How I Invest with David Weisburd
00:03:53 · David Weisburd
[00:03:53] S1: Yeah. This first mover advantage, I've thought a lot about it in technology because very few of the companies were first movers. Google, I believe, was the eleventh search engine. Facebook was maybe even further along in the twelfth or thirteenth search engine. But yet, this first mover advantage persists. And I think the reason for that is, first of all, the first mover advantage is quite persistent in other asset classes. So outside of venture capital, the first mover advantage tends to tends to hold much more strongly. And secondly, of course, people invest for two reasons, fear and greed. And I think fear more than greed. And people just get afraid of losing that that number one player. And even if they passed on OpenAI for one round and two round, three round, some some people... At some point, those investors capitulate, and they they wanna go and go into these momentum investments.
00:04:48 · Gavin Ezekowitz
[00:04:48] S0: I think that's that's true. I think I don't know that it's different in in AI, but one of the observations that I would make is that it is very evident from the early days of the the AI phenomenon that this was there there was gonna be multiple disruptive events, whether you can recall even recently the deep sea. You know, suddenly, we had these Chinese open source models, and you have all of these events that were gonna take place. And I think my thinking from the earliest days was this is neat, but it's very structure suggests lots of disruption and even lots of disruption of the disruptors. And, you know, you can observe a company I I missed. I had lots of opportunity at 10,000,000,000 on Cursor. It was like going once, going twice. And they all like, Oh, no, I don't think so. And what I missed, it's so clear in that company now, is that that was a company that iterated multiple times on their journey. And in fact, even now, I was with the leadership team some time ago. They're iterating again within their current xAI environment. And I miss the fact that some of those really special companies are able to innovate, disrupt themselves, watch the new new thing, catch on. They've got the quality of the team. They're not married to a singular thesis, that this is the only way, and we're just going to plunge ahead. They've got a very flexible mindset. And I think that if you look at that approach, you can see that, yeah, we may see vast differences in the kinds of companies that emerge out of businesses that start very differently.
00:06:43 · David Weisburd, Gavin Ezekowitz
[00:06:43] S1: This episode is presented by Juniper Square, the operations partner for private markets. It's fascinating that you said team and this evolution of products. I invested Anthropic as well, $4,100,000,000 valuation. And I had a relatively simple thesis. One was that AI was gonna be transformative. I had the benefit of actually having a few friends at OpenAI, and they were like, this is it. Because people have been talking about AI, I think, going back to fifties. I can't confirm that firsthand, but they've been talking about AI for so long. And so many really smart people have been talking about AI for for so long. It felt like it was actually gonna come. Nobody could predict how quickly or or to to what degree. The second part of the thesis, I knew that a lot of the top OpenAI investors were... I knew that a lot of the top OpenAI employees were actually going over to Anthrop. [00:07:38] S0: Mhmm. Mhmm. Yep.
00:07:39 · David Weisburd
[00:07:39] S1: Including, of of course, Stario. And that to me was the strongest signal. Yep. And then I had a relatively simple underwrite, which was, okay, if AI is gonna be big, there's probably gonna be a consumer version of it and an enterprise version of it. And I I just, like, licked my hand, finger, put it in the in the sky, and thought, has to be a $100,000,000,000 plus company. Although, at that point, a $100,000,000,000 companies were just insane. In fact, it was the exact same time where Founders Fund was going to their LPs and pitching this whole concept, which was very controversial at the time, which is in order for us to get the kinds of returns that we're gonna continue to get from previous vintages, we need $100,000,000,000 outcome per vintage. Every three years, we need a $100,000,000,000 outcome. And I remember because LPs would would ask me, do you think they could deliver $100,000,000,000 outcome for three years? And my answer was, it... A, it's Peter Teal. So maybe. And b, it sounds absolutely crazy. There's no way they could do that. So I was kind of conflicted myself. Yeah. But if I was to re underwrite Anthropic today or a new company today, I think I would actually take one of those legs of the stool. The whole idea that it would be an enterprise business, I think that's... It's so unpredictable to predict what a company will be like on evolution version number 93. I think you just go back to market, and is the team good? And I know that's not that rocket science, but I feel like in the age of AI, the team becomes so much more important because the evolution and the iterations are just so much greater. It's almost impossible for the human mind to predict where the company itself is going.
00:09:20 · Gavin Ezekowitz
[00:09:20] S0: Interesting how you think about that underwrite, because I think it's maybe not dissimilar to how we think about it. You take your best judgment, your best judgment of how the company will grow in their market, how those, you know, their opportunity set. You know, you you try to get a few years out, maybe get three, four, five. You know, you of course, you've got less and less like probability of of being correct as you get into out years. But you kind of you kind of get this base view of where things might go. And I think that you say, well, look, if if it went like that, you know, are we satisfied with the starting point of that that return profile? Right? If it goes something like that. But then what... I think you've... And I do feel that this is an opportunity set. I think it's also how people will get things wrong, but that that's okay too, is that you've got this potential for truly convex exceptional outcomes that you can't possibly predict. That is how larger market may become, how much of a market a company could inhabit. And currently, it would just be crazy speculation that a market might shift. But cast your mind back not too far to say Uber. A very intelligent way of underwriting that company may have been, here's the taxi market, here's the black car market, here's how big they are, and here's how much market share they can take. None of us... I didn't underwrite Uber, but you didn't predict that you were actually... Once you made vehicles available in this manner, you were going to grow that market massively. That reference point was irrelevant. And I think, you know, we maybe we were seeing this with the Anthropic, with their new wet labs, with their ability to innovate in in biotech with new molecules, be more predictive of what might be successful. And we could end up with this really incredible outcome for that company out of a part of the business that nobody really thinks that much about today. I think we we're always hopeful that we'll get one of those those outcomes. But the core underwrite has to be, you know, do we actually think if this company just delivers, do we think it... Are we gonna... You know, does it meet does it meet what a sensible return?
00:11:45 · David Weisburd, Gavin Ezekowitz
[00:11:45] S1: We were talking about before we started recording valuations [00:11:48] S0: Mhmm. [00:11:48] S1: How hard it is sometimes to invest in these companies because they always seem overvalued the best companies. How did you go about thinking about the valuation of Anthropic at the time? How do you go about underwriting such a transformational company?