY. Tesla’s technology is so good that other car companies rely on it: Daimler uses Tesla’s
battery packs; Mercedes-Benz uses a Tesla powertrain; Toyota uses a Tesla motor. General
Motors has even created a task force to track Tesla’s next moves. But Tesla’s greatest
technological achievement isn’t any single part or component, but rather its ability to integrate
many components into one superior product. The Tesla Model S sedan, elegantly designed from
end to end, is more than the sum of its parts: Consumer Reports rated it higher than any other car
ever reviewed, and both Motor Trend and Automobile magazines named it their 2013 Car of the
TIMING. In 2009, it was easy to think that the government would continue to support cleantech:
“green jobs” were a political priority, federal funds were already earmarked, and Congress
even seemed likely to pass cap-and-trade legislation. But where others saw generous subsidies
that could flow indefinitely, Tesla CEO Elon Musk rightly saw a one-time-only opportunity. In
January 2010—about a year and a half before Solyndra imploded under the Obama
administration and politicized the subsidy question—Tesla secured a $465 million loan from the
U.S. Department of Energy. A half-billion-dollar subsidy was unthinkable in the mid-2000s. It’s
unthinkable today. There was only one moment where that was possible, and Tesla played it
MONOPOLY. Tesla started with a tiny submarket that it could dominate: the market for high-end electric
sports cars. Since the first Roadster rolled off the production line in 2008, Tesla’s sold only
about 3,000 of them, but at $109,000 apiece that’s not trivial. Starting small allowed Tesla to
undertake the necessary R&D to build the slightly less expensive Model S, and now Tesla owns
the luxury electric sedan market, too. They sold more than 20,000 sedans in 2013 and now Tesla
is in prime position to expand to broader markets in the future.
TEAM. Tesla’s CEO is the consummate engineer and salesman, so it’s not surprising that he’s
assembled a team that’s very good at both. Elon describes his staff this way: “If you’re at Tesla,
you’re choosing to be at the equivalent of Special Forces. There’s the regular army, and that’s
fine, but if you are working at Tesla, you’re choosing to step up your game.”
DISTRIBUTION. Most companies underestimate distribution, but Tesla took it so seriously that it decided
to own the entire distribution chain. Other car companies are beholden to independent
dealerships: Ford and Hyundai make cars, but they rely on other people to sell them. Tesla sells
and services its vehicles in its own stores. The up-front costs of Tesla’s approach are much
higher than traditional dealership distribution, but it affords control over the customer
experience, strengthens Tesla’s brand, and saves the company money in the long run.
DURABILITY. Tesla has a head start and it’s moving faster than anyone else—and that combination

means its lead is set to widen in the years ahead. A coveted brand is the clearest sign of Tesla’s
breakthrough: a car is one of the biggest purchasing decisions that people ever make, and
consumers’ trust in that category is hard to win. And unlike every other car company, at Tesla
the founder is still in charge, so it’s not going to ease off anytime soon.
SECRETS. Tesla knew that fashion drove interest in cleantech. Rich people especially wanted to
appear “green,” even if it meant driving a boxy Prius or clunky Honda Insight. Those cars only
made drivers look cool by association with the famous eco-conscious movie stars who owned
them as well. So Tesla decided to build cars that made drivers look cool, period—Leonardo
DiCaprio even ditched his Prius for an expensive (and expensive-looking) Tesla Roadster.
While generic cleantech companies struggled to differentiate themselves, Tesla built a unique
brand around the secret that cleantech was even more of a social phenomenon than an
environmental imperative.


Just as the legal attack on Microsoft was ending Bill Gates’s dominance, Steve Jobs’s return to Apple
demonstrated the irreplaceable value of a company’s founder. In some ways, Steve Jobs and Bill
Gates were opposites. Jobs was an artist, preferred closed systems, and spent his time thinking about
great products above all else; Gates was a businessman, kept his products open, and wanted to run the
world. But both were insider/outsiders, and both pushed the companies they started to achievements
that nobody else would have been able to match.

A college dropout who walked around barefoot and refused to shower, Jobs was also the insider
of his own personality cult. He could act charismatic or crazy, perhaps according to his mood or
perhaps according to his calculations; it’s hard to believe that such weird practices as apple-only
diets weren’t part of a larger strategy. But all this eccentricity backfired on him in 1985: Apple’s
board effectively kicked Jobs out of his own company when he clashed with the professional CEO
brought in to provide adult supervision.
Jobs’s return to Apple 12 years later shows how the most important task in business—the creation
of new value—cannot be reduced to a formula and applied by professionals. When he was hired as
interim CEO of Apple in 1997, the impeccably credentialed executives who preceded him had
steered the company nearly to bankruptcy. That year Michael Dell famously said of Apple, “What
would I do? I’d shut it down and give the money back to the shareholders.” Instead Jobs introduced
the iPod (2001), the iPhone (2007), and the iPad (2010) before he had to resign in 2011 because of
poor health. By the following year Apple was the single most valuable company in the world.
Apple’s value crucially depended on the singular vision of a particular person. This hints at the
strange way in which the companies that create new technology often resemble feudal monarchies
rather than organizations that are supposedly more “modern.” A unique founder can make
authoritative decisions, inspire strong personal loyalty, and plan ahead for decades. Paradoxically,
impersonal bureaucracies staffed by trained professionals can last longer than any lifetime, but they
usually act with short time horizons.

