00:21:37 · David Senra, Nik Storonsky
[00:21:37] S0: 1,000,000 GP, 2,000,000 GP, 3,000,000 GP [00:21:40] S1: each month consecutively. And then if we release a bet and then we see that this bet is historically in cohort of bottom 25% of all the bets, we simply sunset it. So we instill discipline when we're not really running businesses which are not growing very fast. And then bets which are growing very fast, we're actually doubling down. Right? So we knew the more teams, one team becomes second team, three teams, four teams, five teams, and becomes department, and becomes a major pin and alliance. So I think this process is just very disciplined to always filter out things that don't work out. Even myself, kind of, you know, I don't really trust my intuition in terms of which products to build, which products not to build, because historically, I was wrong so many times. And I think only approach which, like, completely algorithmic. Right? Top bets, you've continued to fund. Bottom bets, you just cut, like, within eighteen months. [00:22:34] S0: This is the trader in you. [00:22:35] S1: Exactly. [00:22:36] S0: There's lot of what you're saying reminds me of Bezos. And the way he describes this, these, like, obviously, these disparate bets that he would place inside of Amazon when he was obviously building the company. And he has a great line where he's like, you need to pour gasoline on the promising sparks. So your whole is I'm going to cut the bottom, but then the top performing, do you have a percentage? Is it 10%? Top? It's usually up to 25% [00:22:56] S1: of all of this.
00:22:56 · Nik Storonsky, David Senra
[00:22:56] S1: of all of this. [00:22:56] S0: Okay, then you're just now we know We [00:22:58] S1: just scale it up. [00:22:59] S0: Okay. And you're dedicating a lot more money and resources. Why is it important at the very beginning before it's unproven to to cap the team size of 10? [00:23:06] S1: It's not necessarily 10. It can be a bit more. It just depends how complex is the product, but it should not be more... Generally, it should not be more than 10 people. I guess, as a rule of thumb, okay, need probably two, three back end developers. You need to... In our case, because we also produce mobile apps, you need to have two to four front end developers. So three to four back end developers, one pro... Owner, one designer. That gives you 10 people. [00:23:31] S0: Is the way you're structuring these teams changing because of AI now? Yes. That's actually [00:23:37] S1: a thing now that I'm kind of trying to change. Because last ten years, I think I optimized a lot how you direct people, how you build organization around people, around their strengths and weaknesses. Like, avoiding politics, putting KPIs, and so on. That's actually avoiding people's weaknesses, right, with AI. Structure needs to be a result, to be honest here. I think the team should not be 10 people anymore. It should be two people, three people at best. Because of one one developer can do front end, back end. Can they even do, you know, data science as well? So it should be a result. Can you give
00:23:37 · Nik Storonsky, David Senra
[00:23:37] S1: a thing now that I'm kind of trying to change. Because last ten years, I think I optimized a lot how you direct people, how you build organization around people, around their strengths and weaknesses. Like, avoiding politics, putting KPIs, and so on. That's actually avoiding people's weaknesses, right, with AI. Structure needs to be a result, to be honest here. I think the team should not be 10 people anymore. It should be two people, three people at best. Because of one one developer can do front end, back end. Can they even do, you know, data science as well? So it should be a result. Can you give [00:24:13] S0: me a download of your thoughts about how AI is changing the way that you're running your company?
00:24:13 · David Senra, Nik Storonsky
[00:24:13] S0: me a download of your thoughts about how AI is changing the way that you're running your company? [00:24:18] S1: Well, many things, Anders. I think we're just in the beginning. So, we automated customer support. So, 90% of all customer support team is automated now. We're doing the same. Before it used to be 5,000 people plus, now it's much less. Obviously, is automated as well. We increased the speed of engineers by 30%. Translation, cross selling as well done by LLMs now. A lot of things. But I think ultimate goal is... Or least a bet for us now is to be able to build like full stack AI employee. I think it's completely doable with our current technology. So it's it's not like a chat tool or another like interface where we tell what to do and then it it produces something. No. It's it's more like AI employee, which can join calls with you, which have email, which have Slack account, which have access to all internal back office system and can do work. So I think that's kind of their their ultimate goal that... I mean, sooner or later, you know, majority of companies will come to.
00:24:18 · Nik Storonsky, David Senra
[00:24:18] S1: Well, many things, Anders. I think we're just in the beginning. So, we automated customer support. So, 90% of all customer support team is automated now. We're doing the same. Before it used to be 5,000 people plus, now it's much less. Obviously, is automated as well. We increased the speed of engineers by 30%. Translation, cross selling as well done by LLMs now. A lot of things. But I think ultimate goal is... Or least a bet for us now is to be able to build like full stack AI employee. I think it's completely doable with our current technology. So it's it's not like a chat tool or another like interface where we tell what to do and then it it produces something. No. It's it's more like AI employee, which can join calls with you, which have email, which have Slack account, which have access to all internal back office system and can do work. So I think that's kind of their their ultimate goal that... I mean, sooner or later, you know, majority of companies will come to. [00:25:23] S0: Yeah. You keep mentioning over and over again, like, I don't know if you use the word bureaucracy. I don't think you did, but like, you you hate politics. You wanna minimize that. You want like data. You're much more like just, I don't care what you say. It's like, did we hit the numbers or not? And is this growing or not? What's your organizational structure? Do you just have a shitload of direct reports? Like Alexander Wang was sitting in that chair like two weeks ago, and he has some crazy shit, like 200 direct reports. [00:25:45] S1: Oh, really? Yeah.
00:25:45 · Nik Storonsky, David Senra
[00:25:45] S1: Oh, really? Yeah. [00:25:46] S0: So like, what's your... How how are you organized? [00:25:48] S1: So I have about 50, 51, 52. Reality, I'm not even gonna speak... Well, I I speak with my direct reports, but I also go deeper. Right? I I go down to individual contributor in in important projects. So I can speak directly with design or product owner, with developer. Philosophy is very simple. Right? So whenever you hire smart self guided people, you don't really need to manage them. So you just need to show them direction and then ensure that they're all synchronized. So it's like an army. Right? So you need to ensure that all people are using the same standardized equipment. Right? That's what you need in the company as well. You don't need their... Every single team or department to reinvent their own bicycles. Right? Or their own weapons. Now it has to be the same standard approach. And then if someone invents, you know, some additional kind of tool or additional instrument which allows us to move even faster, then we need to standardize it across all all the teams and departments. And that's what I I do very well. I'm I'm very good at spotting our innovation in one team or one department, and then actually spreading it across the whole company. [00:26:55] S0: Can you give me an example of you spotting an innovation and spreading it through the other departments?