Adam Liska on AI-Native GTM, Vibe Coding, and Revenue Execution

**Alex Theuma** (0:03)
Every decade or so, the rules of software change completely. This is one of those moments. The AI Revolution Show is the intelligence podcast for B2B software founders navigating the platform shift. The founders building through it, and the founders already on the other side.
I've known the team at Recap for years now, and I've watched a good number of their customers grow into something serious. When I talk about them here, it comes from actually seeing how this works. Something I'm noticing more and more is founders thinking carefully about their capital stack before they take on equity. Sometimes equity is the right fit. Sometimes debt makes more sense. When founders go the debt route, they tend to use it to fund growth, bridge to profitability, or hold off on an equity round until they can raise on better terms or without giving up a single share. That's what Recap does. They provide non-dilutive funding to growth companies across the UK, Germany, and the Netherlands, with tickets from 100K to 3 million. It's built for companies already earning real revenue. Their platform helps you work out how much funding and what kind would fit you best based on your actual financials and goals. So if funding is on your mind, head to recap.com, that's recap.com.
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All right. Adam, on the hottest day of the year in the UK, you're joining us on the podcast. Really do appreciate you coming over to the studio for this.

**Adam Liska** (1:40)
Yeah. No, thanks for having me. Fortunately, my office is just six minutes away, so it was easy.

**Alex Theuma** (1:45)
You walked it?

**Adam Liska** (1:45)
I walked, yeah.

**Alex Theuma** (1:46)
Okay. Very good. So it was a two-hour train journey for me. I was a little bit apprehensive that there would be some rescheduling needed in case the trains melted, but actually everything was fine.

**Adam Liska** (1:58)
I did have a few meetings actually moved today.

**Alex Theuma** (2:00)
Yeah.

**Adam Liska** (2:00)
Because of that, people didn't make it to the city.

**Alex Theuma** (2:01)
Well, I'm not coming into London.
I don't blame them, but we're dressed for the occasion, so we've got the summer vibes. But yeah, no, I appreciate you coming here. So Airspeed in a sentence, for those that don't know, what is it?

**Adam Liska** (2:14)
We're really focusing on revenue execution. So how can we make your go-to-market team execute faster, go from an idea or an intent to do something to doing it?

**Alex Theuma** (2:23)
And you and your co-founder, Devang, you came from DeepMind. So what was it that made you transition into AI GTM from DeepMind? What did you see there in your conversations? How did this come about?

**Adam Liska** (2:37)
Yeah, no, good question. And we get this one often, as you can imagine. Well, so Devang and I, we met at DeepMind. We're working on the Gemini team before it was called Gemini. But when we really scaled LNM training, training at DeepMind, I think we were really in a fortunate position to be contributing and seeing where AI is going. We left 2022, it feels like not that long ago, but it's funny looking back. Back then at Google, it wasn't really sure how quickly we're going to put this into product, how quickly we can iterate on it. And we knew the potential, we knew where things were going. We could see that AI went from being able to understand one, two sentences, to being able to understand a whole conversation and a whole suite of conversations.
And so we wanted to build it in the space, build with users and iterate fast.

**Alex Theuma** (3:24)
What was, did you see a gap? I guess how connected were you to sales and what was the gap that really you saw that said, okay, we've got to build this company now?

**Adam Liska** (3:35)
Yeah, so there's a gap and there's also a long-term kind of vision behind the company.
I might start with a gap where, especially GTM sales conversations, it's a lot of unstructured data that the team is connecting, but it's also data that's unique to your organization. Right now, all the public data analysis and everything that's been kind of commoditized, everyone can go and send a cloud agent to analyze Reddit posts or something like that and get that information. But it's really sales conversation and customer conversations where you're learning about what problems people come to you with. How do they view compared to the competition? How are they kind of solving those problems right now? And it's really data that should be driving most of the company's strategy. I think that's one thing. We wanted to take this data because most organizations were just sitting on this data, not doing really anything. We wanted to take this data, analyze it, make sense of it, and then turn it into action and make it kind of useful for the whole organization to both automate a lot of the toil and maybe simple workflows that they do, but also automate some of the more higher leverage workflows around setting product strategy, setting go to market strategy. We go into this vertical, into this geo, et cetera.