The Twenty Minute VC (20VC): Venture Capital | Startup Funding | The Pitch
00:21:43 · Jason Lemkin
[00:21:43] S0: It's not that I think... Well, let me be clear, because I think you'll agree with me. It's not that I think they're gonna be killed. I think they're gonna be maimed. It doesn't matter if this means that Resy's growth falls this much. If this means it impacts 10% of Amazon's advertising revenue. That's just like Meta stocks up 20 some odd percent. If this drives Amazon stock down 20% because it impacts margins, it's a big deal. I can tell you talking to our agents all day, they don't put up with this bullshit. They don't friggin' put up with it, right? Listen, I don't want to name the name or the vendor, please don't make me, but we got a raise this morning from one of our core vendors, massive price increase, massive pricing. Immediately our agent said, I want to work around it. Here are my ideas, dump them. And it actually laid out a twelve month plan to migrate off this vendor on its own. They will not tolerate this crap. Right? And there are so many products you can only buy on Amazon. There's it has so many advantages as warehouse, it has fulfillment, but some of that stuff can be bought on a Shopify store. It could just be enough. It could just be enough. This maiming is a big deal for AI. It's gonna maim the existing folks unless they embrace things they don't want to embrace.
00:22:44 · Rory O'Driscoll, Jason Lemkin
[00:22:44] S1: Two comments. One each way. One is yes, I do think Amazon's biggest defense will be its physical infrastructure and ability to deliver, but zooming. But your point is the right one. I remember someone said, like twenty years ago when the Internet... Probably twenty five years ago now, Internet first came out, that the Internet abhors inefficiency. In other words, middlemen get pounded down. Right? And if you think about things like the travel sites, Expedia, Airbnb, all of that is that, is getting demand and supply closer together. And I think what you're saying, Jason, is correct. AI is the same. It's going to pound down people who are in the middle, who just have information and are using that to make offers. If if that's all you're doing, there will be pressure at the margin. Because if you're reducing search costs, that's valuable to me as a human, but maybe the agent can just do it itself. So I'll go with the maiming comment. If it's even 5% or 10% impact, it's meaningful. [00:23:34] S0: That's the thing. It's easy to shut off perplexity for Amazon. It's just... They're just a gnat. Amazon will have interesting choices when it's everybody. Like, you shut off everybody. It is technically possible. But at some point, it's gonna be complicated. Are we sure we wanna shut off everybody? Moving swiftly on. Anything else that I haven't touched with Muse?
00:23:34 · Jason Lemkin, Rory O'Driscoll, Harry Stebbings
[00:23:34] S0: That's the thing. It's easy to shut off perplexity for Amazon. It's just... They're just a gnat. Amazon will have interesting choices when it's everybody. Like, you shut off everybody. It is technically possible. But at some point, it's gonna be complicated. Are we sure we wanna shut off everybody? Moving swiftly on. Anything else that I haven't touched with Muse? [00:23:52] S1: No. Because it's not really the story of the week. I mean, it's the story of last week. We're gonna do the story of the week, and Jason's gonna be ready as a hands on users to tell us about Jev. Right? That's the story of the week. How do we go? [00:24:03] S0: We can talk about JEV if you want. [00:24:05] S1: It's next one up, and it's the story. [00:24:06] S2: It's the next one up, and fine is Rory's story of the week. So for those that don't know, chat GBT and banter ships JEV. It's a model that decides instead of chats, and it becomes Vercel's fastest ever launch. Jason, I'm sure you've played with it. What did you think? Jason's review. New new segment. [00:24:24] S0: Well, first of all, listen. I'm not I I maybe... I might not be smart enough to get into semantics. I don't even think it's a model. I think it's a classifier backed by an LLM. I've used it. It's awesome. But I don't know that it'll be as disruptive as everyone on x talking about it that probably never used it said it is. But it is awesome. Okay? Jason, what do you [00:24:41] S2: use it for?
