I guess, can you tell us what that means when you're evaluating these startups?

So, let's actually separate the conversation to subject matter expertise and then moat, because moat is like its whole big...

Absolutely.

Right? So...

I think subject matter expertise and being close to the customer and understanding the customer, and then obviously at the back of that, having a very significant market motion because you are part of the industry and you know people, then they believe in you.

I think that is more important in the cycle than in business.

Because in previous cycles, it was hard to build, right? You had to hire the right engineers, and it took time, and the better they are, the faster you get there, and the better experience, better product you have.

Is that something you think about? Or at this stage, it doesn't even matter right now?

I'm just kind of curious how you think about how your thinking is evolving regarding modes and data and what kind of data is really important.

So first of all, I love that you use the word evolving because everything is evolving super fast in venture and obviously in AI, which is what we're focused on.

So look, I'm going to try to, let's do the advanced part.

The basic part, everybody gets.

If you have proprietary data that you have and nobody else has, okay, that's obvious that you have an advantage.

And again, I think it's worth emphasizing that generative AI with the architecture today is, as most of the audience here probably knows, is a statistical model that enables us to build non-deterministic software, right? But And this is more like academic.

But if I give you an infinite amount of data that is applicable to the problem you're trying to solve with AI, you're going to get an AI that's 99.99999% to infinity.

I think there's a whole new wave of startups that are saying, we're going to replace the lawyer or go vertically integrated and go full stack.

If you could show us, Yeah.

Yeah, I'm happy to.

Okay.

Hello, Henry.

So as you can see, this is a production-grade system sitting on recursiveventures.com.

This is our domain, obviously.

It is obviously not accessible to the wide public.

Yeah,

Yeah.

And since then it has evolved into a full suite HR system that does everything you need to manage a workforce, remote, local, whatever.

I think the reason it was controversial at the time was, first of all, HR is kind of an unsexy space.

Uh, there were already several successful companies in the space, like Gusto and Rippling, and, like, Deel actually came afterwards.

The founder, Alex, was-- both founders, actually, Alex and Shu, were very, very young at the time, like 25, and they had zero experience and zero subject matter expertise in the world of HR systems and payments and remittance and compliance and all those things.

So something that you'd maybe expect more of a mature adult to be able to figure out because they know how HR works.

No, these guys didn't have that, right? And, uh, it was also, you know, they pivoted, like, once or twice before they, they figured it out.

And what are examples of founders you remember very well and that they had a strength that kinda outpaced the norm?

So curious to know what kind of AI automations have you already implemented?

Yeah.

So I think my case, our case is a very interesting case because we run a kind of a small boutique venture capital firm, obviously financial services.

And one thing that's interesting about venture capital is that traditionally it's been a partnership.

So there's been like a bunch of general partners all working together.

Each one is sort of a lone wolf, but then they get together as a pack to get scale and intelligence and deploy capital together.

But in a way, that's been a necessity of the past.

So how do you like as a founder, how do you go about this threat? Because you never know, you know?