The High Flyers Podcast with Vidit Agarwal
00:06:55 · Vidit Agarwal, John Willett
[00:06:55] S0: When I spoke to Gabe, who's your cofounder at Vrogon the other day, he said to me at Princeton, you would finish three hour exams in thirty minutes. I don't know if he was joking. Like, is that true? [00:07:05] S1: That's a funny... That's an interesting perspective on it. No. I mean, I may be very... I would have to be very confident in it because there were two kind of competing forces. One is, like, my... I was good at school, like, almost everyone at Princeton, so that was one force. And then the other force is my sort of like Irish Catholic upbringing, which causes me to constantly be paranoid and the kind of second guess and things are gonna go wrong. And so like, feel like just as often as that would happen, I would, you know, maybe finish it in twenty minutes and then spend two hours and forty minutes, like, reading over every single answer to make sure it's right. And I probably have that conflicting Jekyll Hyde personality at Rogo at times as well. [00:07:43] S0: I mean, the exact quote he actually said is he said, John is one of the highest IQ people I've met and a standard deviation above people I've met. He was always that boy. [00:07:52] S1: Did he say always that boy? [00:07:55] S0: He literally gave me that... We had a call and he gave me that line and he said he can quote me and that was the exact line he said. [00:08:01] S1: That's so funny. That And [00:08:03] S0: I'm like, did that form... Like, clearly, he's a big fan of few, which is great. Like, that's
00:08:03 · Vidit Agarwal, John Willett
[00:08:03] S0: I'm like, did that form... Like, clearly, he's a big fan of few, which is great. Like, that's [00:08:08] S1: I think he's... He's being very generous and very kind. Gabe is Gabe is an extremely smart guy. Yeah. I mean, I mean, yeah, again, growing up I was a huge nerd. I mean, I like... But I wasn't publicly so. Like I always... I didn't really like like it about myself, would say. Like I literally... I remember in, I think it was sixth grade or something. So I was like 12 years old, 11, 12 years old. [00:08:28] S0: I mean, how did that shape your aspirations when you were just about to finish high school? So if I met you at age 18, what would I have assumed you'd do with your life? I think like this [00:08:39] S1: generic sort of like business or finance. Like I was so... Maybe I was book smart, but I was not good at the kind of extra mile, like getting to know the career paths ahead of me or or like networking or, you know, really knowing the topography of these different areas within finance. So I'm probably generic would have been would have been like, yeah, I'll be like a CFO or maybe a CEO of some company and having zero idea what that meant, zero concept of, like, the path towards that zero concept of, like, what industry that would be. So, like, generically, was like, okay. Economics is probably a reasonable first step towards towards that. So that was kind of the random walk that I was on at that time. [00:09:19] S0: And it sounds like engineering was not a family influence.
00:09:19 · Vidit Agarwal, John Willett
[00:09:19] S0: And it sounds like engineering was not a family influence. [00:09:22] S1: No. I mean, I took my first coding class. I only took sophomore my second year of university at the... Right at the end. I was late to the game, and I quickly realized I'm like, prefer this by a lot to economics and wish that I had done it the whole time. [00:09:34] S0: I know you met Gabe at Princeton. Was that pretty early on? Like, maybe tell us the story of how you met him at Princeton. [00:09:39] S1: Yeah. I mean, we... Princeton's not that big, so we definitely knew each other a bit just from the first few months. We started getting closer kind of maybe halfway through halfway through college, and it was just a bit like... I mean Gabe's also a big nerd and so we would just take some of these random like linear algebra or like stochastic systems classes together and I feel like of the people who were going out and getting drunk on a Tuesday like of that group, which is not a big group at Princeton. Gabe and I were, like, the nerdiest of that group. And so we sort of, like, naturally became close through that. [00:10:10] S0: Do you remember your first impressions? Like, I I told you how Gabe described you when I spoke to him the other day. How would you describe Gabe when you first met him? [00:10:18] S1: So confident. Like, so much just sense of presence, sense of self. Super funny. I mean, out the gate, just, like, hilarious. But not, like, warm and fuzzy. He was a little bit intimidating when I first met him, but always just, yeah, super smart and sharp and and hilarious.
00:10:18 · John Willett, Vidit Agarwal
[00:10:18] S1: So confident. Like, so much just sense of presence, sense of self. Super funny. I mean, out the gate, just, like, hilarious. But not, like, warm and fuzzy. He was a little bit intimidating when I first met him, but always just, yeah, super smart and sharp and and hilarious. [00:10:34] S0: So how did you break in? How did you go from that to becoming friends and then starting companies? Right?
00:10:40 · John Willett
[00:10:40] S1: I think it was classes that we took together. I'm blanking on what the first couple ones were, and then, yeah, we ended up in in some of the same kinda, like, social clubs within Princeton. And then, I mean, the company thing, we did a little bit of independent research together when we were seniors in college. Well, really the story there was... So Gabe had taken some natural language processing classes and we started kind of chatting about it or, you know, junior years. And I had just finished my, like, junior paper for economics. And one thing we just kept talking about is there were all these people in the economics department at Princeton who, like, smart, but they're not technical or they're not... They don't know how to program. And the weird thing about these independent research projects was that you might spend like two weeks coming up with like a topic like, okay, I'm gonna do like an instrumental variable study on this and this. And then like, there's a bit of like collecting the data. And then a lot of it is just literally like writing the bar code or the Python code to like cleanly do the analysis, clean the data and do the outputs. And so it felt like 80% of the work that went into these financial or economic studies were things that the people weren't good at. Like, hated it. They'd like figuring it out from scratch. And anytime you see something like that, it just sticks out. Right? Like, this is a weird dislocation of resources. So we started looking at... Mean, I LLMs were around, but they weren't like that good and there wasn't like an API you could like ping to get like a good, you know, LLM response. And so a lot of it was kind of these more anachronistic grammar based approaches. And we were pretty impressed with a rule set that's not so crazy. You could take pretty open ended strings of text and convert that into more like deterministic like code runs. That was basically the the insight, which wasn't like a novel insight by any stretch of the imagination, but we were really interested in it. So kind of the idea that we set for the next year was like, okay. What if we can, like, build kind of a product that allows you to, as an economic student, just kind of describe what you want, say, hey. Here's this big clunky dataset. Can you remove the outliers and get rid of parts of the data that clearly are mislabeled?
00:12:41 · John Willett, Vidit Agarwal
Like, those sorts of things. Like, do the cleaning, do some of the exploratory analysis, and and then do the outputs. Just describe that and then the system could sort of piece together like a Python script to do that analysis. Again, like, this is all stuff that within a day of GBD three coming out would have looked so horrible, like did not work that well. But for the time, felt like it was gonna be helpful. So we spent a lot of time building that after our senior year, we had a few months before we started our, like, investment banking jobs, and we did talk a little bit about, should we try, like, commercializing this? [00:13:13] S0: Was it called Vogo? [00:13:14] S1: This was No. This was before... So we... The original product we called Athena, which is just, the most cliche possible, like, technology name. Like, every single product is called Athena. So from the jump, there was no way from a legal or branding perspective that that was that that was gonna work. But at the time, yeah. [00:13:30] S0: Was that... How different was that to the first Vrgo product that you eventually went with?