Thiel delivered lectures on startups at Stanford in 2012. They’re all online here.

These are superbly interesting. I’ve decided to record here my personal favorite parts.

Class 1: The Challenge of the Future

We might describe our world as having retail sanity but wholesale madness. Details are well understood while the big picture remains unclear.

All successful companies are different; they figured out the 0 to 1 problem in different ways. But all failed companies are the same; they botched the 0 to 1 problem.

We tend to think very statistically about the future. And statistics tells us that it’s random. We can’t predict the future; we can only think probabilistically. If the market follows a random walk, there’s no sense trying to out-calculate it.

Companies exist because they optimally address internal and external coordination costs. In general, as an entity grows, so do its internal coordination costs. But its external coordination costs fall. Totalitarian government is entity writ large; external coordination is easy, since those costs are zero. But internal coordination, as Hayek and the Austrians showed, is hard and costly; central planning doesn’t work.

Severe coordination problems may stem from something as seemingly trivial or innocuous as a company having a multi-floor office.

The easiest answer to “why startups?” is negative: because you can’t develop new technology in existing entities. There’s something wrong with big companies, governments, and non-profits.

The intellectual rephrasing of these questions is: What important truth do very few people agree with you on? The business version is: What valuable company is nobody building?

Class 2: Party like it’s 1999?

We are all born into a particular culture at a particular time. That culture is like an extended dinner conversation; lots of people are talking, some lightly, some angrily, some loudly, some in whispers.

It is questionable whether one can really understand startups without, say, knowing about Webvan or recognizing the Pets.com mascot.

Most of the 1990s was not the docom bubble. Really, what might be called the mania started in September 1998 and lasted just 18 months. The rest of the decade was a messier, somewhat chaotic picture.

The 1990’s could be said to have started in November of 1989. The Berlin Wall came down. Two months of pretty big euphoria followed.

In 1998, the Ruble crisis hit Russia. These were unique animals in that usually, either banks go bust or your currency goes worthless. Here, we saw both. So your money was worthless, and the banks had none of it. Zero times zero is zero.

The technology bubble was an indirect proof; the old economy was proven not to work, as we could no longer compete with Mexico or China. Emerging markets were proven failures, rife with cronyism and mismanagement. Europe offered little hope. And no one wanted to invest with leverage after the LTCM disaster.

Proof by contradiction is a dangerous way to draw conclusions. The world is not always a logical place. So even if something’s not A,B,C, or D, it doesn’t necessarily follow that the truth is E.

There’s no shortage of anecdotes. There were 40-year-old grad students at Stanford who were trying to start dozens of rather wacky companies. Now, usually being a forty-something grad student means you’ve gone insane. And usually, trying to start several companies at once is seen as unwise. But in late 1998, many people believed this to be a winning combination.

The founders agreed that PayPal could not afford to hire sketchy people. So they just hired their friends instead.

The PayPal team reached an important conclusion: BD didn’t work. They needed organic, viral growth. They needed to give people money.

7 to 10% daily growth and 100 million users was good. No revenues and an exponentially growing cost structure was not.

A South Korean firm that really wanted to invest called up PayPal’s law firm to ask where they could wire funds to invest. It promptly wired $5 million without any documents or negotiating a deal. The Koreans absolutely refused to say where PayPal could send the money back.

For bubble and anti-bubble thinking are both wrong because they hold the truth is social.

If the herd isn’t thinking at all, being contrarian – doing the opposite of the herd – is just as random and useless.

Class 3: Value Systems

Enemies in the War on Fraud were many. There was “Carders World,” a dystopian web marketplace that vowed to bring down Western Capitalism by transacting in stolen identities.

The term “perfect competition” seems pregnant with some normative meaning. It’s not called “insane competition” or “ruthless competition.” Thats probably not an accident. Perfect competition, we’re told, is perfect.

Globalization seems to have a very competitive feel to it. It’s like a track and field sprint event where one runner is winning by just a few seconds, with others on his heels. That’s great and exciting if you’re the spectator. But it’s not a natural metaphor for real progress.

The single business idea you hear most often is: the bigger your market, the better. That is utterly, totally wrong. The restaurant business is a huge market. It is also not a very good way to make money.

Well-defined, well-understood markets are simply harder to master.

Class 4: The Last Mover Advantage

Too often in the race to compete, we learn to confuse what is hard with what is valuable.

The pithy, wry version of this is the line about Rhodes Scholars: they all had a great future in the past.

Henry Kissinger’s anti-academic line aptly describes the conflation of difficulty and value: in academia the battles are so fierce because the stakes are so small.

Just look at high school, which for Stanford students and the like, was not a model of perfect competition. It probably looked more like extreme asymmetric warfare; it was machine guns versus bows and arrows. No doubt that’s fun for the top students. But then you get up to college and the competition amps up. Even more so during grad school. Things in the professional world are often worst of all; at every level, people are just competing with each other to get ahead.

Top high school students who arrive at elite universities quickly find out that the competitive bar has been raised. But instead of questioning the existence of the bar, they tend to try to compete their way higher.

Universities deal with this problem in different ways. Princeton deals with it through enormous amounts of alcohol. Yale blunts the pain by encouraging people to pursue extremely esoteric humanities studies. Harvard sends its students into the eye of the hurricane. Everyone just tries to compete even more.

If a bearish investor reminds you that 90% of restaurants fail within 2 years, you’ll come up with a story about how you’re different. You’ll spend time trying to convince people you’re the only game in town instead of seriously considering whether that’s true.

There are three steps to creating a truly valuable tech company. First, you want to find, create, or discover a new market. Second, you monopolize that market. Then you figure out how to expand that monopoly over time.

What is amazing about Amazon was how they were able to gradually scale from bookstore to the world’s general store.

Zynga wants the narrative to be about hardcore psychometric sauce. it’s a better company if it’s figured out how psychological and mathematical laws give it permanent monopoly status. Zynga wants, perhaps needs, to be able to truthfully say: “We know how to make people buy more sheep, and therefore we are a permanent monopoly.”

The best way to fail is to start big and then shrink.

Disruptive companies tend not to succeed. Disruptive kids get sent to the principal’s office. Just look at Napster.

The time to build a car company was the time when car technology was being created. The last major car company that got started is the American Motors Corporation in 1954.

An important subquestion is whether, given a gold rush, you’d rather be a gold digger or the guy selling shovels.

Why should the 20th employee join your company? If you have a great answer, you’re on the right track. The right answer has to be that you’re creating some sort of monopoly business.

