Bain Capital Ventures Bets $1.6 Billion on AI’s Next Act

0:00 Bain Capital Ventures has raised a $1,600,000,000 fund to back early stage AI companies for building on a playbook it established with its previous fund 10. ECB partners Slater Stich is with us, and this fund is for life after AGI. Explain. That's right. Well, first of all, Ed, great to see you. So good to be here. Thanks for having me on the show. You're right. So one of the big ideas that we have for this fund is that we have, stored up this incredible ability with artificial intelligence, and we've seen some applications for it. In some cases, there may be the more obvious applications. But as, the technology gets even better, we should expect an explosion of new applications. And we wanted to approach this fund with the philosophy of really thinking about that hard from first principles. What does it mean, like, when we go through a technological revolution and intelligence just as profound as electrification or mechanization earlier? What would it mean to, to sort of have a post AGI economy?

1:02 There there are three different sort of well, four probably flavors of this infrastructure, physical AI, which can mean robotics, security Mhmm. Which, you know, given the events of the last seven days is massively important, and then also services. Of those four, to your mind, which is most present in the post AGI life that you're envisaging? I think that all of those will have important roles to play, and it's just a question of sequencing, you know, sort of in what order will we see these different tests.

1:30 See an order? I I think that, you know, things that seem sort of like knowledge work on a computer flavored are going to be the form factor where it's easiest to make progress fastest. We sort of know how we would ascend up the scaling curves there. The models the base models get more intelligent each generation. The harnesses get better. The sort of task horizon for agents gets better. The tool usage. It's just easier to do things in a purely digital domain. So that's where we see it happening first. But, of course, we're incredibly optimistic about applications and robotics and other physical world, applications over time.

2:06 I know you guys talk about, life after AGI. The the difficulty is AGI is not universally defined. Some would say we we we are we are at AGI. You know, I'm thinking more recently about OpenAI's release of Astra. Mhmm. And and Greg Brockman is an example saying, you know, this is the first step to true AGI. How are you defining it and measuring it? Well, you know, one thing I think about is if I just gave my past self information, what I have called this AGI, they went back to Right. How I thought in 2016 or something like that. And by that measure, absolutely. I mean, I I think if you had told me that we would be solving millennium problems or being able to run these incredibly useful long running agents that would have surprised me at the time. So I would say that from a, economic and also even from a scientific perspective, a lot of the promise we're already already seeing there. You know, I do think AGI is one of these terms that can never be fully defined. No matter how good the systems are, there will always be sort of some next thing. But I I you know, I personally am most interested in the ways that'll affect the economy, and I feel like the technology is already there to do so much.

3:20 This is an early stage fund. Right? So it's $1,600,000,000 to invest at that early stage for companies where you feel they have an opportunity in that future economy? So if we take physical AI robotics, for example, where would you apply that to the economy today? Where are the gaps in this US economy where you think, okay. This is ripe for for robotics to be the solution. Yeah. I think that, the nature of you know, again, I think a lots of things will happen in the long run. In the short run, you know, application areas with predictable environments with sort of relatively set tasks are the ones that will, of course, be easiest.

3:57 But I you know, in some ways, in the long run, that might be the the least important. So, you know, for example, we're investors in a company called Sunday Robotics Yes. That's working on, home robots, sort of fully integrated to that use case. And I do think that when you take an application like that really seriously, you can make progress very quickly. You know, I do think that there is also, there's also this question of, you know, the industrial applications Yeah. Will probably have some of the biggest impacts. We have, you know, sort of good industrial robots for relatively predictable manufacturing tasks. For manufacturing tasks that are less predictable, that's where intelligence can actually play a role.

4:39 Can we talk a little bit about investing? So this is a specific fund. It is fund 11 technically. It comes up to fund 10. What's realistic in a in a calendar year? Do you go after high volume, or do you just say, okay. Like, this is high conviction in this environment. We have a thesis for this fund, so we'll do a handful of investments and kinda cap it. How does that work? We don't think about it in in that way. Like, the way that we think about it is that we know what it looks like when we see a incredible founder pursuing an outlier opportunity that we believe in. You know, we might get the conviction on that opportunity in different ways. In some cases, it could be thesis driven like you're describing. You know, I would say that our investment in fleet, for example, the oil environments company Yeah.

5:22 Happened that way. You know, in other cases, it's really through conversations with the founder and learning opportunity that we get the conviction. But I don't think about it in terms of, you know, capital deployment over some period of time or some sort of strict rules about how we would deploy it. It's yeah. Take us inside Bank Capital Ventures, it's how working as as a firm at the moment. So if you have an opportunity or an idea, you're the sponsor of it, how did did the partners kinda get around it and decide, this is the bet we wanna make, particularly when you're saying, okay. We wanna invest in an opportunity for life after AGI.

5:56 Yeah. I think it's so one one way that I think about this is opportunities that we think could be tremendously valuable and that we understand technological path, to achieving them. So for example, you know, in companies like Decagon or, Cognition, you know, we understand the promise of what those companies in automating software engineering or, customer support. And it's sort of, clear that the plan if the if the sort of founders are able to do the things that they want to do, that we should be able to achieve that. There's other cases, you know, a company like Periodic Labs, for example, which is building an AI scientist initially focused on material science applications where we spend a, you know, sort of more time on the technology and sort of why, we think the founders are gonna be uniquely able to achieve that.

6:49 I I'd like to to end the conversation talking a little bit about cognition. You know, they've just closed around. Around. But the thing that's changed for me in the in the last calendar year or so is the the ads in San Francisco. There I'm I'm paraphrasing, but it says Devon is actually good now Yeah. Which is sort of an admission that it's taken time. But that's amazing. I mean, you see billboards over SF all the time, but just in Cognition's case, what you saw in the development arc.

7:13 Totally. So, I really love that campaign. And, what I like about it is to me, it's Cognition calling their shot really early on. So, you know, at the time that they sort of put a flag out and said, we are going to be the autonomous software agent, that works. You know, I would say that the base models were not quite there yet At that time. But that was an easy thing to do. But they knew they understood exactly where things were going and sort of understood that that was the valuable place to be in the long run. And so I think it was, like, a courageous thing to do, and I think they called it perfectly.

7:46 Is there a next cognition then with this fund that you think you can find? We do. I think that there will be, you know, other applications that look like this. And then I also think that as you just sort of go up levels of intelligence automation, there will be all sorts of things that we can't even anticipate yet.