**Want to start a startup?** Get funded by [Y
Combinator](http://ycombinator.com/apply.html).  
  
  
September 2012  
  
I've done several types of work over the years but I don't know another as
counterintuitive as startup investing.  
  
The two most important things to understand about startup investing, as a
business, are (1) that effectively all the returns are concentrated in a few
big winners, and (2) that the best ideas look initially like bad ideas.  
  
The first rule I knew intellectually, but didn't really grasp till it happened
to us. The total value of the companies we've funded is around 10 billion,
give or take a few. But just two companies, Dropbox and Airbnb, account for
about three quarters of it.  
  
In startups, the big winners are big to a degree that violates our
expectations about variation. I don't know whether these expectations are
innate or learned, but whatever the cause, we are just not prepared for the
1000x variation in outcomes that one finds in startup investing.  
  
That yields all sorts of strange consequences. For example, in purely
financial terms, there is probably at most one company in each YC batch that
will have a significant effect on our returns, and the rest are just a cost of
doing business. [1] I haven't really assimilated that fact, partly because
it's so counterintuitive, and partly because we're not doing this just for
financial reasons; YC would be a pretty lonely place if we only had one
company per batch. And yet it's true.  
  
To succeed in a domain that violates your intuitions, you need to be able to
turn them off the way a pilot does when flying through clouds. [2] You need to
do what you know intellectually to be right, even though it feels wrong.  
  
It's a constant battle for us. It's hard to make ourselves take enough risks.
When you interview a startup and think "they seem likely to succeed," it's
hard not to fund them. And yet, financially at least, there is only one kind
of success: they're either going to be one of the really big winners or not,
and if not it doesn't matter whether you fund them, because even if they
succeed the effect on your returns will be insignificant. In the same day of
interviews you might meet some smart 19 year olds who aren't even sure what
they want to work on. Their chances of succeeding seem small. But again, it's
not their chances of succeeding that matter but their chances of succeeding
really big. The probability that any group will succeed really big is
microscopically small, but the probability that those 19 year olds will might
be higher than that of the other, safer group.  
  
The probability that a startup will make it big is not simply a constant
fraction of the probability that they will succeed at all. If it were, you
could fund everyone who seemed likely to succeed at all, and you'd get that
fraction of big hits. Unfortunately picking winners is harder than that. You
have to ignore the elephant in front of you, the likelihood they'll succeed,
and focus instead on the separate and almost invisibly intangible question of
whether they'll succeed really big.  
  
**Harder**  
  
That's made harder by the fact that the best startup ideas seem at first like
bad ideas. I've written about this before: if a good idea were obviously good,
someone else would already have done it. So the most successful founders tend
to work on ideas that few beside them realize are good. Which is not that far
from a description of insanity, till you reach the point where you see
results.  
  
The first time Peter Thiel spoke at YC he drew a Venn diagram that illustrates
the situation perfectly. He drew two intersecting circles, one labelled "seems
like a bad idea" and the other "is a good idea." The intersection is the sweet
spot for startups.  
  
This concept is a simple one and yet seeing it as a Venn diagram is
illuminating. It reminds you that there is an intersection—that there are good
ideas that seem bad. It also reminds you that the vast majority of ideas that
seem bad are bad.  
  
The fact that the best ideas seem like bad ideas makes it even harder to
recognize the big winners. It means the probability of a startup making it
really big is not merely not a constant fraction of the probability that it
will succeed, but that the startups with a high probability of the former will
seem to have a disproportionately low probability of the latter.  
  
History tends to get rewritten by big successes, so that in retrospect it
seems obvious they were going to make it big. For that reason one of my most
valuable memories is how lame Facebook sounded to me when I first heard about
it. A site for college students to waste time? It seemed the perfect bad idea:
a site (1) for a niche market (2) with no money (3) to do something that
didn't matter.  
  
One could have described Microsoft and Apple in exactly the same terms. [3]  
  
**Harder Still**  
  
Wait, it gets worse. You not only have to solve this hard problem, but you
have to do it with no indication of whether you're succeeding. When you pick a
big winner, you won't know it for two years.  
  
Meanwhile, the one thing you _can_ measure is dangerously misleading. The one
thing we can track precisely is how well the startups in each batch do at
fundraising after Demo Day. But we know that's the wrong metric. There's no
correlation between the percentage of startups that raise money and the metric
that does matter financially, whether that batch of startups contains a big
winner or not.  
  
Except an inverse one. That's the scary thing: fundraising is not merely a
useless metric, but positively misleading. We're in a business where we need
to pick unpromising-looking outliers, and the huge scale of the successes
means we can afford to spread our net very widely. The big winners could
generate 10,000x returns. That means for each big winner we could pick a
thousand companies that returned nothing and still end up 10x ahead.  
  
If we ever got to the point where 100% of the startups we funded were able to
raise money after Demo Day, it would almost certainly mean we were being too
conservative. [4]  
  
It takes a conscious effort not to do that too. After 15 cycles of preparing
startups for investors and then watching how they do, I can now look at a
group we're interviewing through Demo Day investors' eyes. But those are the
wrong eyes to look through!  
  
