Venture Europe: Entrepreneurship | Technology | Venture Capital | Eu/Acc
00:20:30 · Chaz Englander, Calin Fabri
This is past productivity. This is revenue generating [00:20:34] S0: stuff, [00:20:34] S1: right, where you can get a lot more done. You've got a lot more ideas coming across your desk. And theoretically, you're kind of doing what humans are good at, you know, building relationships and selling and these sorts of things that, at least for now, AI is not going to do for you. [00:20:49] S0: That's incredible. I think it was the guy from Altimeter that said he's invested both in cloud and OpenAI. He said that up until now, let's say, when you look at market sizes, you look at software market size, but right now software doesn't eat only from the software market size, it actually eats from jobs to be done or actually jobs, you know, like analysts. Okay, how many analysts, how many associates can you replace or actually make them more productive, like to your point, and also you can increase speed. Think it's just like fascinating. I think this is how maybe you can argue that you can build a trillion dollar company, right? Because if you don't have this element, I think it's just very hard to argue because you would just look at the market size as it was in the past. I know that also you mentioned that you want to become a trillion dollar company. What do you think are the steps to get there?
00:21:51 · Chaz Englander
[00:21:51] S1: So first of all, let's talk about the elephant in the room is how do we feel about verticalized applications versus the labs, OpenEye, Anthropic and the others. Interestingly, in the last week, we've been in the process of working not just with those two, we work with all of them that are providing the front end models. And we're looking at kind of renegotiating our contracts for the year. And all of these contracts are kind of 8 figure type contracts, right? And I honestly couldn't tell you whether we're going to spend 20,000,000 with x or 20,000,000 with y and zero with one and zero with the other. I couldn't tell you, Right? If you actually just look at our evals over the last six months, it's three months with one and three months with the other and three months with one and three months with the other. Right? Now, we have the luxury that the second that a newer model is released, we programmatically no human intervention whatsoever. We're running evals at an agent level. The second that a model is better at doing that particular task, it could be the main agent doing tool calling, it could be an agent writing an SQL query, whatever it might be, it can swap that model out automatically. Right? And the thing is if you look at the sector that we work in, can any of our customers afford to have not the best product in the market for a three period? Well, clearly, the answer is like no. Right? Now I mentioned that because often when we talk about a trillion dollar opportunity here, people are like, where does that sit in the stack? Right? And, you know... But where is this heading? You know, for now, we talk about productivity. We're going to revenue generative. How far away are we from these types of products being able to predict the performance of companies, private and public, better than humans? Now clearly, with a human mandate, how far away are we from that? I'll give you an example.
00:23:51 · Calin Fabri
[00:23:51] S0: So you mean, like, how far away are we until you don't need a human in the loop to make the decision that you could invest and this goes automatically? Is that
00:24:02 · Chaz Englander
[00:24:02] S1: Exactly, right? But let's break that down a little bit. I think middle market private equity is, in our world, the best because their appetite to explore tools is high. They sit in a very low bar from a regulatory perspective so they can integrate and plug things in and really get the true value from these products very, very quickly. Many of our middle market privacy clients now have entirely AI generated pages in their IC memo and IC process. When I say it's still mandated by the human, so it's still based on what they care about as a firm. To your point, You know, you mentioned that fund, $250,000,000. You know, they're only gonna make seven investments. There's only these companies that are covered, etcetera. Right? So it's still mandated by the fund and what they care about and what they've seen historically, etcetera. But it's still the AI that's offering an opinion. Now interestingly, what we've noticed is for every quarter that goes by, those pages in that IC meeting are becoming more and more and more important. You know, if I look at Q3 last year, it was, oh, this is interesting. Yeah. It says the management team is slightly weak in this area because of x, y, zed. This person's actually gone through four jobs in the last eight years. Move on to the next thing. Mhmm. Now these are becoming more and more and more sophisticated based on real data that you can obviously track and trace. Where... Like, how far away is that world of, like, your... You know, if you're if you're on on buy side, you're receiving a SIM from an adviser, and boom, before you've even looked at it, you've got your member exactly with the things that you care about. How far away are we from that and then how far away are from that AI sort of decision or indicator, let's call it, being like the most important indication in the room? I think a lot closer than people
00:25:53 · Calin Fabri, Chaz Englander
[00:25:53] S0: I I I just went to New York a couple of months ago, and I met this GP, and it's the first AI native fund. The only way that they make decisions is just they let the AI, you know. They have I don't know how many sources. Like how far away do you think we're going to be from the first PE fund that makes decisions just purely on AI? The humans there will just be on the relationships, investor relationships, but all the decision making is going to be by AI. [00:26:25] S1: I think about eighteen months. [00:26:27] S0: Eighteen months? [00:26:28] S1: Yeah. Wow. [00:26:32] S0: Also, talked with Steve from Feet. They led the round. He told me a bunch of questions that I should ask you. But I think the first one, and indeed I'm also curious, how come you guys decided to let them lead the round when, as everyone knows, you chose them over the elite of Silicon Valley?
00:26:59 · Chaz Englander
[00:26:59] S1: So this is an interesting one. It's an interesting topic. So first of all, when have a scale lawsuit and you have product market fit and you're going after clearly an enormous TAM, you're going to have acute competition. Right? Your only threat is competition, really. Right? You know, the way that we think about our business is if you have escape velocity, escape velocity, by way, I don't use that word lightly. Escape velocity is where twelve months ago, it was a risk to use Model ML. Now it's almost a risk in some cases to not use Model ML if you're working with all of their peers as an example. I'm not saying that's the case, but I am saying that that is what we define escape velocity as, right? So if you have those things, you have product market fit and escape velocity, what is your risk? Your risk is speed, right? Because in an AI world, you might have product market fit today, but you might wake up in the morning, you no longer have product market fit. So it all comes down to the speed at which you could move. Put bluntly, if you move faster than the competition, you will win fact, right? So that really played in my mind, particularly as we're coming to this round, it was competitive, the business was moving in the right direction, etcetera. And as we looked at our stage, right, and what was still going to be possible in the future versus now, I spoke a lot with Steve and know, Steve is a force of nature and arguably the best, you know, certainly the best fintech investment banker, you know, that's ever existed. And Steve had done a lot of work in the market. Frankly, a lot of people were looking at Steve as like, okay, tool is the out there from a verticalized perspective? And, you know, I sat with Steve and he gets it, know, Steve himself, remember, he's an entrepreneur, right? So he got it. And I think we made the decision on the basis that, you know, we're going to need every ounce of help we can get because Arne and I, we're not planning to come second. Know, I say team regularly, we have three outcomes, 1,000,000,000,000, dollars 100,000,000,000 and zero, and you have two choices, everyone better be choosing zero and $1,000,000,000,000 No one is choosing $100,000,000,000 We're not going to be sat there in twenty, thirty years' time saying, Yes, we made $100,000,000,000 company, but we came second. No one wants that, right?