The Twenty Minute VC (20VC): Venture Capital | Startup Funding | The Pitch
00:35:36 · Erik Bernhardsson, Harry Stebbings
[00:35:36] S0: It actually is like one of those products. I I think one of the benefits of being in infrastructure, but also one of the drawbacks in a weird way is, like, you kind of just have to trust your gut on, like, what are, like, important primitives and just build, like, amazing building blocks. I think we're in the space of, like, providing building blocks. We try to look at, like, what do engineers need and not, like, listen too carefully because, like, they'll ask for, like, all kinds of random stuff. Distill it down into like, what are some of the building blocks? And we put out a serverless function product in 2021. It saw success in 2023 with GenAI inference. We put out a sandbox product in 2023 because we saw a lot of people using LMS to generate code. And then it saw success in 2025, like I said. So a lot of like how we think about building products has always been kind of like, let's just put out like good building blocks. And then it exploded. But like to answer your question, it was reinforcement learning, it was vibe coding, background agents, and maybe some other stuff too in the future. Those were things we actually didn't anticipate. So I think infrastructure is often like that. Like we didn't anticipate stable fusion when we started building our serverless function product. It just happened to [00:36:38] S1: be the killer app. What's your takeaway from that? The only thing that matters is you've gotta stay in the game long enough for your timing to be right?
00:36:38 · Harry Stebbings, Erik Bernhardsson
[00:36:38] S1: be the killer app. What's your takeaway from that? The only thing that matters is you've gotta stay in the game long enough for your timing to be right? [00:36:46] S0: Sometimes, I think that's right. I mean, we've definitely been extremely lucky in certain ways with timing. Like we put out products like right before we started the company in 2021, and then Stable Diffusion and ChatGPT came out 2022. We had really good timing with that, right? It just created so much demand and we're very well positioned. But some of it is also like with infrastructure, like, again, like, I think it's about like building products that, you know, you anticipate will be useful in the future. And from your own experience are things that you always wanted to see. I think you have to kinda trust your gut in that. [00:37:13] S1: You said that about, you know, resource allocation and that being very, very important as you think about this breadth of products. Where did you allocate resources where with the benefit of hindsight you wish you hadn't, and how do you reflect on that?
00:37:13 · Harry Stebbings, Erik Bernhardsson
[00:37:13] S1: You said that about, you know, resource allocation and that being very, very important as you think about this breadth of products. Where did you allocate resources where with the benefit of hindsight you wish you hadn't, and how do you reflect on that? [00:37:24] S0: I think we should have allocated more resources towards LLM inference like earlier. I think we're a little bit on the sidelines for a while. We didn't realize how big open source inference would be, and we thought it would be kind of a race to the bottom, just a commodity space. And then DeepSeek came out, we're like, fuck. Like, we gotta move very fast. And so we staffed up a team immediately, you know, went from, like, you know, one or two people working on this to, like, 30 people twelve months later, and and now we're one of [00:37:48] S1: the top three providers. Jason Lemkin, a dear friend of mine who I do a show with every Thursday, he always says that now we've reached peak open source LLM inference usage. We're gonna see frontier providers bluntly provide incredibly cheap products that they are now. US enterprises don't wanna use Chinese models. That will continue. And so, actually, with those two core prevailing wins, Frontier will actually research, and we will see a reduction slash plateauing of the OS LLM inference model.
00:37:48 · Harry Stebbings, Erik Bernhardsson
[00:37:48] S1: the top three providers. Jason Lemkin, a dear friend of mine who I do a show with every Thursday, he always says that now we've reached peak open source LLM inference usage. We're gonna see frontier providers bluntly provide incredibly cheap products that they are now. US enterprises don't wanna use Chinese models. That will continue. And so, actually, with those two core prevailing wins, Frontier will actually research, and we will see a reduction slash plateauing of the OS LLM inference model. [00:38:17] S0: I think that's a little bit of a fixed pie size mental... Like, I I I think, you know, with with all due respect, I do think both spaces will grow five x, 10 x, 20 x over the next twelve months and and beyond. Like... And and so, like, it's hard to argue, like, you know, which one's gonna be bigger than the other, but I think both will grow, like, in, you know, orders of magnitude over the next few years. [00:38:35] S1: Five x, 10 x, 20 x over the next twelve months. [00:38:37] S0: Yeah. For sure. [00:38:38] S1: You just hit a billion in revenue. Yep. Well done. [00:38:40] S0: Yeah. Does that feel [00:38:41] S1: pretty cool? [00:38:42] S0: It feels pretty cool. It's, you know, like, I I don't know. Like, I'm just like, you know, Swedish guy that, you know, grew up in a random. For me, it's like these numbers are absurd, but like, yeah, it feels great. It's so much money. [00:38:54] S1: Erik, you're saying, do you know what? I wasn't expecting you to be so likable and cool.
00:38:54 · Harry Stebbings, Erik Bernhardsson
[00:38:54] S1: Erik, you're saying, do you know what? I wasn't expecting you to be so likable and cool. [00:38:59] S0: I don't know. It's like a lot of zeros. How many zeros are in a billion? [00:39:02] S1: It's a lot. Your wealth manager will tell you. When you look at that, where will you be in twelve months? [00:39:09] S0: I don't know. What I can say is we've been growing... We grew 15x in the last twelve months. So you can extrapolate that. I mean, I don't know. Like at some point we start... Markets just get very big and they start to slow down a little bit. But with the growth rate right now, like the growth rates are not slowing down. Like we're growing 30, 40 So you percent a did [00:39:26] S1: 4,000,000,000? I hope to be way beyond that. With the greatest of respects, 15,000,000,000 then feels like quite a cheap price. I'm an investor, so this is now my ballpark. If you think you were gonna be at 4,000,000,000, say dropping, I don't know, a billion 2 to the bottom line, then they actually only paid, what, 14x end of year next year bottom line, 3x top line? [00:39:47] S0: Yeah. It's kinda cheap. [00:39:48] S1: That feels pretty cheap. I think it's cheap. I mean, like, [00:39:50] S0: I wouldn't do this if I didn't think we could grow and become, like, a generational company. I think there's so much upside. I think this is one of the largest markets opportunities that's ever existed. I think that the demand for compute, the demand for AI applications, it's gonna be enormous, and they're all gonna need a place to run. And I hope a lot of them are gonna run a modal.
00:39:50 · Erik Bernhardsson, Harry Stebbings
[00:39:50] S0: I wouldn't do this if I didn't think we could grow and become, like, a generational company. I think there's so much upside. I think this is one of the largest markets opportunities that's ever existed. I think that the demand for compute, the demand for AI applications, it's gonna be enormous, and they're all gonna need a place to run. And I hope a lot of them are gonna run a modal. [00:40:07] S1: What revenue line do you not have today, or is tiny, that you think will be very significant in three years' time, five years' time?