The Exchanges

Q I'd say like Peter Thiel and you both got like boring jobs and then like realized that you had to leave and go do something better. Some of us kind of went more straight to the entrepreneurial journey after school. What, what, what is it about your personality that caused you to do the two years of boring stuff and then go do something cool? Like what, what happened there?

A Joe, the funny thing is those two years cost me dearly because the reality is when I was leaving, when I was leaving, uh, Harvard, I was actually very close to joining Facebook then, which would have been truly at zero. I was in Kirkland house when Mark launched it. Uh, and I was a huge fan of it. I actually had been pretty close to six degrees, which was one of the proto social networks that actually wrote the friending patents back in the day. So I was around it. I thought it was a huge deal, but honestly, Joe, here's the reality. I was still in the gold star game. I liked Being told I was good at things. And I thought that the, I thought that people knew things. Um, and so it was, you know, I kind of graduated Phi Beta Kappa from Harvard. I wanted, I actually got good grades in college. Then I left and I wanted other people to tell me I was still good at things. And Bain told me I was good at things. And so it took me an extra two years to figure out the emperor had no clothes and that honestly you could just do stuff. Uh, at which point kind of the journey began.

AI assessment note: “I was still in the gold star game. I liked Being told I was good”

Q Or it's Nate in our chat if I post something too far right, but that's, that's totally fair. Let's talk about your fund. You co-founded Slow Ventures. It's one of the top angel funds in Silicon Valley. Tell us about your focus and some of your core themes. What are you, what are you focused on?

A Yeah, it's interesting, Joe. So look, you know, all throughout, even my early years, you know, when I was at Bain and then after, you know, I was pretty involved as like an angel investor personally, right? So I, you know, I was the first investor in Venmo. I, you know, helped seed MakerBot. Like we've kind of built a whole New York ecosystem when that was a backwater, you know, of kind of early stage, just getting cool people together and finding cool ideas. When I left Facebook, Kevin Collar and I, along with Dave Moore, and he's a good friend to do a podcast with him. We're like, let's just like Like formalize a real seed fund. And so, you know, we've raised now we're on our fifth fund, um, kind of towards the end of our fifth, about to start our sixth fund of our core fund. We have an opportunity fund. We've kind of built this crazy creator fund, but our whole thing has just been like in the end of the day, you know, where can we put money that's non-obvious, right? Um, where there's real leverage, where we're betting on people and ideas that I'd call are like out of the money. Like I think seed investing is basically buying out of the money call options. Right. And so in the end of the day, and like the good news about that, Is that when it works, it really works. Like, you know, I, I was the, you know, I was like, I think the third investor ever and like really did help s…

AI assessment note: “where can we put money that's non-obvious, right? Um, where there's real leverage”

Q based on merit, over 20% Jewish. It's very clear that along with this other kind of anti-Semitic stuff that was like not okay for the people running it, and they, and they've pushed that down to, I think, under five percent now. Like, like, is that going to keep going? Are they going to go back to merit and just see what happens? Like, like, it just seems bad, right?

A Here's what I'd say. The merit, this is the thing I think you and I probably most vehemently agree upon, which is we have to optimize for merit, right? That is it. Right, and like we can talk about what kind of where you take that and where you go, and that is the only possible true north. Now, the complicated places come when people talk about antisemitism at Harvard. It gets really complicated really fast, so I'll give you, I'll give you some, just some data points. One is, yes, the Jewish population has declined at Harvard a lot, and people question why. One answer, which is true, it's actually not the Jewish population, it's the white population. Right? So is it really anti-Semitism or is it actually the Jews are just a scalar on effectively the white population has come down? There's another thing in play is everyone looks at the numbers and say, well, guess what? It's definitely anti-Semitism because how could it possibly not be from a merit perspective? Well, here's the thing. There's a strong argument. I say this as a proud Jewish person that here's the thing. Jews in America have gotten pretty successful. We're now a few generations in. In a lot of ways, the Asians are the new Jews. That could be true, that the Jews are getting out-competed.

AI assessment note: “it's actually not the Jewish population, it's the white population.”

Q How'd that process work? You actually hired a new associate. What kind of tests did you create?

A Yeah, we, we basically, I did, I mean, you gotta dog food your own stuff to learn, right? So I worked with some friends. We built a V one, literally end to end. We built a test around it instead of just hiring, you know, calling my friends at Goldman and saying, who are the four kids that are interested in venture capital, right? Which is what we've done historically. I posted it on the internet. We got like 1500 people to fill out this test, right? And then we kind of talked to the best people. And hire someone, right? And like that, and it was from a place we wouldn't have hired from historically. And so I think that's like, you're like, this does work. And this does feel like the way the world should go and will go. But in the end of the day, like, you still need to build this stuff, right? That's like, kind of, I think, where the company comes from, and what you and I are teaming up on.

AI assessment note: “We built a test around it... I posted it on the internet.”

Q in America today, I think it's more about agency and culture. And, and then intelligence. Now, now I want, I want to ask about these tests. Like what should the best talent assessments measure? Because obviously there's like IQ is a very big part of this. Uh, but then there's other things as well. And like, like, like, how do you think about that? What are the vectors you're measuring?

A You know, it's a good question, Joe. And I think it's different for every role and opportunity. Like not all things are the same. So I think it's a really, a little bit hard to think about this fully in the abstract versus saying, I mean, in an ideal world, you think about it in an ideal world, which I don't think is that far off. You as a hiring manager, someone has an opportunity. You might not even be able to articulate what you should be testing for. Instead, you might say, hey, who are the 10 best people at my company? Right? Like, let's just run AI with them and emergently figure out what the right questions are to ask, right? Because you might actually not know, right? Or even need to know. So I think there's like, there's a whole bunch of stuff that's going on that is kind of the future of this stuff. But there, I think the reality is, is that for Most normal roles or most people you want to work with, it's, it's the same stuff that matters, right? Yeah, you, you, in most jobs, not all, but a lot of jobs, like, you know, how your IQ matters to a point. If it doesn't, then maybe not, but in a lot of jobs, it does, especially in an AI, like grit. I've always cared most about gritty people, right? That are just going to run through walls because I, in my experience, even very intellectual jobs, and there's some balance to this, um, Nothing's that hard, right? There's a spe…

AI assessment note: “how your IQ matters to a point... like grit. I've always cared most about gritty people”

Q Were they bigger if they were too hot? Was that what would happen?

A They would glom together and you'd have these like super M&Ms, right? And they were like at this loss rate problem. It was the whole thing. It was actually a fun adventure in business history, but you, you know, you kind of have this like very narrow view of what metrics are and, and you start fighting them. You're like, well, we, we can't look at this stuff. We need to think big, but then you start realizing that in some ways the beauty of, I mean, the beauty of capitalism, right, is the metric is profit, right? And that, if you look at how the best For profits operate versus nonprofits with exposure to both. There is incredible beauty in being like, make money, right? And that's how you do it. It's interchangeable. It's freeing. It allows you to do great stuff. Whereas in nonprofits, you have this constant problem where you have like a triple bottom line. You have four goals. They compete with each other. How do you optimize around that? It becomes kind of a management mess, right? And so really thinking strategically, I think Facebook, the story of You got to measure the right stuff. You measure, you're going to get whatever you measure. So you better have the right numbers and have the right instrumentation. But then thinking really strategically about, you know, where that's actually quite freeing versus constraining, I think is one of the most interesting problems in busi…

AI assessment note: “They would glom together and you'd have these like super M&Ms”