The Twenty Minute VC (20VC): Venture Capital | Startup Funding | The Pitch
00:39:36 · Harry Stebbings, Naveen Rao
[00:39:36] S1: So then help me out. What happens if the delivery mechanism or the output of all the infrastructure is then commoditized? [00:39:43] S0: Well, I I think commoditization doesn't necessarily mean it's bad. It just means that margin, yeah, falls quite lot, but it also means that the market is very big. So you you could argue that tomatoes are commoditized, but we still eat them. We still need them. You know? So we will have a huge market for intelligence, and that market will continue to grow, but the margins may not be huge. I I actually don't think the model companies will be the ones who own the margin of the whole stack. It's not even true today. Like, NVIDIA owns the margin of the stack today. Right? I would say they're probably the one who take the lion's share of the of the margin. [00:40:17] S1: A A lot of people say to me the cost of inference will actually go massively down over the next few years, and we'll see the commoditization potentially of the inference market. Would you agree with that or not not agree with that? [00:40:28] S0: Well, let's break it down. What is in... What is commoditization of the inference market mean? What that means is that the operator who's who's running inference, I assume. Yeah? [00:40:37] S1: Yeah. Absolutely. Your Fireworks, your model, your base TANs, and the services that they provide.
00:40:37 · Harry Stebbings, Naveen Rao
[00:40:37] S1: Yeah. Absolutely. Your Fireworks, your model, your base TANs, and the services that they provide. [00:40:42] S0: Because if you look at their value prop, what they've done, and they've done very well, is take a model that exists, an open model, say, and then make it work well, you know, with uptime guarantees and make it, you know, relatively cost efficient to run on infrastructure. So they're an infra play. Right? They're basically mapping the model onto physical hardware and doing that well. Now I think there will be value there in the future, but the price of inference, like what people are willing to pay per token, will drop. And so they're basically... They have to squeeze more margin out of the hardware's capabilities to the delivery of that token. And that, you know, the amount of juice in that layer, I think, will decrease. So I think it'll result in them having lower margins. And and I think the model itself, like, is commoditized. You have several different ways to get it now. But the hardware side of it probably won't won't collapse. I think that part of it is still gonna have an advantage because you can still squeeze more juice out of, hey. I convert energy to intelligence more efficiently. The... We have more... A lot more juice to squeeze there versus the infrastructure layer in my view. I actually think the hardware is the place to be over the next ten years. [00:41:45] S1: Dude, it's quite fucking hard doing hardware investing. It's a very different mindset. Is this generation of investors equipped to be hardware investors?
00:41:45 · Harry Stebbings, Naveen Rao
[00:41:45] S1: Dude, it's quite fucking hard doing hardware investing. It's a very different mindset. Is this generation of investors equipped to be hardware investors? [00:41:55] S0: No. I would say if you're a pure software investor, you're kinda fucked, And I'll say that pretty confidently because SaaS, I don't think is gonna be where you gain margin anymore. And we had this sugar high for the... Since, what, 2011, 2010 timeframe till now of, you know, I can very quickly spin something up on an AWS cloud service, test the market quickly, try things out, and then go after a 100,000,000 or $200,000,000 SaaS was like massive fragmentation of the market because the delivery mechanism became very easy and frictionless. Now we're in this place where applications start to become more about the intelligence layer, and I just don't see software being a huge market in twenty years. [00:42:38] S1: Do you not just think SaaS becomes legora? And what I mean by that is, like, is legora SaaS? Well, kind of. Yeah. Enterprise SaaS, but kind of not. No. So does, like, the semantics not just change? I don't think anyone really is like starting fresh being like, oh, we're we're a SaaS company.
00:42:38 · Harry Stebbings, Naveen Rao
[00:42:38] S1: Do you not just think SaaS becomes legora? And what I mean by that is, like, is legora SaaS? Well, kind of. Yeah. Enterprise SaaS, but kind of not. No. So does, like, the semantics not just change? I don't think anyone really is like starting fresh being like, oh, we're we're a SaaS company. [00:42:56] S0: Right. So exactly. I think you're right. So I was taking the classic definition of SaaS, I suppose. But I think companies where you deliver an outcome and you do so through a combination of software and services, absolutely. You know, we're seeing that in in several companies, and I I invest pretty actively in startups, generate the seed stage. And, you know, I'm I'm seeing a crop of companies come where they're taking engineering tasks that have existed for a long time that were done in a traditional way and have to be done correctly. And they're making those tasks much more, much faster, much cheaper by using AI plus humans. It's great. That's... I mean, I would say Harvey was the first example of this for law firms, where the old way was I have, you know, a set of lawyers who go and look at contracts and, you know, write contracts, that kind thing. And they basically said, well, I can use AI and verify the outputs with humans and deliver the same thing with fewer humans and deliver it faster at the same quality or near the same quality, and I will disrupt that market. So I think we're gonna see... This is sort of the new test.
00:43:52 · Harry Stebbings, Naveen Rao
[00:43:52] S1: Can I? We see it... You know, I call it word wank, which is where, like, you know, VCs come up with a coin theory of the world. And it's like, you know, the the trillion dollar services thing that, you know, I think Sequoia did a brilliant piece on. And I love Julian who did it. It's very good. But, like, are we not just slightly jazzing it up? That's just the future. People using AI to do things efficiently. There's, like, a whole glamorization of it. Bit overkill, isn't it? But aren't you just investing in a law firm when you do that? [00:44:21] S0: Effectively. Yeah. But you're just... It's a better version of a law firm. Right? [00:44:24] S1: That's a lot. And you... And... But you'd be okay to do that because I meet a lot of companies doing exactly what you say. And I'm like, I don't wanna do a law firm. I'm happy doing a Legra or a Harvey, which sell to law firms, but they're not actually a law firm.
00:44:24 · Harry Stebbings, Naveen Rao
[00:44:24] S1: That's a lot. And you... And... But you'd be okay to do that because I meet a lot of companies doing exactly what you say. And I'm like, I don't wanna do a law firm. I'm happy doing a Legra or a Harvey, which sell to law firms, but they're not actually a law firm. [00:44:36] S0: Well... But we are seeing that. Like, some of the large law firms are now investing in AI directly. So I think in its limits, you'll see, basically Harvey sells to the law firms because the law firms have the channel. You know, is that channel gonna be enduring? I don't know. But I could also see them saying, well, you know what? We could just sell directly to companies. Like, personally, I would buy that. If Harvey said, hey. I have a solution that does all your NDAs. It does... It reviews your contracts, blah blah blah, like, all these things, and I I can gain, confidence that it works, I would send 80% of my workloads, my legal workloads to them. [00:45:10] S1: I am intrigued, though, because you spoke about some firms that are building their own. I think you saw KNE in the legal space commit, like, $500,000,000 to it. You know, Lin, Fireworks, where I'm an investor, spoken very openly about owning your own intelligence and the importance of companies leveraging their own data to build their own models. Do you think that is a very viable future or actually a slightly techno optimist prediction from a very specific standpoint?