Class 5: The Mechanics of the Mafia

Cults are crazy and idealistic in a bad way. Cult members all tend to be fanatically wrong about something big.

You want your people to be different in a way that gives the company a strong sense of identity and yet still dovetails with the overall mission.

Engineers and STEM people tend to be highly intelligent, good at problem solving, and naturally non zero-sum. Athletes tend to be highly motivated fighters; you can only win if the other guy loses.

The problem with a company made up of nothing but athletes is that it will be biased towards competing. Athletes like competition because, historically, they’ve been good at it. So they’ll identify areas where there is tons of competition and jump into the fray.

The problem with a company made up of nothing but nerds is that it will ignore the fact that there may be situations where you have to fight.

The notion that diversity in an early team is important or good is completely wrong. You should try to make the early team as non-diverse as possible.

In a team, an n-squared communications problem emerges. In a five-person team, there are something like 25 pairwise relationships to manage and communications to maintain. The more diverse the early group, the harder it is for people to find common ground.

The most talented folks are almost always quirky. Watch for the quirks and embrace them. Nothing is stranger than watching a quirky entrepreneur criticize another quirky entrepreneur for being too quirky.

The management team at PayPal was very frequently incompatible. Management meetings were not harmonious. Board meetings were even worse. They were certainly productive meetings. Decisions were made and things got done. But people got called idiots if they deserved it.

If people complain about people behind each other’s backs, you have a problem. If people don’t trust each other to do good work, you have a problem. But if people know that their teammates are going to deliver, you’re good.

Even though people would physically fight on the engineering room floor, if you ever asked PayPal people if they respected each other, the answer was obvious. For a long time, everyone believed in everyone else.

The standard view is that companies get destroyed by external competition. Maybe that’s true in the long run. But in the short run, they get destroyed internally. They are complex entities with complex dynamics. Usually those dynamics blow up before some predator from the wider ecosystem strikes.

If you graduate Stanford at 22 and Google recruits you, you’ll work a 9-to-5. It’s probably more like an 11-to-3 in terms of hard work. They’ll pay well, it’s relaxing, but what they’re actually doing is paying you to accept a much lower intellectual growth rate. When you recognize that intelligence is compounding, the cost of that missing long-term compounding is enormous. They’re not giving you the best opportunity of your life. You might realize one day that you’ve lost your competitive edge. You won’t be the best anymore.

Arguing about smart marketing moves or different approaches to solving tactical or strategic problems is fundamental. These are decisions that actually matter. Avoid groupthink in these areas is key.

Class 6: Thiel’s Law

Beginnings of things are very important. Beginnings are qualitatively different.

The importance of foundings is embedded in companies. Where there’s a debate or controversial claim at Google, one says, “The Founders have scientifically determined that x is true,” where x is his preferred position.

Once the paradigm shifts from 1 to n, the founding is over.

Good, high-trust people with low alignment structure is basically anarchy. Talented people could work on all sorts of different projects and generally operate without a whole lot of constraints.

Sometimes the opposite combination – low trust people and lots of rules – can work too. This is basically totalitarianism. Foxconn might be a representative example.

The low-trust, low-alignment model is the dog-eat-dog sort of world. People you might not trust can do a lot of whatever they want. An investment bank might be a good example.

The ideal is the combination of high-trust people with a structure that provides a high degree of alignment. People trust each other and together create a good culture. But there’s a good structure to it, too. People are rowing in the same direction, and not by accident.

If the founders are in sync, you can move on to the rest of the company. But if they aren’t, it will blow up the company.

You should set up as a Delaware C corporation. That is the right answer.

Experience has shown that there is great predictive power in a venture-backed CEO’s salary: the lower it is, the better the company tends to do.

Being part-time, holding other jobs, or bringing on consultants or advisors to do important work are big red flags because those arrangements are very mis-aligning.

Class 7: Follow the Money

The more a VC understands the skew pattern, the better the VC. Bad VCs tend to think that all companies are created equal, that some just fail, spin wheels, or grow. In reality, you get a power law distribution.

It’s troubling if a startup insists that it’s going to make money in many different ways. The power law distribution on revenues says that one source of revenue will dominate everything else.

People who are most heavily motivated by money are never the ones who make the most money in the power law world.

If you go to an incubator that’s not Y-Combinator, that is perceived as a negative credential. It’s like getting a degree at Berkeley.

You can discover a lot about founders by asking them about their choices. What are the key decisions you faced in your life and what did you decide? What were the alternatives? Why did you go to this school? Why did you move to this city?

Class 8: The Pitch

Be funny and help your cause. In the tech community, even one joke will suffice.

Raising too much can haunt you. Map out your operating expenses for one year, multiply that figure by 1.5, and ask for that, as a first approximation.

It helps to pitch as early as possible in the day.

When you make your ask, don’t give them tons of different financing options or packages or other attempts at optimization. That will burden them with a cognitive load that will make them unhappy. Keep it simple.

No senior VC needs to do your investment. You should never forget that.

Do not rely on VCs to draw key inferences. They may, but why risk it?

There’s a romantic notion that th eonly thing that matters is product and that you can devote yourself to that entirely. That is false. In fact, fully half of your job is selling the company because the CEO is the only one who can pitch effectively. No VP wants to be pitched by the VP of Sales.

Make an affirmative statement about what you do and why it’s important. SpaceX has a great elevator pitch: “Launch costs haven’t come down in decades. We slash them by 90%. The market is $XX billion.” Contrast this pitch with: “We’re NASA meets Toyota!”

You need a deck to explain your idea. Don’t pitch without one. There will be zero VC interest without a deck, so you need to make one. A deck is written propaganda. It will be emailed around and therefore must stand alone. It is a means of presenting data within a narrative that people read by themselves.

One trick to further exploit the natural deficiencies of your victim: at some point, the junior analyst will be dispatched to analyze your company. You should thus write text that the junior analyst can plagiarize.

… and so begins the VC equivalent of the Bataan Death March. Too many people are determined to finish: you made all these slides, and, dammit, you’re going to get through them.

Your only chance is to have a straightforward, content-rich deck, and then to leave it behind as soon as possible.

It’s cognitively efficient for VCs to say no. So try to be perfect. If you give them any reason to say no, they will.

A trick that smart law students understand is to underline key phrases. Professors never actually test 15 important concepts in any given question on a law exam. So if you underline those concepts on the paper, the professor sees them. The professor probably won’t even take the time to see if you’ve correctly embedded those concepts. You’ve made grading easy, and you get an A.

An aside: Do not ask for an NDA. Ever. You will be perceived as a rank amateur.