We can afford to take at least 10x as much risk as Demo Day investors. And
since risk is usually proportionate to reward, if you can afford to take more
risk you should. What would it mean to take 10x more risk than Demo Day
investors? We'd have to be willing to fund 10x more startups than they would.
Which means that even if we're generous to ourselves and assume that YC can on
average triple a startup's expected value, we'd be taking the right amount of
risk if only 30% of the startups were able to raise significant funding after
Demo Day.  
  
I don't know what fraction of them currently raise more after Demo Day. I
deliberately avoid calculating that number, because if you start measuring
something you start optimizing it, and I know it's the wrong thing to
optimize. [5] But the percentage is certainly way over 30%. And frankly the
thought of a 30% success rate at fundraising makes my stomach clench. A Demo
Day where only 30% of the startups were fundable would be a shambles. Everyone
would agree that YC had jumped the shark. We ourselves would feel that YC had
jumped the shark. And yet we'd all be wrong.  
  
For better or worse that's never going to be more than a thought experiment.
We could never stand it. How about that for counterintuitive? I can lay out
what I know to be the right thing to do, and still not do it. I can make up
all sorts of plausible justifications. It would hurt YC's brand (at least
among the innumerate) if we invested in huge numbers of risky startups that
flamed out. It might dilute the value of the alumni network. Perhaps most
convincingly, it would be demoralizing for us to be up to our chins in failure
all the time. But I know the real reason we're so conservative is that we just
haven't assimilated the fact of 1000x variation in returns.  
  
We'll probably never be able to bring ourselves to take risks proportionate to
the returns in this business. The best we can hope for is that when we
interview a group and find ourselves thinking "they seem like good founders,
but what are investors going to think of this crazy idea?" we'll continue to
be able to say "who cares what investors think?" That's what we thought about
Airbnb, and if we want to fund more Airbnbs we have to stay good at thinking
it.  
  
  
  
  
  
**Notes**  
  
[1] I'm not saying that the big winners are all that matters, just that
they're all that matters financially for investors. Since we're not doing YC
mainly for financial reasons, the big winners aren't all that matters to us.
We're delighted to have funded Reddit, for example. Even though we made
comparatively little from it, Reddit has had a big effect on the world, and it
introduced us to Steve Huffman and Alexis Ohanian, both of whom have become
good friends.  
  
Nor do we push founders to try to become one of the big winners if they don't
want to. We didn't "swing for the fences" in our own startup (Viaweb, which
was acquired for $50 million), and it would feel pretty bogus to press
founders to do something we didn't do. Our rule is that it's up to the
founders. Some want to take over the world, and some just want that first few
million. But we invest in so many companies that we don't have to sweat any
one outcome. In fact, we don't have to sweat whether startups have exits at
all. The biggest exits are the only ones that matter financially, and those
are guaranteed in the sense that if a company becomes big enough, a market for
its shares will inevitably arise. Since the remaining outcomes don't have a
significant effect on returns, it's cool with us if the founders want to sell
early for a small amount, or grow slowly and never sell (i.e. become a so-
called lifestyle business), or even shut the company down. We're sometimes
disappointed when a startup we had high hopes for doesn't do well, but this
disappointment is mostly the ordinary variety that anyone feels when that
happens.  
  
[2] Without visual cues (e.g. the horizon) you can't distinguish between
gravity and acceleration. Which means if you're flying through clouds you
can't tell what the attitude of the aircraft is. You could feel like you're
flying straight and level while in fact you're descending in a spiral. The
solution is to ignore what your body is telling you and listen only to your
instruments. But it turns out to be very hard to ignore what your body is
telling you. Every pilot knows about this
[problem](http://en.wikipedia.org/wiki/Spatial_disorientation) and yet it is
still a leading cause of accidents.  
  
[3] Not all big hits follow this pattern though. The reason Google seemed a
bad idea was that there were already lots of search engines and there didn't
seem to be room for another.  
  
[4] A startup's success at fundraising is a function of two things: what
they're selling and how good they are at selling it. And while we can teach
startups a lot about how to appeal to investors, even the most convincing
pitch can't sell an idea that investors don't like. I was genuinely worried
that Airbnb, for example, would not be able to raise money after Demo Day. I
couldn't convince [Fred Wilson](airbnb.html) to fund them. They might not have
raised money at all but for the coincidence that Greg McAdoo, our contact at
Sequoia, was one of a handful of VCs who understood the vacation rental
business, having spent much of the previous two years investigating it.  
  
[5] I calculated it once for the last batch before a consortium of investors
started offering investment automatically to every startup we funded, summer
2010. At the time it was 94% (33 of 35 companies that tried to raise money
succeeded, and one didn't try because they were already profitable).
Presumably it's lower now because of that investment; in the old days it was
raise after Demo Day or die.  
  
**Thanks** to Sam Altman, Paul Buchheit, Patrick Collison, Jessica Livingston,
Geoff Ralston, and Harj Taggar for reading drafts of this.  
  

