00:32:28 · Molly O'Shea, Gorkem Yurtseven
[00:32:28] S0: So, what are the key traits that you guys look for? You mentioned [00:32:33] S1: good Agency is one thing that we I talk about in the think everyone would want people with agency, but you just mentioned software engineers even making business decisions. I think it's unheard of in a big company like Amazon, Coinbase, whatever software engineers do software engineering. But because the market is moving so fast, the customers are, you know, emerging, changing between different models so fast that a lot of the times we want our software engineers to make business decisions or work with customers, therefore have to make business decisions around them. So that's the hardest type of engineer to find, and I think you look for agency. If you think this person can act independently, take responsibility and own the decisions, then the other things we want just comes naturally with it. Hard to test for it. I think the best way to know is if you worked with him before or her, that's the best way to know it. But that's something we care about a lot.
00:33:37 · Burkay Gür, Molly O'Shea
[00:33:37] S2: Yeah, I think we also look for maybe correlates a little bit, but, like, hunger, I think, is something that's, like, very, very important because, like, I think you need to be able to, like, really push in this market, like, to actually win. So, you have to, like, just really want to, you know, win and build a big company. So, we try to test for that, which is very hard to test, but I think, like, you can kind of get a sense when you, like, sit down and talk to a candidate. We do a little bit of, like, reverse selling. I think that helps maybe to identify hunger. Like, Hey, like, it's a lot of work. We don't, like, believe in I don't think we believe in, like, I don't know, toxic work hours or things like that. We go home during weekends, for example. [00:34:26] S0: Really? [00:34:27] S2: Yeah. What? Imagine that. [00:34:28] S0: This is the first I've heard [00:34:29] S2: of So, nothing to, I think, brag about. Like, to brag about [00:34:35] S0: You not going go home during weekends and you're still successful.
00:34:35 · Molly O'Shea, Burkay Gür
[00:34:35] S0: You not going go home during weekends and you're still successful. [00:34:39] S2: Yes, imagine. Crazy. I think, like, there is a certain baseline, I think, that we try to be realistic about, like, what to expect. And so, that's part of the reversal, I think. Hey, like, can be a lot of, like, time crunch, you know, like, you know, we really push and we have to spend a lot of time working and sixty hours and eighty hours. And I think that, like, filters out maybe, like, certain, you know, certain people. So, I think looking for hunger is very important. And then I think, like, culturally, I would say anyone, like, who interacted with our team, like, on the customer side, they would probably attest to this is like our team is like pretty low ego, like pretty easy to work with. I think we look for like humility in general. Like, they gotta be really talented but at the same time, like not be a jerk about it. I think that's like pretty unique to find. And I think like anyone who's interacted with, like, our team probably knows that and that's, I think, why they really like us. Like, people are really easy to work with and, like, really friendly. I think you can have both at the same time. So, we try to filter for humility as well. [00:35:58] S0: What have been the biggest surprise challenges that you guys have come across? And not just the standard stuff, but it could just be something you had no idea you were gonna expect.
00:35:58 · Molly O'Shea, Burkay Gür
[00:35:58] S0: What have been the biggest surprise challenges that you guys have come across? And not just the standard stuff, but it could just be something you had no idea you were gonna expect. [00:36:09] S2: I'd say, like, being at the forefront, like, as a company is pretty hard. I think, one, you have to really want it. Right? Like, you have to want to build a big company. And two, you have to, like, keep up with it, right, which requires a lot of effort. So, I think in order to, you know, build a big startup, you really have to just be very committed and be very hungry. And I think, like, that's, you know, that definitely, that's a lot of work. You know, that takes a toll on you. I think Adam would say this, probably. You know? But, yeah, it just requires a lot of hard work. [00:36:53] S0: I don't know. I asked him what he's most excited about. He says he doesn't feel excitement. [00:36:59] S2: He's beyond that point. [00:37:00] S0: You're going to get there one day. No emotions.
00:37:00 · Molly O'Shea, Gorkem Yurtseven
[00:37:00] S0: You're going to get there one day. No emotions. [00:37:04] S1: Our industry is incredibly dynamic, right? When there's no good model for a month, everyone starts panicking, oh my god it's been one month, nothing new has happened. But the answer is just wait another month and something incredible is going to happen. It's been true since we started and that keeps excitement going, and that keeps people very encouraged that, okay, there's going to be the next model that's going to unlock these other use cases, which is going to unlock these other types of customers, and that has brought so much growth to our business, and so far it just keeps happening for us. [00:37:42] S0: Where have you been seeing some of the best models come from? Do they just come out sporadically? Is there any consistent theme between all of them?
00:37:49 · Gorkem Yurtseven
[00:37:49] S1: So, now we play a bigger role in the ecosystem because we are an infrastructure partner for the model providers, but we are also the API partner for the application layer or studios, people who are consuming the models. So we got a good sense of supply on demand on both sides. And we are in such a compute constraint moment right now that if you are coming up with a new model you really have to plan ahead of time, you have to make sure you have enough compute to run inference. If you are successful, you are likely not going to be able to procure it on your own, so it's usually a good idea to partner up with an inference provider like us to do your launch. So we work very intimate with the model providers. And for customers, they usually use multiple models at the same time, but they really care about model releases because they usually tie their product releases with model releases as well. So we keep in very close communication with them as well. And then we have to sometimes anticipate how much growth is gonna come on the model side to procure our own compute. To maybe do some investment on our side to enable the whole space. And someone really has to do that because otherwise all the compute is going to go to coding agents or whoever is doing By the bigger planning ahead and investing on compute a little bit we can enable both the model providers and the applications being built on it. So that has become our responsibility in the ecosystem these couple months because compute is so hard to come by.