The Twenty Minute VC (20VC): Venture Capital | Startup Funding | The Pitch
00:25:12 · Harry Stebbings, Parag Agrawal
[00:25:12] S1: this business is a little bit like music with streaming, which is like the business just becomes candidly much worse for the creators. And it still provides some money and significant money, but they have to get a little bit more creative with alternative streams, touring, merchandise, alternative business. Is it the same where your core goes down and you have to get more creative? [00:25:33] S0: I don't know, but I don't think so. I think there's one fundamental thing that is different here. Agents using the web a thousand x more, like that thousand x is really different. Now all of a sudden, the amount of utility added goes up if these agents are presumed to be doing something useful. And so this is not just a change in the share of value that people transact over. This is a large growing pie. And when that happens, it is actually possible to transition business models. And of course, don't get me wrong. There are going to be winners and losers. Right? Like, some pieces of content will become very valuable. Some pieces of content will get more commoditized, and people are going to have to adapt to a new customer, to a new market dynamic, to a new kind of monetization engine. But the overall market size, I think, has the potential to increase. Unlike in music where it took a while for it to grow back. I think my understanding is now the industry has grown back up and exceeded its previous peaks in a material way, but there was a moment where it was smaller. In this case, that might be a very compressed period given how fast these things are growing.
00:25:33 · Parag Agrawal, Harry Stebbings
[00:25:33] S0: I don't know, but I don't think so. I think there's one fundamental thing that is different here. Agents using the web a thousand x more, like that thousand x is really different. Now all of a sudden, the amount of utility added goes up if these agents are presumed to be doing something useful. And so this is not just a change in the share of value that people transact over. This is a large growing pie. And when that happens, it is actually possible to transition business models. And of course, don't get me wrong. There are going to be winners and losers. Right? Like, some pieces of content will become very valuable. Some pieces of content will get more commoditized, and people are going to have to adapt to a new customer, to a new market dynamic, to a new kind of monetization engine. But the overall market size, I think, has the potential to increase. Unlike in music where it took a while for it to grow back. I think my understanding is now the industry has grown back up and exceeded its previous peaks in a material way, but there was a moment where it was smaller. In this case, that might be a very compressed period given how fast these things are growing. [00:26:45] S1: Everyone questions the sustainability of margin structures in this business. How do you think about that as a business today?
00:26:53 · Parag Agrawal
[00:26:53] S0: Today, we're in the infrastructure business, and we have a real technical lead in terms of being able to do things at very high quality, very cheap. If you think of the tech we're building, right, like what are we doing? We like to give the highest quality answer. Make it fast, make it cheap. Spend the least amount of compute doing it. Like, we obsess about only these three things. Right? Quality, cost, latency. Turns out if you do that relative to a stack built for humans over the last twenty years, years, you can do things at the same quality for one twentieth, one fiftieth of the compute. And so a lot of margins come down to market structure on competition over time rather than any other factor. Factor. And And in our industry, the market is large. We're too early to know what future competition and market structure looks like. But the margin change due to content owners is not something I worry about. And let me tell you why. The entire premise of us paying content owners is driving incentive alignment. So we like to pay content owners the marginal contribution that they added to an agent doing work. What does that mean? Let's assume that there's an agent trying to get something done, and you're gonna spend a dollar on that agent to get this thing done. Now if you've spent a dollar and ten seconds, because we have a larger model available or ways of spending compute, you could have gotten a slightly better answer. If you spend 90¢, you would have gotten a slightly worse answer. If you're running good agents, like, they're on this Pareto curve. So now imagine I took out one content owner, their data from the web index, and I still spent a dollar. But let's say after taking them out, the quality of the result was the same as the 90¢ agent with their content. So why wouldn't we go and take this 10¢ of marginal contribution they had as a content owner and pay out a decent chunk of it to the person who brought that data? That's how we do our math. That's how we have trained our models, which tell us how much to pay for what content need. And so to produce, if I was going to offer an equivalently good product to my customer, I'd rather pay content owners than spend on inference because I'm spending the
