How I Invest with David Weisburd
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.
00:39:38 · David Weisburd, Joseph Coyne
[00:39:38] S0: I'll tell you the bold case. Virtue of Lucas Swisher, he runs growth for Coyne, previous podcast guest, and he talked about the three s curves of adoption. So the first s curve, the early adopters in terms of LMs from a revenue standpoint have been developers. What's crazy about that is that there's only only 50,000,000 developers in the world out of 8,000,000,000 people. And on top of that, only a small percentage of developers have actually implemented, if you look at worldwide kind of engineers. So we're still at really the small end of a small market. Now, sure, enterprises have adopted it, but to your point, 95% of them have failed. There's not that mass adoption. Not... There... There's not many enterprises that are super users today. So we're still seem to be... And then, obviously, there's all of enterprise. First, have engineers, then you have all of enterprises, then you have consumers. And then you could argue a fourth s curve, which is agents. Mhmm. So some smart people would argue that your TAM is not actually 8,000,000,000. It's 8,000,000,000 people and their agents talk to each other. So, in terms of the adoption curve, you... We started this conversation talking about we're in the first inning of AI. [00:40:48] S1: Well, I think you just made my point a little bit there too. [00:40:50] S0: I I I there's an argument there.
00:40:50 · David Weisburd, Joseph Coyne
[00:40:50] S0: I I I there's an argument there. [00:40:52] S1: Side, there's room to run. Right? There's definitely room to run. So because you established that, you know, this market is growing and the TAM is expanding even from a very large base, it's extremely attractive. And I think that will also attract new entrants, new players, whether it's, you know, the FANG players or some player we haven't even started talking about. But that could erode, you know, pricing power. Right? So it could erode in two ways, which is over time, you just see switching costs and you see the markets divided among more players. You can see the entrance of sort of where we invest, which is bespoke enterprise software meets AI for specific industries that has foundational [00:41:27] S0: Verticalization. [00:41:28] S1: Yeah. That has more foundational, you know, subject matter expertise baked into it, which then leads to trust within specific verticals, like airlines, banking, insurance, etcetera. And then over time, I think you also have a pricing compression, which is like enterprises are gonna be willing to pay more, but how much more will they be willing to pay? In order for... To to really capture the the lion's share of the wallet, you need to have much higher r... Higher ROI than we're seeing right now in the in the first inning. So it's sort of multifactor. It'll be fascinating to watch, but I don't think you can lose coming in where you came in.
00:41:28 · Joseph Coyne, David Weisburd
[00:41:28] S1: Yeah. That has more foundational, you know, subject matter expertise baked into it, which then leads to trust within specific verticals, like airlines, banking, insurance, etcetera. And then over time, I think you also have a pricing compression, which is like enterprises are gonna be willing to pay more, but how much more will they be willing to pay? In order for... To to really capture the the lion's share of the wallet, you need to have much higher r... Higher ROI than we're seeing right now in the in the first inning. So it's sort of multifactor. It'll be fascinating to watch, but I don't think you can lose coming in where you came in. [00:42:01] S0: Also, investor in vertical AI solutions like Legora. How do you think about horizontal versus vertical? Are there gonna be different areas where vertical wins versus horizontal wins? And what's your framework for that?