How I Invest with David Weisburd
00:00:00 · David Weisburd, Jerry Ye
[00:00:00] S0: This Anthropic signal before Anthropic became Anthropic today. What exactly were you seeing in the data? [00:00:05] S1: Anthropic was hiring people with more... In terms of, like, pedigree types signals, like better schools, better experience, and on average, that actually had them surpassing OpenAI. [00:00:17] S0: A lot of venture capitalists have been trying to quantify which founders are gonna be most successful at the very early stage. What do we know today about what kind of founders succeed? [00:00:26] S1: This really depends on the sector. I remember, like, an early study that showed PhDs in enterprise tended to have better outcomes. Right? So domain experience, if you're particularly niche for your sector, requires that domain expertise. But that doesn't really matter at all for consumer companies, right, where you might have a very strong pedigree, founder, and team, but you don't have traction. Right? And and traction in that case is actually super important. [00:00:49] S0: Let's say that you're advising a CEO of one of the top multistage venture capital firms, one of these top 15 firms. And the CEO was bought in of the firm, and they wanted to institute data in the deepest level within their firm on every part of the stack. How would you advise them to execute on that strategy? [00:01:08] S1: You need KPIs. Like, what a true north star is. And it has objective that's in a way that's grounded by data.
00:01:08 · Jerry Ye, David Weisburd
[00:01:08] S1: You need KPIs. Like, what a true north star is. And it has objective that's in a way that's grounded by data. [00:01:14] S0: One of the interesting factors that we see in the startup ecosystem today is these tranche rounds. Sequoia will come in at a billion dollar valuation, and then startups will raise another round at $2,000,000,000 almost a couple weeks later. What do you think about these tranche rounds? [00:01:30] S1: It's pretty interesting. [00:01:35] S0: Jerry, you've spent most of your career trying to make venture capital quantifiable. What have you learned?
00:01:35 · David Weisburd, Jerry Ye
[00:01:35] S0: Jerry, you've spent most of your career trying to make venture capital quantifiable. What have you learned? [00:01:40] S1: Early in in my career, we spent a lot of time looking at the talent ecosystem. So trying to understand where the most interesting founders were coming from, right, and who they were able to attract in terms of talent. So starting off there, I was just mostly looking at it from a who perspective. And later on in the career, I spent a lot more time in terms of trying to understand traction data, mostly focused on consumer prosumer type companies. And there, it's mostly trying to understand product market fit from the outside in. So buying alternative data, credit card data, whatever panels that was actually pretty familiar to the hedge fund side, but net new to the venture side. Right? And that gave us a lens into what was essentially trending and what was seeing inflection, was seeing high retention from the outside in before we even reached out to the companies. And then the more recent part was kinda like, you know, bringing in all these other signals that other firms were working on in terms of, like, quantifying growth. Like, Social Capital did a bunch of work there and being able to do that on data room, and once the company was actually in front of us, to make better decisions or get faster to time the decision.
00:01:40 · Jerry Ye, David Weisburd
[00:01:40] S1: Early in in my career, we spent a lot of time looking at the talent ecosystem. So trying to understand where the most interesting founders were coming from, right, and who they were able to attract in terms of talent. So starting off there, I was just mostly looking at it from a who perspective. And later on in the career, I spent a lot more time in terms of trying to understand traction data, mostly focused on consumer prosumer type companies. And there, it's mostly trying to understand product market fit from the outside in. So buying alternative data, credit card data, whatever panels that was actually pretty familiar to the hedge fund side, but net new to the venture side. Right? And that gave us a lens into what was essentially trending and what was seeing inflection, was seeing high retention from the outside in before we even reached out to the companies. And then the more recent part was kinda like, you know, bringing in all these other signals that other firms were working on in terms of, like, quantifying growth. Like, Social Capital did a bunch of work there and being able to do that on data room, and once the company was actually in front of us, to make better decisions or get faster to time the decision. [00:02:55] S0: Let's start with talent. A lot of venture capitalists have been trying to quantify which founders are gonna be most successful at the very early stage, which is where you focused on. What do we know today about what kind of founders succeed?
00:02:55 · David Weisburd, Jerry Ye
[00:02:55] S0: Let's start with talent. A lot of venture capitalists have been trying to quantify which founders are gonna be most successful at the very early stage, which is where you focused on. What do we know today about what kind of founders succeed? [00:03:10] S1: This really depends on the sector. Right? And I I remember like an early study that showed PhDs in enterprise tended to have better outcomes. Right? So domain experience, if your particular niche or your sector requires that domain expertise. [00:03:28] S0: Something like a very hard and technical problem.
00:03:28 · David Weisburd, Jerry Ye
[00:03:28] S0: Something like a very hard and technical problem. [00:03:30] S1: Yeah. And this is the reason why, if you look at NeurIPS, right, I think from fifteen years ago, was it was like a small niche, little academic research conference for 200, 300 people. Now it's talking about 20, 30,000 people. Right? And VCs are constantly there on the conference floor trying to source and identify the next deal. But that doesn't really matter at all for consumer companies. Right? Where you might have a very strong pedigree, founder and team, but you don't have traction. Right? And traction in that case is actually super important. So it really depends. Right? And and it's not just the founders, it's also who you're able to attract after you start the company. So your your founding team, the people you're able to pull away from the max seven. Right? How you're getting these additive people, because one way that I like looking at it is similar to a venture round. Right? Each engineer or each product person you're adding that could have made an extra 100 k, 200 k per year at a max seven could be seen as like a mini round. Right? And in aggregate, that's actually a very strong signal in terms of conviction or product mark... Or, I mean, in terms of conviction for the company. [00:04:44] S0: Said another way, they could have gotten a higher salary at a max seven firm. Instead, they're foregoing that salary for stock. So they're betting with their own career and with their own time into that startup. And that... That's a very strong signal.