00:00:00 · Marc Bhargava
[00:00:00] S0: GC is one of the three largest venture players. We put up to work about 1,000,000,000.5 on the creation strategy. And first and foremost, it's really around incubating companies. There's a ton of potential right now, especially to incubate applied AI companies. So as the models get better, whether it's OpenAI or Anthropic or Google or XAI or others, we really do think there'll be a lot of new companies that can be built on top of this technology. There's a huge opportunity on creation to incubate applied AI companies. When we do that, we go one of two ways. Either we incubate the applied AI company and we have it scale organically, and then we give them capital for marketing and growth, or that second part has begun to be called the AI enabled roll up. And, obviously, we are extremely involved in companies like Long Lake, Eudia, Titan MSP, Beacon, Crescendo, and others who are kind of the leaders now in this field. At GC, we've been investing between 100 and 150,000,000, but over, you know, three or four rounds of funding. We like to lead at least the first two, and then we start bringing in other investors in the third or the fourth. We think in this much larger TAM than software, you can have software like margins. Because once you take out 30, 40, 50% of what people do and free them up to do the hard stuff, you can double the revenue. Unlike private equity, we screen really hard for, does this company want to change? Do they want to implement AI? And then, of course, we wanna hold them for seven to ten years and go public and not necessarily add debt and cut costs. Some of the companies in the roll up will hit a 100,000,000 of EBITDA, and they're, like, less than two years old.
00:01:21 · Molly O'Shea, Marc Bhargava
[00:01:21] S1: Oh my god. Marc Bhargava, welcome to Sourcery. [00:01:35] S0: Thanks for having me. [00:01:36] S1: 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 Yes. 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?
00:02:00 · Marc Bhargava
[00:02:00] S0: Yeah. Sure. I can talk a little bit about GC and, you know, 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 wanna hold them for a really long time. In addition to these three transformation companies, we have another bucket where we're probably better known for, which is our funds. And so there, we have the traditional venture funds, Ignition on the early stage, Endurance for later stage. We also have a customer value fund for helping companies scale really quickly, which we can talk about. And then lastly, where I'm focused is on the Creation, which is part of our funds business. And Creation has been a very fast growing fund for us because it's all about manufacturing outliers. So while our venture funds are always looking for the next great company or person, we on the creation side are incubating companies, but ones that we would wanna take public in seven to ten years. So they're not necessarily companies we majority own or we would hold forever, But they're businesses we think really should exist that we're creating through creation that we wanna go and take public in seven to ten years.
00:03:54 · Marc Bhargava, Molly O'Shea
And most of the time, they don't exist because there's not enough capital for it or it's multidisciplinary, so it really requires a lot of different expertise or it's a bit more traditional or outside the box, things like the AI roll ups that we're working on these new thesis spaces that just haven't really happened yet. So creation is where I spend most of my time. But GC as an organization, we truly are a company now, building companies for long term, creating and incubating companies that we wanna take public in the future. [00:04:20] S1: So how large is this? And with the company as a new structure, will you be weighing it with AUM? Like, how does this differentiate?
00:04:29 · Marc Bhargava
[00:04:29] S0: So we're kind of one of the three largest venture players. The way we really view it is on the returns for our investors. So our venture funds have to outperform and do really well to attract more LPs, and obviously to attract more founders. The nice thing is that all of these pieces do tie together with really one question, which is what are the best ways to work with the most founders and help them the most? And the answer to that question, we try to plug and match both the companies and the venture funds. So, for example, if you're a founder and you have a tech business and you're growing quickly, maybe you use our wealth management transformation company to manage your money. Maybe you use Percepta to help you create your own mini model or inference or kind of improve your technology stack. Percepta can come in and really help with that. Maybe if you're in health care, you decide to sell into our hospital system in Ohio and be able to test out your technology. So the transformation companies that we build in house in GC are ultimately also helping our founders while delivering value for our... For the investors in GC. And same on the venture side. You know, not every founder has the perfect idea, and they're scaling. Some founders are second time founders thinking about their next thing. So with creation, we help give them the idea. We introduce them to their cofounder. We help them even before the capital formation. And on the other hand, if you're already growing really quickly and you want a way to scale without as much dilution, our customer value fund helps with that. So GC is doing a lot of things at once. We've hired incredible people for each transformation company, for each fund product. But ultimately, we now feel like if you're successfully growing and running a company, there are more ways to partner with GC than any other firm out there. And because of that, we're really seeing our brand rise. We're seeing, you know, the founders we back be extremely high quality and their companies do well because there are just so many more ways to plug in and work with GC than with an individual solo kind of venture fund.
00:06:18 · Molly O'Shea, Marc Bhargava
[00:06:18] S1: With your focus on the creation side of things, how much have you allocated to creation? [00:06:23] S0: In our last fund cycle, we put up to work about 1,000,000,000.5 on the creation strategy. And first and foremost, it's really around incubating companies. So we think there's a ton of potential right now, especially to incubate applied AI companies. So as the models get better, whether it's OpenAI or Anthropic or Google or xAI or others, we really do think there'll be a lot of new companies that can be built on top of this technology. And every three to six months, the models are getting better and better, especially recently at things like reasoning, logic, coding, math. And so we think there's a huge opportunity on creation to incubate Applied AI companies. And when we do that, we go one of two ways. Either we incubate the Applied AI company and we have it scale organically and then we give them capital for marketing and growth, or in about half the cases after incubating an Applied AI company, we actually give them capital to go buy their distribution, buy their client list, and the data that comes there. And so that second part has begun to be called the AI enabled roll up. And obviously, we are extremely involved in companies like Long Lake, Eudia, Titan MSP, Beacon, Crescendo, and others who are kind of the leaders now in this field.