The Exchanges, every show

Q So maybe to kind of clarify, like, we just had Shahar from Terra Security on here. They're kind of like AI pen testing sort of thing, right? At least that's how I understood it. Is that, would that be similar to what you do, or not so much?

A Uh, yeah, we do a lot of that. We, we view like automated penetration testing as like a use case of our platform. And generally what happens when you have companies that focus on that single use case, they're probably going to make something that's more broadly and widely applicable. Maybe it does like a better job at certain compliance things. You can offer it to like SMB and lower size customers. It's very PLG friendly. We are Building something more big and interconnected. So although there might be capability overlap, there's probably practically like no customer overlap. We're targeting Fortune 500 USG, which includes Department of War and like the federal government and state government. And they require something that's a little bit bigger, more intense, a little bit more trustworthy and something that is more cross-functional in nature. So on the surface, probably competitive, but like practically no. And we think that there's a big enough market to support both

AI assessment note: “So on the surface, probably competitive, but like practically no.”

Q How did you raise from A-sixteen? Like, what was that process like for the first round?

A So my other co-founder, Dan, who runs most of our work with investors and also like our commercial business, he left Palantir in 20, 22 and had been warming up certain relationships like a year plus in advance. And so he did a lot of the groundwork that allowed us to go like very quickly. The Palantir alumni network and mafia network also was very advantageous because You know, folks want to support ex-Palantir founders. There's a lot of former Palantirians that are at some of these investment firms, like Michelle Volz was an example. She was at A-sixteen-Z, former Palantirian, and was kind of our first connection there. He was building a relationship with A-sixteen-Z prior to that, like, three-day process, and that allowed, like, Dan to get to know and trust some of the GPs there that would later on go to support us, so we weren't going into it cold. And we knew obviously for what we're doing, which is at the intersection of AI, security, defense, infrastructure, there's really no better first partner there because they just have such a network and system across those different fronts. So they were at our top of our list. When it came together, it just happened quickly. But we put in, Dan especially put in a lot of like work beforehand to build relationships to make that happen.

AI assessment note: “Michelle Volz was an example. She was at A-sixteen-Z, former Palantirian, and was kind of our first connection”

Q What were you doing right before you started the startup method?

A I worked for a more traditional security software company, and my intent, I was VP of product. It was a detection response company, and I helped them go from series A to series C. And that was just a fantastic process to see more traditional security distribution products. Like Palantir was not the right model to try to copy in that regard. Um, you know, being a government operator doesn't teach you how to distribute and build, you know, like a sales business. And that's what I really learned there. Global Salesforce, global team, you know, figuring out two tier, like distribution models, things like that, and those reps were super important to thinking about building and running method today.

AI assessment note: “I worked for a more traditional security software company... I was VP of product.”

Q How long did you have that, like, dark built period for?

A Uh, longer than I think any of us would have liked. I think six months in, we had our first design partnerships. Some of those were Fortune 500 customers. They were, like, naturally more early adopter innovator types so that they, like, knew what they were dealing with, but It was hard for them to like totally see and feel the vision, if that makes sense. But I would say like most of 20, 24 probably felt like in that darker period where we maintained our conviction that we're going to build a cross-functional platform so that you can basically attack and defend in a single experience. And that just took more than a year to fully build. So I would say like that whole time was kind of more of that darker conviction, like type building, even though we had design partners.

AI assessment note: “most of 20, 24 probably felt like in that darker period”

Q And is it generally that quick? Because that's a crazy short sales cycle for enterprise.

A Well, to get to that bootcamp, yes, is not easy. And even to go from successful technical bootcamp to then, like, either contract or more committed large pilot is also not easy. To get to the bootcamp, you need to, like, meet the buyers, any, like, technical middle management, and then you do align schedules, and it's an enterprise nightmare often. And then even when you get the bootcamp, then you're looking at Procurement, oftentimes, just to do like a pilot, you need to get like waivers for interacting with some of their data in a certain way, and there's a lot of things programmatically to like knock down. We're, we do not look and feel like a PLG company. We're selling pretty big contracts with big customers.

AI assessment note: “to get to that bootcamp, yes, is not easy”

Q Perfect. Well, let me stop it there and ask the three questions we always end on. When was the time that you felt like you'd found true product market fit?

A Product market fit for, like, an enterprise Motion like we're doing. It's, it's really different than like a PLG style, like where you can just look at like crap, like people are just using this thing for us. I think there's a couple of things we met with a certain customer that did a ton of market research into all potential solutions that were in kind of the offensive security space, which is a space that we play a lot in. And they went from market research to Deciding to choose method in such a rapid timeframe on a dollar amount that was like unprecedented for us. This happened to be a government customer. And that timeframe was just like so remarkably tight that I knew like, okay, this team could have anything and they chose us and they chose us very quickly. It's like that specific feeling was like part of product market fit. And then the The other one that's maybe more classic, like product focus is that we started to have recurring usage of like certain types of user groups after we were just grinding with them over and over again, which is more classic marker. But honestly, I, I feel both sides, but when those connect on the same customer, then it's like we've got lightning in the bottle.

AI assessment note: “we met with a certain customer that did a ton of market research”