Generative Now | AI Builders on Creating the Future
00:19:25 · Gabe Stengel
[00:19:25] S1: There were two core things. One was changing our focus from just structured data to structured and unstructured data. So from, because the original product was like was econometrics on structured data, that's what we pitched. Right? It was, hey, make a chart of revenue multiples. You know, create a scatter plot of this versus that. And we weren't taking advantage of what LLMs are best at and most magical with, which is unstructured data. And we were too stubborn before, you know, opening the aperture. The second thing was I just changed the way we were pitching the product. I mean, distinctly remember being on a call with a large private equity firm and it going, you know, the product demo going better than I'd seen a product demo go in a while, in part because we'd added this unstructured data lens. And they asked for pricing. And I was like, well, firms this big never ask for pricing. They normally like race to get off the call. Right. Of course. And so I have no sense of what to charge. And so I took, you know, ten seconds in my head and thought, okay, you know, I'm gonna, let's push the full court advantage here, dollars 2,000,000 a year, right? Just pull a number out of thin air. And they go, okay, makes sense. And as soon as I got off that call, I called my co founder and I said, hey, you know, this firm didn't laugh at that number. This, we might be onto something. You know, if someone hears $2,000,000 a year and goes, oh, that, you know, that could make sense. It means you're pitching something that they think is very valuable. And so it was those two moments changing how we were pitching and what we were building that really started to unlock customer traction.
00:20:51 · Mike Mignano, Gabe Stengel
[00:20:51] S0: The unstructured data. I mean, I think that makes sense. I mean, you're seeing this in a lot of products right now where not just the use case of it and the value it provides to be able to just like throw a bunch of stuff into the model and have it come back at you with something structured. But also just like the time to you spend building an architecture and a database structure and like the old way of doing it, I would say. Like the amount of time and cost that must save your startup is insane. And we see this at a lot of startups. [00:21:19] S1: Yeah. No, I mean, to query structured data well with an LLM, you still need a, you know, a beautiful database that's documented well with data dictionaries. To query unstructured data well, I mean, you need some elastic search indices and like a, you know, smart keyword search prompts. [00:21:34] S0: And a big context window. And like, [00:21:36] S1: you know, just like throw it in there. Yeah, exactly. When you're [00:21:39] S0: talking to this big firm and you're like $2,000,000, clearly that's a big contract, especially given your stage. [00:21:46] S1: Didn't end up being $2,000,000, I will say. But I'm glad it was tethered, anchored to that as a starting point. For sure, for sure.
00:21:46 · Gabe Stengel, Mike Mignano
[00:21:46] S1: Didn't end up being $2,000,000, I will say. But I'm glad it was tethered, anchored to that as a starting point. For sure, for sure. [00:21:53] S0: You know, I'm guessing what, you know, what they start to think and customers at their scale must think is, okay, obviously, this product has value such that we're considering paying for it, but it also better have things like rock solid security, encryption, all this stuff that you associate with big robust financial tools. And at the time, you're a small startup. You're investing in features and moving quickly. How much are you thinking about that enterprise grade stuff at the same time?
00:22:20 · Gabe Stengel, Mike Mignano
[00:22:20] S1: So we, I mean, we were forced to think about it early on by the nature of our customer set, right? Like we were forced to think about what it meant to be multi cloud, what it meant to deploy on prem, what it meant to actually have these enterprise grade, you know, permissioning systems and RBAC systems and governance systems. And so we, I mean, we had to do that much earlier than a startup would in a typical life cycle. And it slows you down, right? Like, it takes attention away from feature velocity and into enterprise stuff, but it's a prerequisite for us. And I think it was also a mindset thing, right? Like we didn't think of security as a side dish and the main dish being the product. We thought of security as one of the main value propositions about what we were building. And so if you treat it like that, you know, you treat it like the product, right? And it's not, oh, we have to build out this enterprise permissioning system. It's, oh, this is a feature. Like this is something our clients want and is just as part, just as, you know, much a part of our product market fit as, you know, the way that we respond to user questions Yeah. [00:23:15] S0: Got it. Makes sense. Did you have that capability on your team? Like how do you go about solving for that? I mean, are you hiring CISO? And yeah, tell us about it.
00:23:15 · Mike Mignano, Gabe Stengel
[00:23:15] S0: Got it. Makes sense. Did you have that capability on your team? Like how do you go about solving for that? I mean, are you hiring CISO? And yeah, tell us about it. [00:23:25] S1: You figure it out. I mean, it's like all of these things. You trial by fire. Can you execute? Bring in the expertise where necessary. Otherwise, you know, like a lot of engineering problems, you can think about them from first principles and there's a lot of resources. And you can, you know, work with your partners and stakeholders to solve them. [00:23:43] S0: But it's interesting. Like you said, it slows you down. And the name of the game, it feels like right now for all AI startups is speed. I mean, we even talked about it early on. In order for a company like Rogo to succeed, you've gotta race far enough ahead of the model providers before they decide that finance is actually a vertical they care about. How do you balance that? How do you move fast in a world where the cost of moving fast and making a mistake in your industry is really, really high? [00:24:13] S1: I mean, we move slower than if we were a consumer company, for sure, from a feature perspective. Like you just have to. I mean, it's a sort of a, you know, threading the needle constantly and thinking about trade offs constantly and allocating as much bandwidth as you can to all your problems at the same time and just staying disciplined. There's no, you know, there's no silver bullet for execution. It's execution.
00:24:13 · Gabe Stengel, Mike Mignano
[00:24:13] S1: I mean, we move slower than if we were a consumer company, for sure, from a feature perspective. Like you just have to. I mean, it's a sort of a, you know, threading the needle constantly and thinking about trade offs constantly and allocating as much bandwidth as you can to all your problems at the same time and just staying disciplined. There's no, you know, there's no silver bullet for execution. It's execution. [00:24:36] S0: Yeah, totally. It's tough. I mean, it's crazy the pace of innovation and shipping you're seeing from startups right now. And it seems like it's just by necessity, right?