Give anyone on your side sufficient ammunition to defend your company to their coworkers. VCs love to poke holes in their partners’ proposed investments – it’s part of the lemon detection process.

At some point there will be talk about a business model. Just have something reasonable to say about this. For young companies, it’s almost certainly a total work of fiction since it will probably change.

Being able to talk about revenue, sales processes, customer acquisition, and barriers to entry/exit shows your VCs that you’re not that naive.

Why were you considering Yale? For the same reason you considered Harvard: it’s a top school.

Put together a data room for your investors. Almost no one does this. It’s hard to understand why. Not having a data room leads to 1000 emails asking for stuff that should have been put in a data room.

The worst thing ever is when people who aren’t yet a company pitch you for an investment. VCs are supposed to invest in companies, not create and build a company for you. Do not pitch until you’re a company. No one wants to be pitched just an idea or product.

Class 9: If you build it, will they come?

Compared to other components that people generally recognize are important, distribution gets the short shift. People understand that team, structure, and culture are important. But for whatever reason, people do not get distribution. They tend to overlook it. It is the single topic whose importance people understand least. Even if you have an incredibly fantastic product, you still have to get it out to people. The engineering bias blinds people to this simple fact. The conventional thinking is that great products sell themselves.

The first thing to do is to dispel the belief that the best product always wins. There is a rich history of instances where the best product did not, in fact, win. (See: Tesla, Edison; and: Tesla, Marconi.)

About 610,000 people work in the U.S. ad industry. It’s a $95 billion market. Advertising matters because it works. There are competing products in the market. You have preferences about many of them. These preferences are probably shaped by advertising.

Advertising works only on other people, right? But exactly how that’s true for everybody in the world is a strange question indeed.

The U.S. sales industry is even bigger than advertising. Some 3.2 milliion people are in sales. It’s a $450 billion industry.

Sales is hidden. Advertising is hidden. It works best that way.

Pretty much anyone involved in any distribution role, be it sales, marketing, or advertising should have job titles that have nothing to do with these things. Having a job title that’s different from what you actually do is an important move in the game. It goes to the question of how we don’t want to admit we’re being sold to.

Sales isn’t very transparent at all. We are tempted to lump all salespeople in with vacuum cleaner salesmen, but really there is a whole set of gradations. There are amateurs, mediocrities, experts, masters, and even grandmasters.

If you work at a big company, you have two choices. You can become something like an international tax accountant. It’s specialized and really hard. It’s also transparent in that it’s clear whether you’re an expert or not.

The other choice is to be a politician. These people get ahead by being nice to others and getting everyone to like them. Both expert and politician can be successful trajectories. But what tends to happen is that people choose to become politicians rather than experts because it seems easier. Politicians seem like average people, so average people simply assume that they can do the same thing.

Top salespeople get paid extremely well. But average salespeople don’t, really.

People probably thought sales was easy and undifferentiated. So they tried it and learned their error the hard way.

The really good politicians are much better than you think. Great salespeople are much better than you think. But it’s always deeply hidden.

Great distribution can give you a terminal monopoly, even if your product is undifferentiated. The converse is that product differentiation itself doesn’t get it anywhere. Nikola Tesla went nowhere because he didn’t nail distribution.

But understanding the critical importance of distribution is only half the battle; a company’s ideal distribution effort depends on many specific things that are unique to its business.

David Sacks: “Networking is not working!” and “Networking is NOTworking!”

There is a fairly serious structural market problem that’s worth addressing. On the right side of the distribution you have larger ticket items where you have an actual person driving the sale. This is Palantir and SpaceX. On the extreme left-hand side of the spectrum you have mass marketing and advertising.

If you can’t solve the distribution problem, your product doesn’t get sold, even if it’s a really great product.

Where distribution is a hard nut to crack, getting it right may be most of what you need.

To gain a significant advantage, your marketing strategy must be very hard to replicate.

Advertising’s historical opaqueness is probably the core of why Google is so valuable; Google was the first company that enabled people to figure out whether advertising actually worked.

Everyone knows that Zynga experienced great viral growth as its games caught on. Less known is that they spent a lot of money on targeted advertising. That allowed them to monetize users much more aggressively than people thought possible.

There is an interesting double standard. There are an awful lot of websites whose business model is ad sales. And then they turn around and say that they don’t actually believe that ads are a good way of getting customers.

There is a lot of room for creativity in distribution strategy.

William Shatner and James Doohan seemed similar. In fact they’re a world apart. Salesmen may seem similar. But some get Cadillac’s, while others get steak knives. Still others get fired and end up as characters in novels.

Marketing people can’t do viral marketing. You don’t just build a product and then choose viral marketing. There is no viral marketing add-on. Anyone who advocates viral marketing in this way is wrong and lazy.

Just as it’s a mistake to think that you’ll have multiple equal revenue streams, you probably won’t have a bunch of equally good distribution strategies.

Poor distribution is the number one cause of failure. If you can get even a single distribution channel to work, you have a great business.

When you drill down on all these people who claim to be authentic, you get a weird sense that it’s all undifferentiated. Fashionable people all wear the same clothes.

Class 10: After Web 2.0

The emphasis of Web 2.0 is on user-generated content, social networking, and collaboration of one sort of another.

People have been betting on mobile for years. Most of them were far too early. Everyone who tried mobile back in ‘99 failed. No one thought that the best mobile investment would be to buy a bunch of Apple stock.

Computers may well end up replacing a lot of legal services currently provided by humans. There’s a sense in which things remain inefficient because people – very oddly – trust lawyers more than computers.

The great irony of the ‘90s were basically correct. They were just too early.

Entrepreneurs are congenitally wired to be too early. And being too early is a bigger problem for entrepreneurs than not being correct.

The people who did see the crash are deeply psychologically scarred. Like burned-my-face-on-the-stove scarred. They are irreparably damaged. These are the people who love to talk about bubbles. Anywhere and everywhere they have to find a bubble.

This kind of scarring just doesn’t go away. It has to be killed off. People who suffered through the crash of 1929 never believed in stocks again. They literally had to die off before a new generation of professional investors got back into stocks and the market started to grow again.

We should never take it at face value when successful companies say they do no sales or marketing. Because that, in itself, is probably a sales pitch.

We hear it all the time: “We’ll be like Salesforce.com – no sales team required, since the product will sell itself.” This is always puzzling. Salesforce.com has a huge, modern sales force. The tagline is “No software,” not “No sales.” Andreessen Horowitz is a sucker for people who have sales and marketing figured out.

