Uncapped with Jack Altman
· Jack Altman, Bennett Siegel, Kevin Hartz
[00:00:00] S0: If you gave somebody $1 billion and then they went and bought an asset for $1 billion and you only own 20% of that thing, don’t you now have $200 million? [00:00:00] S1: The ironic element of this is that the founder can’t lose. The founder has literally bought into a business with embedded asset value that they now own a large percentage of. But unless these companies appreciate dramatically in value, the venture capitalist owns a relatively small percentage. Now people are doing convoluted structures where there’s a holdco and an opco and there’s carry and there’s waterfalls. But no one has actually proven a way that you can monetize this in any way that resembles venture-like returns. [00:00:00] S2: The other dimension of it, in this venture capital/private equity play, is simply that venture capitalists are very good at watching the top line. They want things to blast off, and they’re not so precise. This is all about the top line, but the bottom line more importantly. Venture capitalists don’t pay as much attention to that with their companies. So it just doesn’t feel like the right culture fit for this sort of stuff. [00:00:00] S0: Are there any forms of rollups or structures that you are bullish on? When you look around the different types that are happening, is there any form where you’re like, all right, if I had to buy one, that’s the one I’d buy?
· Jack Altman, Bennett Siegel, Kevin Hartz
[00:00:00] S0: Are there any forms of rollups or structures that you are bullish on? When you look around the different types that are happening, is there any form where you’re like, all right, if I had to buy one, that’s the one I’d buy? [00:00:00] S1: I think there is something to be said for looking at services-oriented professions that have largely recurring, if not truly recurring, revenue sources, and looking at how you could replace people with technology. Because if AI has been very good at one thing, it’s looking at traditional pockets of labor spend and automating it. So there’s a reason why accounting rollups are interesting for people. There’s a reason why HOA rollups are interesting for people. I think ITSM as well, for that reason. It all deals with tickets and deflection and replacing call center people. That feels like a very interesting area, but I would argue 90% of the value created is going to be buying the asset for the right multiple, which once again, venture capitalists are historically very bad at. [00:00:00] S0: So you’re not going to be doing any rollups? [00:00:00] S1: We will not be doing any rollups today at A*. [00:00:00] S2: On the other side, there are always great teams, exceptional teams, in using technology. Bending Spoons comes to mind, as we just sold Eventbrite to Bending Spoons. That’s an incredible operation of how they integrate all these assets, and what they’re doing in Milan is remarkable.
· Kevin Hartz, Jack Altman
[00:00:00] S2: On the other side, there are always great teams, exceptional teams, in using technology. Bending Spoons comes to mind, as we just sold Eventbrite to Bending Spoons. That’s an incredible operation of how they integrate all these assets, and what they’re doing in Milan is remarkable. [00:00:00] S0: What about within AI? What are you guys most excited about? Where are you anxious? Maybe frame up a common meme right now. Software’s extremely difficult because the labs are just expanding, and the workflows are being replaced by agents, and the workflows I need that are important, the labs are going to own. [00:00:00] S2: We can’t take that position. We want to back these independent companies. The labs need to have a very audacious appetite and keep the growth up. But we’ll still keep backing the application layer all around, where we see the right barriers, the right teams, and so on.
· Kevin Hartz, Bennett Siegel
[00:00:00] S2: We can’t take that position. We want to back these independent companies. The labs need to have a very audacious appetite and keep the growth up. But we’ll still keep backing the application layer all around, where we see the right barriers, the right teams, and so on. [00:00:00] S1: There’s a distinction, obviously, between application-layer AI companies and more traditional incumbent software. I don’t know the last time we’ve heard a founder pitching a traditional software business. Now, part of that is the meme that everything’s an AI company. Everyone puts AI in their deck. I think systems of record are still very sticky for a reason. The issue, we all know, is if you can vibe-code an app in a matter of minutes, why do you need so many engineers? What’s the value of the workflows that you’ve built? But what we’re seeing on the application layer is that people are going after systems of intelligence, going after systems of action. They’re new types of spend, and we’re going to continue to back those. In terms of the public markets, there is a reason software’s having significant drawdowns, but the best companies should be able to navigate this. Kevin mentioned early on that we were investors in Ramp. I would say they are a great example of an incumbent pre-ChatGPT company that has now become an AI business, and agents are driving top line and margins. The best teams are going to adapt. So I think you’re fine if you’re in an incumbent software business, as long as you have a team that is going to rearchitect everything from the ground up.
· Bennett Siegel, Jack Altman
[00:00:00] S1: There’s a distinction, obviously, between application-layer AI companies and more traditional incumbent software. I don’t know the last time we’ve heard a founder pitching a traditional software business. Now, part of that is the meme that everything’s an AI company. Everyone puts AI in their deck. I think systems of record are still very sticky for a reason. The issue, we all know, is if you can vibe-code an app in a matter of minutes, why do you need so many engineers? What’s the value of the workflows that you’ve built? But what we’re seeing on the application layer is that people are going after systems of intelligence, going after systems of action. They’re new types of spend, and we’re going to continue to back those. In terms of the public markets, there is a reason software’s having significant drawdowns, but the best companies should be able to navigate this. Kevin mentioned early on that we were investors in Ramp. I would say they are a great example of an incumbent pre-ChatGPT company that has now become an AI business, and agents are driving top line and margins. The best teams are going to adapt. So I think you’re fine if you’re in an incumbent software business, as long as you have a team that is going to rearchitect everything from the ground up. [00:00:00] S0: What about hardware and hard tech? I know you’ve been incubating a company that is software-enabled hardware, I think. I assume you guys have been investing in it. How do you guys think about non-software, potentially even non-AI, but at least hard tech hardware companies?
· Jack Altman, Kevin Hartz, Bennett Siegel
[00:00:00] S0: What about hardware and hard tech? I know you’ve been incubating a company that is software-enabled hardware, I think. I assume you guys have been investing in it. How do you guys think about non-software, potentially even non-AI, but at least hard tech hardware companies? [00:00:00] S2: Again, we want to go where the talent is, and we’re being drawn to these various hardware companies because there are really impressive people. It’s happening across the board. There’s a revolution there. We certainly don’t want to get caught in the same traps that have been difficult for hardware in the past, but hardware puts you out in the real world. Before, in software, we were trapped like a brain inside of a jar. Hardware and robotics and so on is an exciting new world for us. [00:00:00] S0: There is some good defense if you have some sensors and things out in the world, at least. Someone can’t just come along and vibe-code that. [00:00:00] S1: I think that’s exactly true. We just haven’t hit the ChatGPT moment for robotics. AI for the physical world should be as large, if not larger, than what we’ve seen for the knowledge world. The challenge is, right now, we haven’t seen much in the way of commercial applications. We don’t care, we’re seed investors. We’re backing robotics companies, we’re backing companies working on sensors and edge AI. But we do think about the number of robotics companies that have raised at huge valuations with very little commercial promise. So we think a lot of this is still to come.