The High Flyers Podcast with Vidit Agarwal
00:13:30 · Vidit Agarwal, John Willett
[00:13:30] S0: Was that... How different was that to the first Vrgo product that you eventually went with? [00:13:35] S1: Quite different. Quite different. Because the first one didn't incorporate LLMs at all. It was all like uploaded data and it was all like... It was more structured data. It was kind of like, oh, like I have these CSVs or like there's this like dataset I'm integrating with and you would do basically just like structured analysis on top of that. Whereas the first kind of versions of Rogo, we're actually much more like we're plugged into all the like market data and like company fundamentals and company financials and you can ask a question and it would basically just pull those public pieces of information. This was still like Faxat and S and P Global and LSEG still were not picking up the phone. So it all these like random like Databento, like these random third party market data providers that no one in investment banking would ever use or trust, but it was sort of more of a proof of concept. And then the first product was also like a command line interface. So it left a lot to be desired in terms of UI UX to say the least. [00:14:28] S0: It's interesting because when people think of Rogo today in August 2026, people think of Gen AI. Right? Yeah. Back then in 2019, like you said, was pre ChatGPT going mainstream, and it was pre AI disrupting software in general. Yeah. So I'm curious now with the benefit of hindsight when you reflect on that moment in 2019. I guess, what did you know and, like, what did you maybe misunderstand?
00:14:50 · John Willett
[00:14:50] S1: The latter category is much more than than the former. I mean, we, like, we had, like, vaguely an idea that this stuff was cool. Like, that... I think that's probably the extent of our knowledge. There was maybe also a vague sense of, like, this stuff is both cool and getting better. And there was some concept of like Moore's Law and it was all very vague. We were like, okay, maybe this stuff will get better. Had no idea of the timelines or where things were gonna end up. And to give you a sense, it's like we started our banking jobs. We did kind of somewhat quickly where we're like, you know what? We do think this stuff could be applicable to our like front office banking jobs. I'm spending my entire day pulling data from FactSet and then from Cap IQ, PitchBook, Crunchbase, Dow Jones, all these different data sources. And so it felt like some of what we had built could apply, but we had basically no urgency whatsoever to start the company. Like we were like, oh, maybe we'll do, you know, in five to ten years, we'll pool some capital and bootstrap this or start working on it at some point, which I think is a pretty good indication. Like, if we were smarter and really knew where the research was and and knew where things were going, we obviously would have just quit our jobs and started the company immediately. The reason we ended up doing that was our first investor was this guy Kevin Ryan who founded, yeah, MongoDB and Business Insider. And, he's kind of one of the best early stage investors certainly in New York. And he recognized it, I think, little bit before us, and and we were talking about what we were doing. We were like, hey, maybe we'll apply to like Y Combinator at some point. He was like, no, don't. I'll just give you $2,000,000. You should quit your jobs now and start the company. This thing's gonna move a lot faster than you think. So that made it a lot a lot easier and he he Wait. Helped
00:16:25 · Vidit Agarwal, John Willett
[00:16:25] S0: Can you connect those dots? Because by then you had already graduated from Princeton. Right? [00:16:29] S1: Yeah. Yeah. So this was like a year and a half into investment banking or something like that. [00:16:33] S0: And so you were doing this on the like weekends and nights? [00:16:35] S1: Yeah. Basically we're doing a little bit of... I mean, so like at this point, not that much of it was like actual company building. Like we, we were working like eighty, ninety hour weeks in banking. So there was very little like product or like selling. Like we were maybe like doing small user interviews and stuff, but very little. It was much more by the end, like kind of figuring out, like, defining the vision for what we wanted to build and actually putting together, like, a pitch deck, which seemed like a a very important exercise at the time to have a really long and comprehensive... Look, it was such a good investment banking style pitch deck of just, like, so detailed about all of our all of our thoughts. [00:17:09] S0: I I was gonna say exactly that when I spoke to your investors, they said that's the difference in like your board decks compared to other portfolio companies is that both of you worked in iBanking. So your Yeah. Like decks are like very like iBanking style. [00:17:21] S1: Oh, that's so... Because I would have thought that like now we've gotten away from that. So if they still think that, that you guys should see this first one. It was horrific. It was also... Like [00:17:30] S0: some founders write memos. Right? Was I think you guys still do decks?
00:17:30 · Vidit Agarwal, John Willett
[00:17:30] S0: some founders write memos. Right? Was I think you guys still do decks? [00:17:33] S1: Yeah. We... We've we've experimented. I think our series a was a memo. We've experimented with both. Honestly, I I do like the memo. But the first deck, what's so funny about it, this is more of an aside, but but we were looking at it like a couple months ago. It's like we were... I don't think either of us had ever like seed a fundraising deck before. So it was all like from first principles, like zero clue of like how it should look. And we had like our like next twenty four months plan. And like typically when you look at a founder deck, it's like in three months, we're gonna be at like a 100,000,000 of ARR and then we're gonna like take over, then we're gonna start in Europe and then like... And just like this world domination plan that's like very grandiose. We were like so insecure and just we're like, yeah, this probably won't work. So like first six months, like ideation and then like hire an engineer. And then like twelve months later, like launch our first product. And it was literally like by the end of two years, we projected like a 100 k of ARR or something like that, which like hilariously ended up being accurate. But just because we were so not confident, it's actually... It's so funny. We'll have to... At some point if we IPO, we'll release that deck alongside it and it'll give everyone a a good laugh. [00:18:39] S0: Feel like you can do now. Like, you've got enough runs on the board to share that now. Like
00:18:39 · Vidit Agarwal, John Willett
[00:18:39] S0: Feel like you can do now. Like, you've got enough runs on the board to share that now. Like [00:18:43] S1: Yeah. Maybe maybe you're right. Yeah. Yeah. You're right. Should. [00:18:46] S0: I mean, but tell me on the on the Kevin Ryan point, because like you said, he built MongoDB. I mean, he's also done Business Insider, I think, and a bunch of other stuff. So clearly, he could say he understood software. Right? And he still understands it. What did he see in both of you and your, I guess, your MVP Yeah. In viral product in 2019 that gave him confidence to give you 2,000,000?
00:19:05 · John Willett
[00:19:05] S1: I think Kevin probably recognized a bit about... I'm sure he'd followed what was happening at OpenAI and and Google and had probably had some preexisting thesis on on language models and where things were moving, and I'm sure that existed somewhere in his brain. And then he just loves first time founders. That's a big thing with him. Like, he, like, he loves a young talent and, like, giving them money and letting them and letting them kinda run wild. And, was... I don't know if I fully share that thesis, but it worked out incredibly well for us. And Kevin's rationale for that, my understanding is, you know, he was the CEO of DoubleClick, which was one of the early kind of Internet ads companies sold to Google and he ran it incredibly well. And he's like, dude, like, if DoubleClick was like my third company, I would not have been nearly as good because I wouldn't have been as paranoid. I wouldn't have been up all night thinking about it. I wouldn't have been just as much of a freak about it as I was. So he likes the first time founder, like no points on the board, leaving nothing to chance, which like to be fair definitely is our personality, so I see that. So I think for him, it was probably more the calculus of interesting market backdrop of language models. First time founders, I like them, and these guys pass some bar there of drive and whatever. And then probably the bare bones, like, worked in banking. They're gonna start something to attack banking. That's often a pretty successful or interesting idea. So if I had to guess, those were kind of the three legs of the stool.