00:24:41 · Harry Stebbings, Jason Lemkin
[00:24:41] S2: use it for? [00:24:42] S0: What I use it for is deciding who in the SaaS community should meet each other. It's quite good at that. Rory is the CRO at GCI. Harry is the CRO at Perplexity. Should they meet? It's actually not that simple a question. They're at pretty different stages. They live in different places. Should they meet? I spent all of Saturday nothing worked on on Jeb because I had to redo the way I did prompts. Okay, so I thought it was a failure, right? Then what I learned is you've invested the time. It can answer that question in milliseconds for a hundredth the price of anthropic or judge, actually even less. It can just answer a question and it can answer a subset of questions. But I think as we've learned from data labeling and others, there's a lot of classification that needs to be done, a lot of data labeling that needs to be done, but it doesn't output text and it can't do anything particularly complicated or with reasoning. So it's like a big deal. And for this particular use case, I'm talking about who should meet who. It is disruptive, but it's maybe like 20% of all the LLM calls associated with this application. Right? So I love it. I think everyone will do some version of this. I think, you know, maybe even XA and Parallel should do some version. Maybe OpenAnch, everyone should do a version of this, but it's not going take over 100% of your stack and it's not going to replace ChatGPT because it just doesn't do those things. But it does remind us that man, we effing waste a lot of tokens on simple stuff that Astra shouldn't be doing.
00:26:07 · Rory O'Driscoll, Jason Lemkin
[00:26:07] S1: I pretty much a 100% agree with you. I mean, the zoom out comment is this. It's a new model. It's different than an LLM. An LLM returns text and is very computationally intensive, and in computing terms, slow and expensive. This just returns true or false or a ranking or a score, right? So there's three answer types, and it's super fast and super cheap. They don't even charge for output tokens because they're so meaninglessly few. So it's just a faster, more precise. That's why it's called... They refer to it in turn on the website as a system one, which is the Daniel Kahneman thinking fast, thinking slow. And this is the thinking fast part, quick, fast answers. But Jason's math is exactly right. But we're talking about this on Monday, the part of meeting is that there's roughly a $100,000,000,000 today being spent on LLM calls between Anthropic OpenAI and the open source models. Maybe that goes if we just agreed that OpenAI is gonna be doing 350, Amazon, 250. So it's probably gonna go to $500,000,000,000 five years from now. 20%. And, Jason, we had exactly the same number. Only 20% of them are relevant to this, where it's... Today, you're using a complex expensive model for something that really needs a much simpler solution. But 20% of a $100,000,000,000 is 20,000,000,000. [00:27:21] S0: Well, I don't think I don't think the dollar is gonna flow that way. I think the tokens will... Don't think the
00:27:21 · Jason Lemkin, Rory O'Driscoll
[00:27:21] S0: Well, I don't think I don't think the dollar is gonna flow that way. I think the tokens will... Don't think the [00:27:24] S1: dollar Let me finish, damn you. The next thing... Because you you got... You sound like the cynics of my group on Monday. We had this... I've already had this discussion once. That's why I can carry it off. So that's 20,000,000,000, but you're exactly right. As one of my partners said, but, dude, you just said the prices are going to down by five x. So that 20,000,000,000 is going to become 4,000,000,000. You're exactly right. It's just like open source. It's gonna take a slug of the total addressable LLM marketplace, attack it with a better, cheaper product at one fifth the price, net result at 20,000,000,000 becomes 4,000,000,000. But if you're a JEV or if you're a TypeSave, you're saying, hey, that 4,000,000,000 becomes mine. And that's the bet. Now, at the same time, going back to your naming concept, which I love, Jaya from Foundation did a nice post at Biggs. This is just a slug of the total 100,000,000,000 spend that was kind of automatically destined to go to OpenAI and Anthropic and is now kind of sluicing off into a cheaper low cost provider. That's what's happening here. You're right. It's not the end of foundation model. The clever shit is still gonna be done using foundation models. It's just a little maiming of 10, 20% of the revenue that's now gonna be done by someone else at one fifth the cost. Now we can talk about competition in a second because I think that's a real issue, but that's what's going on here.