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Why I Invest in People, Still
“Pattern matching” gets a bad rap –– sometimes deservedly. But to some extent, in early-stage investing, it’s the only way.
First, let’s get out of the way all of the reasons we’re told investing in people is a bad idea. And to be sure, there are reasons!
Let’s begin by talking about pattern matching. Quartz defines it this way: it’s “what it sounds like: If you’re a venture capitalist, find out which human traits, corporate makeups, and financial projections have proven most successful in tech, then go find founders and companies that replicate them.”
The problem with this? It can lead to bias, including racial and gender bias. If Bill Gates and Mark Zuckerberg are the only patterns you start from and match against, and if you define “pattern” too narrowly, you could end up only investing in white men –– which would be both wrong, and stupid. Such lazy pattern matching took a drubbing in the press recently when many journalists decided it was one reason major investors did so little to thoroughly vet Sam Bankman-Fried of FTX.
Says Bloomberg:
“Sam Bankman-Fried fit the pattern. The 30-year-old founder of the cryptocurrency exchange FTX was educated at the Massachusetts Institute of Technology, speaks plainly, convincingly and confidently and is charmingly quirky. His mop of hair gives off Albert Einstein vibes, and his loose-fitting T-shirts and shorts make Mark Zuckerberg seem overdressed.”
So yes, if misused or overused or used as an excuse for laziness when what is needed is due diligence, pattern matching is a bad idea. It can lead to a less just world. It can lead to hucksters getting money they don’t deserve.
But in early-stage investing of the sort I did, it’s still valuable. In fact, it’s still the main tool I relied upon. And here’s why.
I used “pattern matching” and the phrase “investing in people” roughly synonymously in this piece. The reason for this is that in a Web3 world, often there is no product to invest in yet. I was an early-stage investor. I might have become a late-stage investor, but I decided that wasn’t where my passion lay. I was passionate about visions of the future, in glimmers in the eye. I was excited by long shots, big bets, and leaps of faith.
And let me get this out of the way: obviously –– obviously –– the great majority of investments I made returned no money at all. 90% or more of the bets I made did not pan out. Such is the nature of power law distribution. This is one of the core principles of venture capital, whereby a small number of investments in a venture capital portfolio will generate the vast majority of returns.
But this is not the same as saying that my bets were not rational, or that my overall strategy was not rational. Early-stage investing is mathematically sane, even if the statement “90% of the bets I make will not pan out” may sound insane on the face of it. But the goal is to make a certain number of bets, all but one or two or three of which will fail –– but for those one or two or three to succeed so spectacularly that the money lost on the other bets simply doesn’t matter. We were in this for the long haul. We were hunting big game.
Peter Thiel calls this power-law returns, and it’s the philosophy that led him to make a half-million-dollar investment that returned him a billion dollars on that investment. It’s the logic that led YCombinator to invest in 3,000 companies (!) over 20 years, even if the bulk of these didn’t win. The ones that have won, have won big. Heard of Airbnb? DoorDash? Stripe?
This is the game we were playing, and we must not forget it.
So what exactly do you invest in, when you are investing in a glimmer in someone’s eye?
There is relatively little due diligence, in the traditional sense, that you can do. Yes, there are some numbers you can run. You can look at the TAM (total addressable market) that the founder is chasing. You want that number to be high, of course. What’s the point of making a risky bet if the pot of gold at the end of the rainbow isn’t huge?
Beyond that, though, you are investing in the person.
And when it comes down to that, one way or another, I was looking for certain patterns. I was consulting my gut instinct, after scanning for certain attributes and characteristics of a founder that I felt made them more likely to succeed than others.
Broadly, there are three patterns I looked for when investing in a founder.
Are they crypto-native?
This is something I could sense very rapidly; it’s like being a native speaker who can pick up an accent right away. I was looking for people whose “crypto accent” was not there at all, or was barely noticeable. These needed to be people who were so bought into the Web3 future that their whole worldview had shifted.
