00:09:10 · Zeynep Yavuz-Willson
[00:09:10] S1: So, there are a number of them that I mentioned. And the other thing is that I would say, you know, doing this in The US and Europe is different. Yeah. But we've done a lot of the thesis work holistically as a team, so as a global team. And we've already mapped out those markets. So, property management is one, real estate is one, legal is one, and insurance, and within insurance, have MGAs, you have the TPAs, like the claims management, you've got BPOs. So, it goes really deep within insurance and the brokerage space. Then you have wealth, is also another category. And particularly, by the way, if you just like think about accounting, real estate, property management, wealth, insurance, these are not even in house functions necessarily. What I mean by that is that they're selling to SMEs, and they're selling to people. So, these industries will just continue to exist. They will never be fully disrupted with AI. People will be living in buildings. There will be property managers. People will be looking to rent, and people will need to file their taxes, and people will need to get insurance. And all of these are regulated industries, and that relationship that you have with the broker, that customer relationship actually is the key mode. So, what we try to do with the AI transformation work that we do is that how can we free up the time of the agents, the real people who work in these industries, so they can really focus on the relationship side? Because that is the mode. It's not the admin. You know, the admin needs to get done. That needs to be automated so that you can really focus on the relationship. And I think, by the way, that's really interesting is that we always are talking about or trying to understand, like, the moat in AI, And I think more and more people are realizing, like, even the moat in AI is that customer relationship, is the trust that you have with your customer. It ends up being kind of the only moat now that we see in AI. And like the challenge of AI, in my perspective, is not going to be a technological challenge in Europe. Obviously, AI is a technological challenge, and, you know, robotics, and there are different layers of it that needs to be still figured out, but the pace of acceleration on the tech side is happening incredibly fast. Yeah. We're not catching up with is more the change management piece.
00:11:31 · Zeynep Yavuz-Willson, Sebastian Johnson
So, the diffusion of AI, and how are people going to be using AI, and that's... I don't think that challenge is really solved, you can't move fast break things because we're working with real people. People need to adopt it. And that requires trust, word-of-mouth. And it might just not move at the same rate as, you know, some companies have been growing historically. [00:11:53] S0: So to go back to what you said maybe, like, a minute ago, you talked about how relationships is the moats. Yeah. What does that mean in reality for companies that are building technological products? So so having, you know Yeah. A front row seat to Legora's journey, are they using that moat to sort of grow quickly and maintain their base?
00:12:11 · Zeynep Yavuz-Willson
[00:12:11] S1: So, on Legora, mentioned, right, in the low fare market, it's a very tight knit community of people And the customer references you have is everything. I've done obviously a ton of reference calls on my customer calls that I go around, you know. And I'll meet someone, like I'll speak to a legal buyer at a law firm. I will not name it. In the reference call, he will say, you know, I bought this because, you know, I believe in Max. And I you know, kind people like Max will change the world. This is like an AI manager in a mid sized law firm. Yeah. And he's thinking like the person he's buying the technology from, and the team he's buying it from is going change the world. Yeah. So, that relationship that you establish people, that level of trust, you know, you make them feel that way, and then of course, after you sell the technology, they're, you know, the DAU, MAU numbers, so like the engagement is incredibly high. I think that's the mot. The level of engagement you have, the way you make your customers feel, you trust them, that's really the mot. And another example is Langdock, for example, another one of our portfolio companies where they have such strong word-of-mouth. And you can hire a massive sales team to, you know, nowadays, you know, and it is important, you know, the deployed engineering resources. These are important to like, new for the change, etcetera. But actually, word-of-mouth is if you can have that, that's so much more powerful because that scales.
00:13:44 · Sebastian Johnson, Zeynep Yavuz-Willson
[00:13:44] S0: Yeah, and that's really interesting. Then you're making this bet on the services and I guess on the end users and the applications in these companies. That's where you're thinking the value is going to be. Where do you think about the rest of the AI stack then? What's your view on, say, the model layer, open or closed source, the chips, the underlying technology, the hardware? You've made these bets sort of at the very... You talk about diffusion, and you talk about people actually using it and adopting it. That seems to be where you're taking your bet. That's where you think there's most of the value to be captured. What does that say... What are your views then on the rest of the stack and the the value that will ultimately be captured by the hardware players, Frontier Labs. [00:14:24] S1: I have some points of views, also watching very closely on how things change. [00:14:29] S0: So
00:14:29 · Sebastian Johnson, Zeynep Yavuz-Willson
[00:14:29] S0: So [00:14:30] S1: I focus on the applied AI layer, right? So I'm thinking more about how we can apply AI, how we can have the trust of the customer. I look at the engagement and how people are using the product. And I believe that relationship is the defensibility. But the rest of the stack is also important. I think open source is a big tailwind for a lot of these application layer companies. We're already seeing model companies move to the application layer, right? I mean, we all work cloud, we work on cloud. So, that is an application. That is how I engage with Anthropic. And I think that will continue to happen, but now the application layer players also have the opportunity to move down the open source layer, and there are a number of companies, I will not name them in our portfolio, outside of our portfolio, that since the December moment, where I would say the costs of AI have really significantly gone up, capabilities have gone up, but costs also have gone up, and open source, I think, is now there's more consensus around open source catching up with a time lag with a lot of the frontier models. A lot of them have a very active open source and moving to our own model strategy. So, don't think we can say yet, oh, open source, like open source is gonna make at wide AI, you know, have the moat and like things open source, it's all gonna work. All the companies that are building out the application layer have to be actively thinking about this today. If they're not thinking about it today, like, that's... I'd say that's a concern.
00:16:05 · Sebastian Johnson, Zeynep Yavuz-Willson
[00:16:05] S0: That has definitely been the most interesting situation in the last nine months, right? Nine months ago, it was like the frontier companies, the labs, they're coming for the application companies, right? Like Anthropic, they're going to come for all the application layer companies. They're going to do the legal use cases, the vibe coding, whatever. Now it's like, actually, these application companies are going to replace the providers of the models themselves with open source. [00:16:25] S1: Exactly. So what does it come down to then? It's about the customer relationship. It's about the trust. Actually, whoever has that engagement layer has, in a way, a leg up. As long as you have the same performance or better performance or same performance, but better trust, the the focus company that's in the application layer and the customer relationship should ultimately win. [00:16:45] S0: And is that true, do you think, for consumer facing applications as well, where there's less of a relationship but you've still got, I guess, like, brand and you've got... Relationship is a bit more ethereal than a one to one customer success relationship.