The lesson for business is that we need founders. If anything, we should be more tolerant of
founders who seem strange or extreme; we need unusual individuals to lead companies beyond mere
The lesson for founders is that individual prominence and adulation can never be enjoyed except
on the condition that it may be exchanged for individual notoriety and demonization at any moment—
so be careful.
Above all, don’t overestimate your own power as an individual. Founders are important not
because they are the only ones whose work has value, but rather because a great founder can bring out
the best work from everybody at his company. That we need individual founders in all their
peculiarity does not mean that we are called to worship Ayn Randian “prime movers” who claim to
be independent of everybody around them. In this respect Rand was a merely half-great writer: her
villains were real, but her heroes were fake. There is no Galt’s Gulch. There is no secession from
society. To believe yourself invested with divine self-sufficiency is not the mark of a strong
individual, but of a person who has mistaken the crowd’s worship—or jeering—for the truth. The
single greatest danger for a founder is to become so certain of his own myth that he loses his mind.
But an equally insidious danger for every business is to lose all sense of myth and mistake
disenchantment for wisdom.



IF EVEN THE MOST FARSIGHTED founders cannot plan beyond the next 20 to 30 years, is there anything to say about
the very distant future? We don’t know anything specific, but we can make out the broad contours.
Philosopher Nick Bostrom describes four possible patterns for the future of humanity.
The ancients saw all of history as a neverending alternation between prosperity and ruin. Only
recently have people dared to hope that we might permanently escape misfortune, and it’s still
possible to wonder whether the stability we take for granted will last.

However, we usually suppress our doubts. Conventional wisdom seems to assume instead that the
whole world will converge toward a plateau of development similar to the life of the richest
countries today. In this scenario, the future will look a lot like the present.

Given the interconnected geography of the contemporary world and the unprecedented destructive
power of modern weaponry, it’s hard not to ask whether a large-scale social disaster could be
contained were it to occur. This is what fuels our fears of the third possible scenario: a collapse so
devastating that we won’t survive it.

The last of the four possibilities is the hardest one to imagine: accelerating takeoff toward a much
better future. The end result of such a breakthrough could take a number of forms, but any one of them
would be so different from the present as to defy description.

Which of the four will it be?
Recurrent collapse seems unlikely: the knowledge underlying civilization is so widespread today
that complete annihilation would be more probable than a long period of darkness followed by
recovery. However, in case of extinction, there is no human future of any kind to consider.
If we define the future as a time that looks different from the present, then most people aren’t
expecting any future at all; instead, they expect coming decades to bring more globalization,
convergence, and sameness. In this scenario, poorer countries will catch up to richer countries, and
the world as a whole will reach an economic plateau. But even if a truly globalized plateau were
possible, could it last? In the best case, economic competition would be more intense than ever
before for every single person and firm on the planet.
However, when you add competition to consume scarce resources, it’s hard to see how a global
plateau could last indefinitely. Without new technology to relieve competitive pressures, stagnation is
likely to erupt into conflict. In case of conflict on a global scale, stagnation collapses into extinction.
That leaves the fourth scenario, in which we create new technology to make a much better future.
The most dramatic version of this outcome is called the Singularity, an attempt to name the imagined
result of new technologies so powerful as to transcend the current limits of our understanding. Ray
Kurzweil, the best-known Singularitarian, starts from Moore’s law and traces exponential growth
trends in dozens of fields, confidently projecting a future of superhuman artificial intelligence.
According to Kurzweil, “the Singularity is near,” it’s inevitable, and all we have to do is prepare
ourselves to accept it.
But no matter how many trends can be traced, the future won’t happen on its own. What the
Singularity would look like matters less than the stark choice we face today between the two most
likely scenarios: nothing or something. It’s up to us. We cannot take for granted that the future will be
better, and that means we need to work to create it today.
Whether we achieve the Singularity on a cosmic scale is perhaps less important than whether we
seize the unique opportunities we have to do new things in our own working lives. Everything
important to us—the universe, the planet, the country, your company, your life, and this very moment
—is singular.
Our task today is to find singular ways to create the new things that will make the future not just
different, but better—to go from 0 to 1. The essential first step is to think for yourself. Only by seeing

our world anew, as fresh and strange as it was to the ancients who saw it first, can we both re-create
it and preserve it for the future.


Jimmy Kaltreider for helping to think this book through.
Rob Morrow, Scott Nolan, and Michael Solana for co-creating the Stanford class