How I Invest with David Weisburd
00:14:36 · Matthew Harris
We, twenty years ago, invested in Kiva Systems, which was the first sort of warehouse robotics company that Amazon bought for over $1,000,000,000 and consistently throughout in manufacturing and distribution robotics. And here in the past eighteen months, just another kind of Cambrian explosion of amazing robotics companies, including household robots and all sorts of really kind of unprecedented advances. And so that's, you know, maybe a third of what we do. And then we've made 20 investments starting in late twenty twenty two in what people now call AI native services companies. This whole question of like, if you can actually compete in a major industry instead of just selling technology to that industry, depending on what the industry is, it's just a massive TAM expander and allows you to have a more defensible business, you know, relative to the labs themselves. We worry about the Foundation Model Labs and the pressure they will face to build application layer functionality, horizontal and vertical. And one element of defensibility is to move out of application layer applied AI and into actually doing the work. And so we our first version of this is a company called Reserve, which was actually a fun exercise that's still worth doing. Think we, you know, I'm a financial services investor, so we mapped all the financial services and all the business models. And we asked ourselves, if you had a machine that could magically read and write, what are the activities within financial services that would be most vulnerable to this machine? And the answer in our mind was insurance claims, which is really just a human swivel chair, multi screen. You get notice of loss on a policy. You have a policy. You have to read those things. You have to synthesize them into a loss adjustment. It is like what version one generative AI, if you remember, that was what it was born to do. And so we started incubating this with a with a customer, a design partner customer and AI native insurance claims business that ended up being called Reserve. And when we incubate companies, we don't take any common stock. We just put money in. We recruit a founder and then we give them all the common stock. And so they really are the founder and that company is they'll do well over 100,000,000 in this year in revenue and their second full year of life.
00:17:16 · Matthew Harris, David Weisburd
And it's been an extraordinary growth curve. So we were heartened by that. And we went on, as I said, we've done 20 more of these, including two law firms and automated earthmoving company and a home health agency and six or seven more insurance related native services companies. And so we think those companies and actually so far, it's been very clear that they've benefited from advances made by the Foundation Model Labs. And we want to be levered to that, not fighting against that. [00:17:49] S1: That's where I wanted to go, which is at some point, advanced intelligence gets so advanced that it's doing everything. And we're we're like that famous essay where we're just these... We're back in the jungle, and we have these overlords. But until that happens, why is going directly to services, why is that a moat? And maybe you could double click a little bit about how your strategy relates to the large LM models.
00:18:19 · Matthew Harris
[00:18:19] S0: Well, it certainly calls for speculation. I think these companies have the theoretical ability to do anything. So what we can do is look at their incentives. Right now, a vast amount and fast growing percentage of the revenue for OpenAI and Anthropic is coming from large corporates who either directly or via API through partners are accessing their models to automate core business functions. They will have to make a choice at some point along the way or at many different points along the way about which one of those industries they want to actually compete directly with. So right now, Anthropic is making a lot of money from the legal industry. And our view, probabilistically, is that that will inhibit them in starting their own law firm. And the same can be said of many other verticals. They make a lot of money from the insurance industry, and that will likely inhibit them from competing with Travelers, who is a massive customer of theirs, competing with Aon and Willis Towers Watson, who are massive customers of theirs. They feel like they have enough fish to fry selling, of course, just base intelligence. And then building vertical applications on top of that to sell to those corporate end users, not to mention consumer businesses, which they also have. So they may look at those three vectors, the intelligence vertical applications, consumer and horizontal applications like coding applications, for instance. They may look at that and say, that's not enough. We also have to start a law firm or a home health agency or an earthmoving business. But our probabilistic view is that will be pretty long down the path and may never happen. Like, for instance, in fintech land where I've been living for a long time, there's always this question of, you know, if you look at Google and Amazon and Facebook and Apple, which one of those will move aggressively into consumer financial services? And the ones that have always had the most capability actually were Google and Facebook. They had incredibly broad. You could argue Apple, but for a variety of reasons, Apple doesn't like to use data. And so it's they've always moved very, very carefully in financial services. But the most capabilities resided at Facebook and Google and they never have. And they've made little forays here and there, particularly Google.
00:20:58 · Matthew Harris, David Weisburd
They'll like announce something every two or three years and shut it down. And the reason is they're an advertising company. They make their money from the financial services industry in, you know, 20, 30% of their revenue. And so the incentive they have to go poke that industry in the eye by directly competing is a real problem. [00:21:21] S1: Is that because they've run this calculation, they've realized the best business model is advertising business? Or is that because culturally, they have this whole ad team that has 1,500 employees, and they can't cannibalize their own business and culturally just wouldn't work. Which one of those reasons is driving that?
00:21:40 · Matthew Harris
[00:21:40] S0: I mean, they're related and inextricable. It is the cash cow. Right? Which means it's got this power base. And it is observably one of the best business models in history. It's 100% margin business. So those two things are like inextricable and together formidable and so far successful in keeping Google out of offering direct consumer financial services, despite having they bought one of our companies so they could get into the business and then they shut it down because of this angst. Now Apple has a credit card. As I said, I think they've done it in inelegant ways because of their own fear and inhibition. But they don't care about the credit card companies. They don't really focus on selling advertising. And so they're more gloves off, I'd say, as it relates to competing in financial services because they're not wed to that entry. Yes, sure, they sell some MacBooks to venture capital firms. But broadly speaking, they their butters, their bread is not buttered by the financial services industry. And Amazon is another fascinating example. If you go back ten years, they had massive plans in consumer payments. They were going to be a proper disruptor in consumer financial services. And you know what killed that? AWS. All of a sudden, their most valuable business had financial services as a core customer. And so it wasn't the cash cow that advertising is at Google. But at the top of the house, you're starting to have really hard conversations about should we launch our own banking product? Should we get consumers to keep money with us? We'll pay them interest and they spend it on our products, basically do what Starbucks did with their app. Amazon's never really done any of that, even though the plans are still on the shelf because JPMorgan Chase is just too valuable a customer if you're running AWS and if the person running AWS then becomes CEO of the company. So these are the conflicts that we look to historically to give us some confidence about where to put our money today based on predictions about what the Foundation Model Labs are going do and not do. And we, having thought about it, resolved that they are unlikely to start law firms, for example.
00:23:57 · David Weisburd
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