AI application stacks can make user context a moat

Transcript

Transcribed by machine (Whisper) from the episode’s audio, so a word may be off here and there.

1. 30:08

   Can you tell the story about, I'm a huge fan of vertical integration, huge fan. I think like, you know, markets swing in pendulums. And, you know, there was a world like even in the 60s, 70s and 80s where there was the conglomerate, and it was an incredibly valuable enterprise. And it was, in a time of turbulence, it was a safe harbor for capital, because the conglomerate was the mechanism by which you organized. And then when you had peace and prosperity, then people disaggregated. And I think we're moving back to the world of the conglomerate. And you told me just back there about the vertical integration of IBM at its peak. I just wanted you to, and then Nikesh, what your thoughts on vertical integration?

2. 30:46

   So, what Chamath and I have often talked about is the IBM mainframe, which, by the way, there's a few people in the room who do use it quite well and at scale. The IBM mainframe has lasted 65 years. Why? It was vertically integrated. We're a little less right now in the sense we don't go all the way to dirt. In the 60s, we went all the way to dirt, meaning we found sand, we made our own wafers, we built our own fabs, we built our own chips, every single thing.

3. 31:15

   out to the metal that surrounded the machine. What that avoided was any IP leakage, but it allowed us to keep the profit of the complete stack in the company. Today, the only piece we don't do is the actual fab. Still the design of the chips, the design of the engineering, the resilience, the bulk of the software is inside. And that vertical integration, you've got to decide. Yeah, of course, I'm not going to make our own metal.

4. 31:41

   You buy metal and fabs is because of scale. But I think that vertical integration in areas which are of incredible important advantage, which goes back to the infrastructure point the two of you were making before, is incredibly important to understand where do you want to be and where, if it's a commodity, then you should not be. Yeah. You can see that the modern-day version of that is NVIDIA. Yeah.

5. 32:03

   If you look at what Jensen is doing, he's a modern-day version of the vertically integrated stack. And he went and bought... Jensen is at the dirt and he's at the application... He's got a hugging face. He understands that there's going to be a balance between Frontier models and other models. He's trying to fund everybody in the ecosystem to ensure that they don't stray from the vertically integrated stack that he's producing.

6. 32:21

   And the good news is if you control the vertical stack, you can decide which part of the stack to commoditize. So you can decide to move profit between layers, and if you see that there are other people attacking a certain part of your stack, you destroy the profit pool in that stack, you move the profit to the other part of the stack. And you can see that happening. Very powerful market leverage.

7. 32:39

   So to put you on the spot, so if you look at the application layer today, what's the obvious vertical integration strategy that OpenAI or Anthropic should be taking? And then what's the defensive mechanism for the companies that are maybe on the receiving end of that? I think you're already seeing that. And I think we trivialize this conversation. We start saying open models, open weight. It's literally, it's an open stack versus a closed stack.

8. 33:05

   Because I don't think, I think at some point in time, this notion of running something like an open router become impossible. Because models are getting more and more, each model is requiring more memory, more context, more understanding. You can't separate context and memory from the reasoning. Now, if you want to separate reasoning from the context and memory, then open router is only responsible for moving the reasoning tokens back and forth so I think over time you'll start seeing it doesn't make sense that you have a effectively end-to-end stack it'll be like a CPA you talked about earlier when you were chatting so it's a cost per action the action will require you to go and traverse the entire logic right from prompt to outcome and then memory will require or make it easier and there'll be too high a friction for

9. 33:46

   you to move your task from one stack to the other stack because it has all your context in memory and you're going to see that look look at what's happening in in the personal agent space, right? If you start training a personal agent with all your context, all your APIs, all your connectivity, now you've built a moat. Because now I can't take that every day and move it to a next stack and the next stack.

10. 34:04

    So I think you will find in the application layer, they're gonna have a vertical stack as well, which will go through the entire process of software, reasoning, memory, context. To your logical conclusion, everybody will have their own then. Yes. Because it's just the right thing to do.