It’s like surfing. The goal is to catch a big wave. If you think a big wave is coming, you paddle really hard. Sometimes there’s no way, and that sucks. But you can’t just want to be sure there’s a wave before you start paddling. You’ll miss it entirely. You have to paddle early, and then let the wave catch you. The question is, how do you figure out when the next big wave is likely to come?

At the margins, it’s better to err on the side of paddling where there’s no wave than paddling too late and missing a good wave. Trying to start the next great social network company is current wave thinking.

Citibank’s core competency could be said to be political savvy and navigating through bureaucracy.

If you want your board to do things effectively, it should be small. Three people is the best size.

Non-profit organizations sometimes have boards of 50 people or more. This provides an incredible benefit to whatever quasi-dictatorial person who runs the non-profit. A board of that size effectively means no checks on management.

What’s ideal is to have a founder/CEO who’s a product person.

At Andreessen Horowitz we think that being CEO is a learnable skill. This is controversial in the VC world.

It’s fair to say that the most important companies are founded and run by people who haven’t been CEO before.

One thing to learn is that managing people is different from managing managers. Managing managers is scalable. Managing people is not. Once you learn how to manage managers, you’re well on your way to be CEO.

It’s very difficult to learn about startups if you go work at Microsoft or Google. They are great companies with phenomenal people. But there are shockingly few companies started by these people. One theory is that they are too sheltered. They are just too far removed from the startup processes.

The skill you learn at IBM is how to exist at IBM. It’s completely self-referential. It’s a terminal state. People don’t leave.

Class 11: Secrets

Discovery is the process of exposing secrets. The secrets are dis- covered: the cover is removed from the secret.

Conventions can get covered up and become secrets again. It’s often the case that people stop believing things that they or previous generations had believed in the past.

The big secrets discussed so far have involved monopoly vs. competition, the power law, and the importance of distribution.

Kacynski argued that people are depressed because the only things left are easy things or impossible things.

What you can do, even kids can do. But what you can’t do, even Einstein couldn’t do. So Kacynski’s idea was to destroy technology, get rid of all bureaucracy and technical processes, and let people start over and work on hard problems anew.

Cool people make some ironic antitech juxtapositional statement and thereby become even cooler. Never mind that gears and brakes on bikes are actually pretty useful; hipsters do without.

Now you can’t really be an explorer anymore. At least it’s very hard to explore the unexplored.

Some 90% of the inhabited ocean is deep sea. There have been only about 200 hours of human exploration there.

Four primary things have been driving people’s disbelief in secrets. First is the pervasive incrementalism in our society.

Second, people are becoming more risk averse. The prospect of dedicating your life to something that no one else believes in is hard enough. It would be unbearable if you turned out to be wrong.

Third is complacency.

Finally, some pull towards egalitarianism is driving us away from secrets. We find it increasingly hard to believe that some people have important insights into reality that other people do not.

In the economics context, disbelieving in secrets leads to the conclusion that markets are completely efficient. But we know that’s not true. We have experienced decades of extraordinary inefficiencies.

Andrew Wiles started working on Fermat’s Last Theorem in 1986. He managed to prove it in 1995. No one would ever succeed in doing these incredibly hard things if they didn’t think that it was possible.

Two distinct questions to ask are: What secret is nature not telling you? And what secrets are people not telling you?

If you think that these secrets are foundational, you end up concluding that physics is the fundamental science. Studying nature becomes the most important thing you could possibly do. This is why physids ph.d’s are notoriously difficult to work with; because they know fundamental things, they think they know all things. It’s not clear how many levels up that logic can go without getting too twisted.

One way to get started thinking about secrets is to think about majors that aren’t at Stanford. Physics, for example, is a real major at all real universities. So ignore it for a moment. The opposite of physics might be nutrition. Stanford doesn’t have it. Real universities don’t let you major in nutrition. That might mean we’re on to something.

The food groups are probably completely wrong at this point. The pyramid that tells us to eat low-fat and ridiculous amounts of grains and carbohydrates were probably more a result of Kelloggs’ lobbying than actual science.

Could you start a cleantech company that embraced the dynamic and focused on making a fashion statement? The answer is yes. You could start Tesla, which is exactly what Elon Musk did.

The basic challenge is to find things that are hard but doable. You want to find a frontier. But don’t simply accept the definition of other people of the frontier. Existing priorities and ways of thinking need not be your own.

In a world with many secrets, the best companies may be hidden. The power law is the same. Your job in a secretive world is to identify the hidden companies with the potential to be the best. What potentially great company are people overlooking?

Class 12: War and Peace

A working theory is thus that you must choose your enemies well, since you’ll soon become just like them.

The Kissinger line on this was that “the battles are so fierce because the stakes are so small.”

It unfolds like this: conflict breaks out. People become obsessed with the people they’re fighting. As things escalate, the fighters become more and more alike. In many cases it moves beyond motivational theater and leads to all out destruction. The losers lose everything. And even the winners can lose big. It happens all the time. So we have to ask: how often is all this justified? Does it ever make sense? Can you avoid it altogether?

There are two competing paradigms one might use to think about conflict. The first is the Karl Marx version. Conflict exists because people disagree about things. The greater the differences, the greater the conflict. The bourgeoisie fights the proletariat because they have completely different ideas and goals.

The other version is Shakespeare. This could be called the external perspective on fighting; from the outside, all combatants sort of look alike. It’s clear why they’re fighting each other. Consider the opening line from Romeo and Juliet: Two households, both alike in dignity.

So which perspective is right in the tech world? How much is Marx? How much is Shakespeare? In the great majority of cases, it’s straight Shakespeare.

Look at the computer industry in the 1970s. It was dominated by IBM. But there were a bunch of other players, like NCR, Control Data, and Honeywell. Note that those are longer common names in computer technology. At the time, all these companies were trying to build mini computers that were competitive with IBM’s. Each offering was slightly different. But conceptually they were quite similar. As a result of their myopia, these companies completely missed the microcomputer. IBM managed to develop the microprocessor and eclipsed all its competitors in value.

The crazy ‘90s version of this was the fierce battle for the online pet store market. It was Pets.com vs. PetStore.com vs. Petopia.com vs. about 100 others. The internal narrative focused on an absolute fight to dominate online pet supplies. How could the enemy be defeated? Who could afford the best Super Bowl ads? And so on. The players totally lost sight of the external question of whether the online pet supply market was really the right space to be in.

But what was strange was that they weren’t really aimed at customers; they were aimed at each other, and each other’s employees. It was all intended to be motivational theater. Ellison’s theory was that one must always have an enemy.

The formula was theater + motivation = productivity. The flaw was that creating fake enemies for motivation often leads to real enemies that bring destruction.