Is this product they are pitching me truly Web3, or does it merely have some blockchain language slapped on top? I could smell the difference at this point. I could intuit their tacit understanding of the Web3 space, because I’d been in crypto for nearly 10 years. I saw how they thought, how they ideated on product, how they imagined the future, how they thought about tokenomics structure and incentive models, how they thought about a product's relative position in a Web3 tech stack. All these things were signals to me on how “crypto-native” a person was, how fundamentally they were bought into the movement of Web3.
Are they product people?
I mentioned in an earlier post how Reid Hoffman sized me up: “You smell like a product person.” I never forgot that, and I learned to pick up the scent myself.
What exactly do I mean by a product person? It’s not that they need to be slinging code per se (though great if they do). It’s something squishier than that: it’s the question of whether they have an ability to discover product when you have nothing. One of my former investors, Mike Maples, once said to me, “A startup is an experiment to see if a business should exist.” Fundamentally, then, I was looking for an experimenter. I was looking for someone –– either in their responses to my initial questions, or in iterations over time –– who was a good experimenter: someone who understood data, evaluated, and iterated quickly in an attempt to achieve product-market fit.
I wanted to see, to feel out, how a person responded to the fundamental experimental feedback loop that is generating a thing that people want to use.
This is one reason why I rarely wanted to see someone’s pitch deck (for starters, at least). If you focus on that, you’re simply getting someone reading from a script. I wanted to see someone think on their feet; I wanted to riff with them, feel out how open they were to getting feedback and capturing data. Ultimately, did this person treat me as a collaborator? Because I was going to be, fundamentally, their business partner if I invested.
Being an early-stage investor in a person and product is a ten-year journey. Did we want to get married for 10 years? Or were we at risk of sinking a bunch of money on a wedding for a relationship that might blow up in six months?
What’s their track record?
And it didn’t have to be a track record of pure monetary success. Other metrics would do. I wanted to see a person’s grit, their competitiveness. If they acquitted themselves honorably in a battle, even if it was lost, that’s someone I was interested in. That’s someone who lived to fight another day, someone who had promise.
This desire for a track record was one reason I actually cultivated relationships over a long time, often, before committing to an investment. (I found them anywhere and everywhere, most often via other founders.) I think of this as “just dating,” whereas the investment is a proper marriage. Perhaps a founder pitched me an idea, but it was missing a few core pieces. I’d communicate that, and then in a few months or a year, I wanted to see how their idea had matured. Sometimes I’d invest purely on this growth that I’d seen, on this ability to iterate on an idea over a span of a few months.
Recently someone pitched me on something, and it just felt too Web 2.0 for my interest. I said to him, in so many words, “Let me pontificate a bunch of shit on you about Web3 and how it’s different.” To his credit, he listened, and went away, and came back three months later. Not only did he grok my pontification –– he took it ten steps further. I wanted to be in business with fast learners like these.
That’s a time span of a few months; but sometimes these flirtations lasted a decade, then moved very fast. Recently a different founder sent me a pitch deck. I’ve described my aversion to pitch decks, but this was someone I had known a bit for many years. The pitch deck felt to me like someone had thrown 10 strands of spaghetti against the wall. But wouldn’t you know, three of those strands stuck! I thought to myself, “Three of these ideas are pretty good.” I also knew this person to be a veteran founder who had done impressive things in e-commerce, having steered one company to a valuation of near a billion dollars. Mere ideas, but good ones, from someone with such a track record? That’s a deal I wanted to be in on. I committed a chunk of angel investment over email almost immediately (pending basic due diligence).
So it’s true. Investing in people can get a bad rap. And “pattern matching” has been much maligned, sometimes fairly so.
But when you are betting on visions of the future, sometimes it’s the best and only tool you have. You need to trust your gut. You need to feel out people when there is simply no product yet to invest in, quite. It’s quite simply the name in the game, and it’s why I believe in investing in people, still.