00:29:00 · Harry Stebbings, Parag Agrawal
[00:29:00] S1: same amount. So they're they're all big numbers, but then it actually comes back to revenue at a certain point. Companies are scaling faster than ever revenue wise. Is it a business where your revenue is able to scale as fast as others? [00:29:12] S0: One mental model of our business is we are an adjacency to inference or knowledge work or personal agents. So take out GPUs going into media generation or training. So take training away. Take media generation away for a moment. Look at all of the GPUs, whether it's small models, open models, proprietary models, all of that. Every bit of inference across all models going into running agents, I think somewhere between five to 20% off that spend that goes into GPU will need to go into some sort of a web search stack. Now, if you look at like how many data centers we are gonna build and how much power we'll generate and how many GPUs will build and the scale of this build out and at what rate that's growing. This is a very material market. And if inference grows three x, five x, seven x year on year, we grow alongside it in the same rate. If we're just holding our share constraint, if we're growing share, we're growing even faster. [00:30:12] S1: So like your fireworks scales to 2,000,000,000 in revenue in four years. Is that like a... I'm I'm bringing up. Is that like a similar revenue structure that you can follow?
00:30:12 · Harry Stebbings, Parag Agrawal
[00:30:12] S1: So like your fireworks scales to 2,000,000,000 in revenue in four years. Is that like a... I'm I'm bringing up. Is that like a similar revenue structure that you can follow? [00:30:20] S0: Yeah. But I think when Fireworks is 2,000,000,000 in revenue, the inference market revenue is 200 or more, maybe 300. And so our market potential based on my five to 20% math is, what I'll call it, 10 to 50, 15 to 60, whatever. And what fraction of that can we capture? That dictates how fast our revenue can grow. Like today, I think we grow alongside infants or more. [00:30:44] S1: If you think of it like a $20,000,000,000 there, let's just take that kind of middle. If you assume a 33%, that... Which would be a lot of a market, that would be, you know, whatever that is, 6 to 7,000,000,000, give or take. That's amazing. But before you told me it was a $100,000,000,000 business plus, that doesn't get you to a 100. [00:31:03] S0: In valuation, it does. We were discussing valuations earlier, not revenue. Yeah. So 6,000,000,000 growing at the rate of inference gets you to a 100,000,000,000 business easy, but that's in the next few years. [00:31:13] S1: And and you think that's possible in terms of that revenue scaling that fast? [00:31:17] S0: Yeah. I think in the next few years, it is. [00:31:20] S1: 2030, we're gonna sit here. You think you can be there? I'll get a tattoo for Parallel if you can. [00:31:25] S0: I think it's possible. I think we are gonna have to execute well, and a couple of chips have to fall our way.
00:31:25 · Parag Agrawal, Harry Stebbings
[00:31:25] S0: I think it's possible. I think we are gonna have to execute well, and a couple of chips have to fall our way. [00:31:31] S1: What would be the reason why you don't? Let's map out the... What do we have to get gnarly about these problems? [00:31:37] S0: One reason would be that we see agent don't work. Like, there is, like, a tail risk that agents don't deliver on the profits and we overshoot at the society, which is extraneous to us. If agents work and deliver value and we spend all the money on GPUs that we plan to right now, then the main question is, did we execute well enough to have a 33% share that you bet on. And that comes down to in my mind, did we build the best tech? Did we partner with all of the content providers to have their content available? Because without it, it's not very useful if you want to rely on it. And did we go on the draft of the customers that end up having a decent chunk of that inference in four years from today? And then again, there's like large cone of uncertainty. Right? Like the... I'd say there's a five uncertainty in Fireworks share at that point. If open models crush it like based on Fireworks model, all of them will have a huge chunk of revenue. So did we end up selling alongside them? Did we find all the customers which are spending money on them to spend money on our website by making it the best website in the world?