In 2007, it was Microsoft vs. Google. But fighting is costly. And those who avoid it can often swoop in and capitalize on the peace.

But the focus wasn’t on objective productivity or usefulness; the focus was on beating X.com. During one of the daily updates on how to win the war, one of the engineers presented a schematic of an actual bomb that he had designed. That plan was quickly axed and the proposal attributed to extreme sleep deprivation.

If you do have to fight a war, you must use overwhelming force and end it quickly. If you take seriously the idea that you must choose your enemies well since fighting them will make you like them, you want wars to be short. Your strategy must be shock and awe—real shock and awe, not the fake kind that gets you a 10-year war.

At PayPal each person had just one thing that he or she was supposed to do. And every person’s thing was different from everyone else’s. This wasn’t very popular, at least initially. People were more ambitious. They wanted to do three or four things. But instead they got to do one thing only. It proved to be a very good way to focus people on getting stuff done instead of focusing on one another. Focusing on your enemy is almost always the wrong thing to do.

A good intermediate lesson in chess is that even a bad plan is better than no plan at all. Having no plan is chaotic. And yet people default to no plan.

You should either like what you’re doing, believe it’s a direct plan to something else, or believe it’s an indirect plan to something else. Just adding a resume lines every two years thinking it will buy you options is bad.

Groupon, for instance, couldn’t be created here. They need 3,000 salespeople. That is not the game that Silicon Valley specializes in. It worked very well in Chicago.

One anti-New York perspective is that the media industry plays much bigger role there than it does here. That induces a lot of competition because people focus on each other, and not on creating things. New York is structurally more competitive in all sorts of ways. People literally live on top of each other. They’re trained to fight and enjoy fighting.

Class 13: You are not a lottery ticket

Statistical tools are meaningless if you have a sample size of one. It would be great if you could run experiments. Start Facebook 1,000 times under identical conditions. If it works 1,000 out of 1,000 times, you’d conclude it was skill.

A class on startups would be worthless if it simply relayed a bunch of stories about people who won lotteries. There is something very odd about a guide to playing slot machines.

If the future is determinate, it makes much more sense to have firm convictions. You won’t join tons of different clubs or do every single activity. There is just one thing—the best thing—that you should do. This is decidedly not how people build up their resumes these days.

The idea was that the future would get better, but not in ways that you could know. Unlike the determinate future of the past, which contained many secrets, today the future seems to contain very few. There is much more room for mystery. God, Mother Nature, and Market are unknowable and inscrutable. But the universe is still fundamentally benevolent. It is thus best to just figure out incremental things to do and wait for progress to come.

In a determinate world, there are lots of things that people can do. There are thus many things to invest in. You get a high investment rate. In an indeterminate world, the investment rate is much lower. It’s not clear where people should put their money, so they don’t invest.

But instead of investing, companies today are generating huge cash flows—about $1 trillion annually at this point. They are hoarding cash because they have no idea what else to do with it. Almost by definition, you wouldn’t have free cash flows if you knew where or how to invest.

The math version is calculus vs. statistics. In a determinate world, calculus dominates. You can calculate specific things precisely and deterministically. But the indeterminate future is somehow one in which probability and statistics are the dominant modality for making sense of the world. Bell curves and random walks define what the future is going to look like.

How each quadrant shakes out in practice looks something like this:

Optimistic, determinate: Engineering and art. Very specific engagements.

Optimistic, indeterminate: Law and finance.

Pessimistic, indeterminate: Insurance.

Pessimistic, determinate: Wartime rationing.

At his height, Moses was significantly more powerful than the mayor or governor of New York. He pretty much rebuilt all of the state of New York in 30-40 years. From today’s perspective, this is crazy. Surely Moses had too much power.

All this came to an end in 1965, when Moses planned highway that would run through Greenwich Village. A sufficiently large number of people thought that the old buildings that would have to be torn down should be preserved, and protested the development. It was the last time that new highways were built in the state.

John Reber was a teacher and amateur theater producer in San Francisco. In the 1940s he came up with a plan to radically reconstruct the San Francisco Bay Area. The basic plan was to construct two large earth and rock dams, one between San Francisco and Oakland and the second between Marin Country and Richmond. They would drain water from the north and south sides and replace it with freshwater. Some 20,000 acres of land would be filled in. A 32-lane highway would be built. And high-rise buildings would be scattered throughout the thoroughly reconstructed city.

Today, by contrast, the idea would be dismissed as lunacy. This is especially true if it came from someone like John Reber. What credentials does a schoolteacher have for redesigning the entire Bay Area? The John Rebers of the world have long since learned to keep their plans to themselves. Even safer is not to develop any grand plans at all.

In a future of definite optimism, you get underwater cities and cities in space. In a world of indefinite optimism, you get finance.

The big idea in finance is that the stock market is fundamentally random. It’s all Brownian motion.

Think about what happens when someone in Silicon Valley builds a successful company and sells it. What do the founders do with that money? Under indefinite optimism, it unfolds like this:

Founder doesn’t know what to do with the money. Gives it to large bank.

Bank doesn’t know what to do with the money. Gives it to portfolio of institutional investors in order to diversify.

Institutional investors don’t know what to do with money. Give it to portfolio of stocks in order to diversify.

Companies are told that they are evaluated on whether they generate money. So they try to generate free cash flows. If and when they do, the money goes back to investor on the top. And so on.

Money plays a much more important role if the future is indefinite. There, having is always better than specific things. It’s pure optionality, and that optionality encapsulates the indefinite view. In a definite future, by contrast, money is simply a means to an end.

If you think that the future is indeterminate, the most important people are statisticians. Pollsters become more important than politicians.

We have polls on everything. And we believe them to be authoritative—it’s dangerous to try and outthink a statistically shifting bloc of voters. Unsurprisingly, then, politicians react to the polls instead of thinking about the future. This helps explain the strange mystery in 2008 of why John McCain picked Sarah Palin as a running mate. The McCain people reviewed all the polls about Republican governors and senators. Most were very unpopular. Palin, by contrast, had an 89% approval rating in Alaska (some of which seems attributable to Alaskans’ receiving an annual $1000+ oil royalty check). Just parsing poll data, Palin was the obvious choice.

There’s a philosophy version of this too. Marx and Hegel dominate the optimistic determinant quadrant. The future is going to be better and you can do specific things in 5-year plans. Rawls and Nozick are optimistic but indeterminate. The socialistic version is that you should have a welfare state because that’s what people would want behind a veil of ignorance. The libertarian version is that no one really knows anything, so people have to be free to run about and stumble upon success. Plato and Aristotle are squarely pessimistic and definite. You can figure out the nature of things, but there’s no reason to be excited about the future. Epicurus and Lucretius represent pessimistic indeterminacy. The universe is void. Things just bump into each other randomly.

