The Exchanges

Q capital. It's over. That was the, that was the whole idea. But then some people thought, oh no, this is an opportunity. This is an opportunity to roll up companies, to apply AI, to use these efficiencies. And one of those people, or one of those funds was General Catalyst. And so you guys actually like really leaned in hard for this. What was the decision making process for it?

A Yeah, for us, it was a boat strategy. So we actually think three approaches can win. One, some folks view it as the model companies will end up being the winners. They're gonna keep iterating. They make better and better models. They'll go direct to the consumer. And we're obviously investors in Anthropic, large investors from the last round, from this current round. Um, we absolutely think companies like Anthropic and OpenAI and Google can benefit and the model layer can benefit. So we agree with that. We also agree with folks who say, well, it's been overestimated. SAS is not dead. If you look at public market comps, they've continued to grow, do well. There are all kinds of new, interesting SAS companies that are being started and growing. But we also think there is this third bucket. So we're kind of an all of the above. We think there'll be winners in each category, and we obviously want to be part of them. But that third bucket is for really fragmented industries where it's very hard to sell into AI native services and products. Can we actually build the AI native service platform and software and then go buy our distribution? So a few examples. One that was very early on was Crescendo, where we led several rounds of funding to build AI native software for call centers. And we teamed up Andy Lee, who ran Alorica for over 30 years, a call center chain with two amazing CTOs…

AI assessment note: “we actually think three approaches can win... that third bucket is for really fragmented industries”

Q That's so fascinating. Can you talk through the funding mechanism part of it? Like how do you structure it?

A Yeah. So we normally do one or two rounds to build the software piece. Like with the Titan MSP, for example, we gave them kind of a traditional seed series A to build out AI automation for IT services for MSPs. And they went out and they got six pilot clients and over three or four months, they sort of showed us, Hey, look at all the tickets that happened in MSP. We can now automate 38% of them. So when that happens, then we start talking to them about a second round of funding. We say, well, let's actually go look for targets because if we can buy one of these companies and automate 38%, we're certainly going to increase the margin and be able to reinvest a lot of that free cash flow into growth and create a really successful company. And so we look at a lot, especially the pilot clients that they're working with and who could, who really wants this AI technology. And unlike private equity, we screen really hard for does this company want to change? Do they want to implement AI? Um, and then of course we want to hold them for seven to 10 years and go public and not necessarily add debt and cut costs. That's a really different model than private equity. Um, but in their case, then we gave them a second round of funding when they found their target RFA. And now that they've found that target and, you know, are doing really well on the AI transformation, then they say, okay, now …

AI assessment note: “investing between a hundred and a hundred fifty million in each of these projects”

Q Well, this is fun. This is great. I've been waiting to do this for a while now. You are the managing director at General Catalyst. You are a managing director at General Catalyst. I don't think many people know the breadth of General Catalyst's asset management function. So could you just break down how it's structured?

A Yeah, sure. I can talk a little bit about GC and how we're set up, what we're all working on. So we were a venture capital firm, but we're evolving to be really a company. And people ask me, well, what does that mean? There are two big parts to it. As a company, one, we're actually building companies for the long term. So folks have seen the announcement about us buying a hospital system in Ohio, for example. That's a, we did that through an organization called HATCO, which we incubated and then bought a hospital, and we plan to hold that for a really long period of time. We have a wealth management business that we've set up to help founders manage their money. That's another company we've built in house that we plan to hold for a very long time. And then finally, we have now an AI consulting business called Percepta that really comes in and changes Fortune 100 companies, helps implement AI, Really leverages everything we've learned from AI investing, and that's another company we've built in-house that we, you know, will hold for a really long time, maybe forever in these cases. So GC as a company is building in-house what we call transformation companies, with these three being examples of businesses we think should exist, are good for society. We're not planning on taking them public. We want to hold them for a really long time. In addition to these three transformation com…

AI assessment note: “two big parts to it... one, we're actually building companies... we have another bucket”

Q This was a good question from Kyle Harrison, but he wanted to ask, how do you decide when to choose from building an AI roll up or investing in another SaaS company?

A Yeah, it's a really good question. Uh, one answer to that is percent automation. So if we think a space is going to be 90 or a hundred percent automated, then probably software is the best solution. And honestly, an incumbent like Microsoft or Amazon or Google that has the distribution can just push the software. It can be part of your Google workplace or your prime subscription. So if something's a hundred percent automatable, it probably should be a software or agentic solution And then most likely the winner there could be a fast growing company, but also it's very likely someone who just already has the distribution. Um, so if coding gets fully automated, maybe it can just be pushed through by Google or Microsoft or someone else. So one thing we're careful about in the AI enable rollups is we, we target 30% automation at least, but we actually don't want more than 70% automation because if something is approaching 80, 90 or a hundred percent automation, then there's really not the people services part of it. So that's one important part. The second thing is fragmentation. Like when the industry is really hard to sell into, imagine creating AI native software for homeowner association, HOA management, like that's just extremely hard to sell into. So you could create an amazing product, I'm sure, but your sales process would be very, very slow. So the second thing we look for…

AI assessment note: “one answer to that is percent automation... The second thing is fragmentation.”

Q You've been at General Catalyst for a couple years now. What is the biggest lesson that you've learned from him on?

A Definitely, um, advocating on team and paying up when you have to. Like, um, I got to learn from HT some epic stories about how GC got involved in Stripe. And, you know, I won't repeat all of the details there, but there are some companies you just really want to be in. And it's less about the terms. It's more about catch them early. Like you can buy 10 or 20% of an iconic company at seed or at A or at B. So a lot of people have the mentality of, oh, this is a hundred million dollar check. Let's spend all our time. This is more important than like a one million seed check. But the reality is normally your a hundred million check is buying you 10% of a company. Your seed check for one million is also buying you 10% of the company. So it's really important to kind of what are going to be the next 50 iconic companies and ideally try to catch them early and pay just as much attention to buying 10% of some seed business as 10% of an established business. So we have really a GC shifted a lot. Our focus on seed, um, with the acquisition of La Familia and bringing in Jeanette and who's running our Europe practice and as a very prolific seed investor from La Familia, um, Venture Highway, the India seed firm that we also acquired, uh, we brought in recently and then Yuri to come lead our us seed practice. He had a successful seed firm. So I think that mentality we're really pushing throu…

AI assessment note: “Definitely, um, advocating on team and paying up when you have to.”

Q in tech, and that there's going to be an 86% chance that there's going to be more layoffs this year than in twenty-twenty-four. Um, but I do think I don't know if that one's true or not, so you'd have to check the data. But, um, you would think that because of all this mix, new industries might pop up. What are you thinking might, like, what could come next?

A Yeah, I think it'll be a lot more of things that right now are really limited to people with resources. So I think there'll be a lot more legal use cases and way more representation and legal, I think like real time understanding of your company, your balance sheets, accounting, it'll, There'll be a lot more there. So I think it'll be industries that already exist, but much more abundance. On the nursing side right now, if you're dispatched from a hospital, maybe they follow up with you for three months or six months, but it just doesn't make economic sense to follow up with patients nine months a year out. But if you were truly doing the best thing for your patient, you would follow up with them in nine months and in 12 months. So I think a lot of these industries like healthcare, insurance, legal, where people have resources, but then are tapped out, there'll be just a lot more around that. And so I think you'll have way more sophisticated markets in all of these places.

AI assessment note: “I think it'll be a lot more of things that right now are really limited”