How I Invest with David Weisburd
00:32:53 · David Weisburd
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00:33:43 · Joseph Coyne
[00:33:43] S1: And the numbers are sort of the numbers. Now those numbers have shifted. Right? Like, the the big outcomes are now tens of billions, not a billion. So there is a world where that that can happen, but it's still very low probability. And so when I think about portfolio construction, those are the nice to haves, not the need to haves in terms of how I underwrite. Like, if we're fortunate enough to get into a company that's a $20.50, $100,000,000,000 company, that's fantastic, obviously. But we are underwriting a more rational, high probability outcome, and that gives us some price discipline at entry. But I think that's why we also play in the intersection of what would be formerly enterprise software and AI core use cases, not in the sort of lab based world that requires billions of investment into the top talent, which has just become more expensive over time. We'd like to be the beneficiaries of that great work that's being done by those model companies without investing and owning that team. Right?
00:34:39 · David Weisburd
[00:34:39] S0: I have this come various conversation with Matt Harris from Capital Ventures, where I know you used to be. And the heuristic he used is in evaluating, for example, Anthropic's valuation, it's reported it's gonna be $2,000,000,000,000 valuation is... One way to think about it is just to take off three zeros. So imagine taking off three zeros from 2,000,000,000,000, you get 2,000,000,000. And imagine taking three zeros from a 100,000,000,000 reported kind of 2026 and and run rate, so a 100,000,000. And a 20 x revenue is not that unreasonable. It's just people get... I think rationally so or at least evolutionarily so, people get so hung up on the sticker shock that they can't imagine there's still being upside at 2,000,000,000,000. But then when you look at the revenue, it starts to make more sense.
00:35:25 · Joseph Coyne
[00:35:25] S1: I think that's a fair argument. My counterpoint to that would be the probability of getting that type of outcome is just very, very long tail. Right? It's like a six sigma type outcome or a generational outcome. If you rewind twenty years, it would be like being the investor that found Google. Right? Those guys did okay. Similar to that, the folks who found OpenAI, Anthropic, etcetera, will do very, very well. Now, as I think with, like, my public market investor hat or my late stage investor hat, those companies are also facing new threats, both from each other. Right? Every model release is a step change in terms of functionality. And they're fighting in sort of a duopolistic market right now, but new entrants are not a fordrawn conclusion. Like, they may come. Right? Open weight models may come into into a higher use. Foreign models that we that we aren't even in the conscious right now could come into the into the purview. And so I think rising competition for a massive... Right. You're you're... They've demonstrated the TAM and the growth of the TAM. What you see in markets like that is that you have new entrants, lower cost entrants. The consumer willingness to pay or expectation to pay is between 0 and $10 per month. Like... And those are some of the early adopters. Over time, that probably goes down while models and switching costs between models become... Switching costs become lower. Right? I've... I switch between four to six models in a week and agents. So switching costs are low. I'm always chasing the best and fastest LLM for my use cases. And so what that results in, it potentially is that it's harder to monetize your huge user base because of competition. And we're not even talking about some new entrant that could be the next Anthropic. If we rewind two years ago, we wouldn't have been talking about Anthropic necessarily. We would have been talking about OpenAI. And looking at that graph can be a cautionary tale in the sense that OpenAI was inflecting at a rate that nobody had ever seen, and then here comes Anthropic and actually apexes it. And so seeing that is an interesting thing to watch, let's say. I was not fortunate enough to invest in OpenAI or Anthropic, but some of my LPs were, and they've asked me over the last several years, like, when to sell.
00:37:36 · Joseph Coyne, David Weisburd
And I've given a similar argument for them, especially depending on where their basis is. [00:37:41] S0: So I did invest in Anthropic at a $4,000,000,000 valuation. So maybe you could give me some advice because I'm trying to get a balanced view in terms of the upside and the downside moving forward. How would you underwrite it today, October 2026? [00:37:55] S1: Well, I think I would look at the implied forward capture of the market. Right? So how big is the market likely to be, then what percentage are you expecting to capture as Anthropic vis a vis or relative to OpenAI and some unknown entrant or entrants? So I think that's hard to handicap on the who's coming next, right, conversation. [00:38:15] S0: But It's unknown unknown. Who's gonna have that idea or the resources?
00:38:18 · Joseph Coyne
[00:38:18] S1: The unknown unknown. But you have other folks that are devoting a lot of resources to the space that have billions of dollars in reasons to be highly defensive. The Googles, the Metas, the Amazons, etcetera. Right? And they they may take a different approach or a similar approach to building very very robust models, but that will only up the ante in terms of competitiveness over time. And then if you look at or make an assumption around whether they'll just be two players in the future, I think it's very unlikely that there'll be two dominant players in the LLM world. So if you start to model, and you can sort of stress test this, right, a few more entrants, and then you look at the market size, of course, it's gonna continue continue to grow. What do you... What's the implied capture rate of that future revenue in three, five years that Anthropic would have to have to justify their current valuation? I think right now, it is converging to a rational sort of pre IPO price, so you're probably in a in a good spot. But that's absent my assumption around increased competition and lower cost players. Now I think the other angle or lens is what is their... Who are the customers of all these LLMs? OpenAI tends to be slightly more consumer. Anthropic Anthropic tends, especially with Claude Code, tends to be slightly more enterprise. So for that reason, I would value every dollar revenue differently across those two. And so I give a little boost to Anthropic in that regard, and you can see that's probably why they've eclipsed OpenAI in terms of their growth rate.