L.A. could have been built from scratch in early 20th century. It would have been magnificent. But there were no grand plans. Instead we got incremental sprawl. The market didn’t solve the problem. L.A. is still one of best cities in world. But it is nowhere near what it could have been. The L.A. experiment at least suggests there are grounds to be pessimistic about indeterminacy.

When people mention Darwinist theory in a business context, they’re probably about to do something really mean.

Apple is absolute antithesis of finance. The corporate strategy is well defined. There are definite, multi-year plans. Things are methodically rolled out.

Companies with really good plans typically do not sell. If your startup gets traction, people make offers to buy it. In an indefinite world, you will take the money and sell, because money is what you want.

Young people today tend to be indeterminately optimistic. They iterate, one resume line at a time. They buy into a narrative of never-ending improvement, even if they have no idea what that path might look like.

Our society has been indeterminately optimistic for the last quarter century. But that quadrant is fraying at edges. We’re falling downwards towards pessimism. Can we shift instead to definite optimism? Computer Science is our best hope. CS is about deterministic as you can get.

Class 14: Seeing Green

You can’t just plan to go and get a new job every 2 years and call it a plan. That’s the absence of a plan. It’s equivalent to having a plan to get rich. “I intend to get rich and famous” is a vague aspiration, not a plan.

To think about the future of energy, we can use the same matrix. The quadrants shake out like this:

Determinate, optimistic: one specific type of energy is best, and needs to be developed

Determinate, pessimistic: no technology or energy source is considerably better. You have what you have. So ration and conserve it.

Indeterminate, optimistic: there are better and cheaper energy sources. We just don’t know what they are. So do a whole portfolio of things.

Indeterminate, pessimistic: we don’t know what the right energy sources are, but they’re likely going to be worse and expensive. Take a portfolio approach.

In the indeterminate pessimism of Japan and Europe, you get a whole range of inferior options. People ride bikes. If they drive they drive tiny cars. Or maybe they take the train and have a long commute.

Gone are the days where Robert Moses could unilaterally re-architect the state of New York. We don’t do things on that scale anymore. Instead we think about the future indeterminately.

China falls in the bottom left quadrant of pessimistic determinism. The future is coal and oil. The plan is to buy up oil fields in Africa and domestically mine as much coal as possible. Something like 3,000 to 5,000 people die in coal mining accidents every year in China. They’re essentially fighting small war each year to get enough coal.

One argument against the indeterminate view is that the history of energy consumption in the U.S. has been very determinate. A single energy source has always tended to dominate. Up until the mid-19th century, that source was wood. One reason that America had such a higher standard of living than Britain is that we had more wood. People more or less ran out of trees to cut down in Britain and so they would get cold at night. Coal started to take off around the mid-19thcentury and dominated up through the early 20th century. Petroleum took over as the leading energy source in the 1930s and ‘40s. Natural gas has now emerged and overtaken coal as number two. Nuclear comes in at a very distant third.

t doesn’t make sense that the universe would be ordered such that many different kinds of energy sources are almost exactly equal. Solar is very different from wind, which is very different from nuclear. It would be extremely odd if pricing and effectiveness across all these varied sources turned out to be virtually identical. So there’s a decent ex ante reason why we should expect to see one dominant source.

The U.S. then was like Saudi Arabia today—a very big exporter. The Texas Railroad Commission effectively set the world oil price.

This cynical view is that it’s all a game of musical chairs game. In a determinate pessimistic world, who gets shot next?

Enumerating all the mistakes that were made in cleantech would be quite a project. But the most important were mistakes about the following:

markets

mimesis and competition

secrets

incrementalism

durability

teams

distribution

timing

financing

luck

To have a successful startup, you must have good answers—or at least a good plan for getting those answers—to all 10 of these points; 8 out of 10 is sort of a B-, and 5 of 10 earns you an F.

This explains the phenomenon of social entrepreneurship, which can be defined as doing well while doing good. The problem is that social entrepreneurs usually end up doing neither.

It has an incredible ambiguity to it. Is it actually good for society? Or is it simply approved of by society? Those are very different questions.

Secrets can allow you to escape mimesis and competition in a world of long time horizons, but those secrets need to be pretty big.

Savvy observers would have seen the trouble coming when cleantech people started wearing suits and ties. Tech people and computer people wear t-shirts and jeans. Cleantech people, by contrast, looked like salesmen. And indeed they were. This is not a trivial point.

Many startups run into problems because they discount the importance of distribution. But cleantech’s problems in this sphere were even sharper; companies literally couldn’t distribute the power they would generate.

No one asked whether Solyndra’s technology worked. But that is precisely the kind of substantive engineering question that you would ask in a determinate world. In an indeterminate world, though, people ask legal and financial questions. They focus on whether the proper processes were followed. And this is exactly what happened.

eBay is basically a recycling company. Amazon is getting rid of suburban sprawl. And Airbnb is curbing excess and unnecessary hotel construction costs.

Thorium is a big secret. When the government became very interested in nuclear technology in the 1940s, it found that you could get nuclear power from three chemical elements: plutonium, uranium, and thorium. The problem with Thorium was that it contains no fissile isotopes, which means you can’t weaponize it. And the government was interested in building bombs, not generating power. Eisenhower’s ‘53 Atoms for Peace speech was originally intended to warn of the perils of a thermonuclear age where everyone could be obliterated instantly. When that seemed too dark, it was retooled to talk about the promise of non-weaponized nuclear energy as well. Power generation was decidedly not the government’s focus during the intensive R&D of the 1940s. But there is a sense today that we really don’t need any more nuclear weapons. On that basis alone, thorium power seems worth revisiting.

Thorium seems promising for a couple of reasons:

Thorium is much more abundant than uranium. There is enough to power the world for a million years at current energy consumption levels.

Thorium is relatively clean. With uranium, you only end up using about 0.7% and there’s a lot of waste from the enrichment process. With thorium, by contrast, there’s much less waste because it’s a self-contained cycle.

You can build thorium reactors that don’t require hundreds of atmospheres of pressure like uranium reactors do.

You can’t get a runaway thorium reaction for the same reasons you can’t weaponize it.

Thorium is something like 1/10 as expensive as other forms of nuclear power. Thorium plants would cost about $250 million to build, whereas uranium plants cost $1.1 billion.

You can think of technology’s relationship with government as fitting one of three molds: being sold to the government, being subsidized by the government, or replacing the government.

Class 15: Back to the Future

There are no CS visions of the future that haven’t happened yet.

LightSail is developing a way to store energy more effectively. At one level, it’s basic Boyle’s law. You use power to compress air into steel tanks. Later, when you want power, you decompress the air to release it. The main challenge is that air becomes very hot when you compress it. That allows power to dissipate. The fix is to basically spray water into their air to cool it down. Naturally, there are myriad complicated details on how to actually get it to work, but it’s a simple idea on a high level.

Thinking long-term is good. But 25-50 years is really long-term; it’s just beyond the horizon where people are no longer accountable. So that prediction may be code for, “It will happen, but I don’t have to do anything. Someone else will do it.”

The Space Shuttle program was oddly Pareto inferior. It cost more, did less, and was more dangerous than a Saturn V rocket.

We have been launching rockets into space for more than half a century now. But the cost to launch 1kg of mass into orbit hadn’t changed very much in 40 years.

The retrofuture idea is simply this: think about where the past failed, learn the right lessons, and make it work this time. But it’s important to resist just being pulled in by the iconic future of old. There’s no sense in making the same mistakes over again.

Danielle Fong: It turns out that the idea of using air as a medium for energy storage has been around for very long time. It was very popular in the 1870s, some 10 years before the electrical grid. And during that “golden age of compressed air,” people actually tried improving efficiency by spraying water in air! They knew that water has a very high heat capacity. But the technology was completely abandoned. All we can dig up is that there were “problems.” We don’t know any more than that. It’s possible that they didn’t have right materials. Maybe they had corrosion problems. It’s really hard to debug the mental processes of long-dead inventors. But what’s really amazing is that if things were done in the right sequences—if they had gotten aerocompression right—the history of technology would have unfolded extremely differently. There is a powerful path dependency to the history of energy.

Very successful enterprise startups tend to have iterative sales models. They achieve a 50-100% growth rate year over year for several years. They might make $5M in the first year, and if things go really well, that will double every year for a decade.

You might wonder why the revenue doesn’t just 10x in the fourth year when everybody understands the product’s superiority. But it doesn’t work like that. It usually turns out that no customer is willing to do a deal that’s 10x the size of your largest deal to date. Maybe 2x your biggest deal is a more realistic hope.

So the strategy should be to get the smallest customer that is also a good reference customer. Move quickly and acquire good references.

Greg Smirin: Most sales models fail because people miscalculate the sales cycle. They underestimate just how long it takes to land the ideal clients. So a good recipe for success is to get the smallest, best customers you can, quickly. Jump the easy hurdles first. Then you’ll know more about how to deal with the larger enterprise customers.

It is very hard hard for investors to invest in things that are unique. The psychological struggle is hard to overstate.

Class 17: Deep Thought

On the surface, we tend to think of people as a very diverse set. People have a wide range of different abilities, interests, characteristics, and intelligence. Some people are good, while others are bad. It really varies. By contrast, we tend to view computers as being very alike. All computers are more or less the same black box. One way of thinking about the range of possible artificial intelligences is to reverse this standard framework. Arguably it should be the other way around; there is a much larger range of potential AI than there is a range of different people.

We tend to think of AI as being marginally smarter than an Einstein. But it is not a priori clear why the scale can’t actually go up much, much higher than that. The bias is toward conceiving of things that are fathomable. But why is that more realistic than a superhuman intelligence so smart that it’s hard to fathom? It might be easier for a mouse to understand the relativity than it is for us to actually understand how an AI supercomputer thinks.

There is a weird set of theological parallels you could map out. God may have been to the Middle Ages what AI will become to us. Will the AI be god? Will it be all-powerful? Will it love us? These seem like incomprehensible questions. But they may still be worth asking.

Recently the popular concern has shifted from intelligent computers to empathetic computers. People today seem more interested in whether computers can understand our feelings than whether they are actually smart. It doesn’t matter how intelligent it is in more classic domains; if the computer does not find human eye movement emotionally provocative, it is, like Vulcans, still somehow inferior to people.

There are two basic paradigms. The Luddite paradigm is that machines are bad, and you should destroy them before they destroy you. This looks something like textile workers destroying factory cotton mills, lest the machines take over the cotton processing. The Ricardo paradigm, by contrast, holds that technology is fundamentally good. This is economist David Ricardo’s gains from trade insight; while technology displaces people, it also frees them up to do more.

But this depends on the relative magnitudes of advantage. The above scenario plays out if the AI is marginally better. But things may be different if the AI is in fact dramatically better. What if it can do 3000x what humans can do across everything? Would it even make sense for the AI to trade with us at all? Humans, after all, don’t trade with monkeys or mice. So even though the Ricardo theory is sound economic intuition, in extreme cases there may be something to be said for the Luddite perspective.

We may end up creating a supercomputer in the cloud that calls itself Zeus and throws down lightning bolts at people.

When the audience voted, it was a sea of green. 100% agreed with that prediction. There wasn’t a single dissenter. Perhaps that should make us nervous. Unanimity in crowds can be very disconcerting. Maybe it’s worth questioning the biotech-as-info-science thesis a little bit more.

The single idea that people thought was the worst was that all cars would go electric. 92% of the audience voted against that happening. There are many reasons to be bearish on electric cars. But now there is one less.

AI, by contrast, is an unregulated frontier. You can launch just as quickly as you can build software. It might cost you $1 million, or millions. But it won’t cost $1 billion. You can work from your basement. If you try to synthesize Ebola or smallpox in your basement, you could get in all sorts of trouble. But if you just want to hack away at AI in your basement, that’s cool.

Palantir’s framework is not fundamentally about AI, but rather about intelligenceaugmentation.It falls very squarely within the Ricardo gains from trade paradigm. The key is to find the right balance between human and computer.

Scott Brown: If you’re building an airplane, you can’t succeed by making a thing that has feathers and poops. Rather, you look at principles of flight. You study wings, aerodynamics, lift, etc., and you build something that reflects those principles.

Class 18: Founder as Victim, Founder as God

PayPal’s founding team was six people. Four of them were born outside of the United States. Five of them were 23 or younger. Four of them built bombs when they were in high school. (Your lecturer was not among them.) Two of these bombmakers did so in communist countries: Max in the Soviet Union, Yu Pan in China. This was not what people normally did in those countries at that time.

Perhaps the founder distribution is, however strangely, an inverted normal distribution. Both tails are extremely fat. Perhaps founders are complex combinations of, e.g., extreme insiders and extreme outsiders at the same time.

This segues to the pure celebrity version, best epitomized by Lady Gaga. Born This Way is her recent hit album and song. On one level, the whole thing is obviously completely fictional. It’s probably safe to say that she was not, in fact, born like this. The big piece must be nurture. But on another level, maybe it isnature. What sort of people would actually do this to themselves? Maybe one actually does have to be born that way in order to do these things. Who really knows for sure?

The perfect scapegoat is someone at both extremes. He must be both an extreme outsider and an extreme insider. It can’t be a completely random person drawn from a homogeneous lot. It must be some sort of outsider, lest the people in the crowd get introspective and realize that the sacrificed was essentially just like them (and, next time, may well be them). But neither can the scapegoat be entirely different from the crowd; he must be an insider, since the pretext behind the ritual is that he is responsible for the internal community strife.

During the French Revolution, there was an interesting legal debate on whether the king should get a trial. Robespierre and the revolutionaries vehemently argued against a trial. The king, they should, should be slaughtered like a wild beast. Having a trial meant that the king might be innocent, which, in turn, meant that the people might be guilty. But it was unthinkable that the people might be guilty. So the solution was to just kill the king.

The “from destructive to immortalized” dynamic goes way back to mythology. Alexander the Great was 32 when he died. He would frequently engage in hardcore quasi-religious drinking marathons. Apparently the game was to consume alcohol until someone died, and Alexander felt that he had to prove that that someone would not be him. It was a strategic error. But he will forever be known as a great conqueror.

Abraham Lincoln was an extreme outsider turned insider. He was born in an isolated log cabin. He was probably our poorest President. He was very smart and also very ugly. And he, probably intentionally, uglified himself even further with his strange beard. Lincoln was always on both extremes.

One (admittedly unconventional) theory is that Bill Gates is still being tortured and punished for his fall. He has to go to all sorts of boring charity events, pretend that the people there are saying interesting things, and then give them his money to boot. And adding insult to injury is the fact that these are the same people who ganged up on him in the late ‘90s.

One of Hughes’ favorite tricks was to pretend to be crazy on the theory that no one would take the time and energy to try to stop or compete with a crazy person. A large part of his mythology was fictionally constructed; he claimed, for instance, to have been born on December 25th, 1905. One has to wonder if he was really born on the same day of the year as Christ, or whether that was an intentional ploy.

How much of this can be avoided? How do you avoid becoming a sacrificial victim? The simple answer, of course, is that if you really don’t want to get killed, you shouldn’t sit on the throne. But this seems suboptimal. Wearing the crown is obviously an attractive thing. The question is whether you can decouple it with getting executed.

Bill Gates was incredible through the 1990s, until Larry Ellison and Scott McNealy and a bunch of CEOs from other tech companies effectively started a “We Hate Gates” club, stirred up attention at the DOJ, etc. From Gates’ perspective, he was on perpetual winning arc of never-ending progress. Everything was perfect, and the haters were just envious and pathetic.

We are biased toward the democratic/republican side of the spectrum. That’s what we’re used to from civics classes. But the truth is that startups and founders lean toward the dictatorial side because that structure works better for startups. It is more tyrant than mob because it should be.

If you want to be a founder and stay a founder, can you extend the founding period? In tech companies, foundings last as long as technological innovation continues. The question is thus how long it takes for the substantive technology focus to yield to process. Once you shift toward ossified, process-based normality, much less gets done. Every founder would thus to do well to never stop wondering whether there are strategies to extend the founding in one form or another.

Even something as seemingly innocuous as holding the title of CEO may actually be quite dangerous. Maybe you can figure out ways to minimize it. Augustus never said he was king. It was dangerous to be a king after Brutus killed Caesar.  So Augustus was just the “first among equals.” Whether that equality was anything more than pure fiction, of course, is very questionable.

But the really decisive difference between one founder and more is that with multiple founders, it’s much harder to isolate a scapegoat. Is it Larry Page? Or is it Sergey Brin? It is very hard for a mob-like board to unite against multiple people—and remember, the scapegoat must be singular. The more singular and isolated the founder, the more dangerous the scapegoating phenomenon. For the skeptic who is inclined to spot fiction masquerading as truth, this raises some interesting questions. Are Page and Brin, for instance, really as equal as advertised? Or was it a strategy for safety? We’ll leave those questions unanswered and hardly asked.

Class 19: Stagnation or Singularity?

Aubrey de Grey: We should be sympathetic toward giving very difficult approaches the time of day.

Aubrey de Grey: It doesn’t only matter that these technologies are developed. When they are developed is hugely important as well. Take anti-aging science, for instance. Very close to 150,000 people die everyday. About 100,000 of these daily deaths are aging-related. (Probably about 90% of deaths in Western countries are aging-related). So each day that you don’t delay saves 100,000 lives.

Michael Vassar: People used to predict the future in a pretty determinate way. Suppose you’re looking for oil. That involves making fairly concrete predictions: there is x amount of oil at y place, and it will last z number of years. People have largely stopped doing that.

Michael Vassar: Science matters much more than engineering does. But it’s easier to talk about engineering. So one should use engineering to discard the 99.9% of people who have no clue what’s going on. But then one should get into the science with the remnant. That is where the upside will come from.

This course has largely been about going from 0 to 1. We’ve talked a lot about how to create new technology, and how radically better technology may build toward singularity. But we can apply the 0 to 1 framework more broadly than that. There is something importantly singular about each new thing in the world. There is a mini singularity whenever you start a company or make a key life decision. In a very real sense, the life of every person is a singularity.

The obvious question is what you should do with your singularity. The obvious answer, unfortunately, has been to follow the well-trodden path. You are constantly encouraged to play it safe and be conventional. The future, we are told, is just probabilities and statistics. You are a statistic.

But the obvious answer is wrong. That is selling yourself short. Statistical processes, the law of large numbers, and globalization—these things are timeless, probabilistic, and maybe random. But, like technology, your life is a story of one-time events.

By their nature, singular events are hard to teach or generalize about. But the big secret is that there are many secrets left to uncover. There are still many large white spaces on the map of human knowledge. You can go discover them. So do it. Get out there and fill in the blank spaces. Every single moment is a possibility to go to these new places and explore them.

There is perhaps no specific time that is necessarily right to start your company or start your life. But some times and some moments seem more auspicious than others. Now is such a moment. If we don’t take charge and usher in the future—if you don’t take charge of your life—there is the sense that no one else will.

So go find a frontier and go for it. Choose to do something important and different. Don’t be deterred by notions of luck, impossibility, or futility. Use your power to shape your own life and go and do new things.