Kevin Scott, CTO @ Microsoft: An Evaluation of Deepseek and How We Underestimate the Chinese

This is the best time to be alive if you have an entrepreneurial spirit. I can very clearly see what we're doing now, and, like, what we're doing next, and I don't see the limit to the scaling laws. Don't believe in this, like, one agent for everything sort of theory. I think you'll have a lot of agents, and, uh, the reason I think you're gonna have a lot of agents is because your product managers are probably going to have to be domain experts. The agents, they will definitely be less transactional, less session oriented going forward.

Ready to go? (instrumental music plays) Kevin, I am so excited for this. I was just telling you, I was listening to you and Shrep on my run. I, I don't think I've ever run quite as fast, which clearly means the conversation was brilliant, um, and I need to listen to all of the shows. But thank you so much for joining me.

Well, either brilliant or awful, uh, in that (laughs) you're trying to end your run so you can be done with it. (laughs)

I've never done a 10K so fast. Um, I, I wanted to start with a super easy question, which is, my job as a venture investor is to try and determine where value lies in different given moments. And I look at the world today, and for the first time in quite a long time, Kevin, I don't know. (laughs) And my question to you is, in this next generation of AI, where does value lie sustainably, do you think?

Yeah, so I, I think the thing that you just described, which is, like, all of a sudden things have gotten a little less clear than they had been, is exactly the thing that happens at the beginning of every big technological paradigm shift and every new cycle that's driven by it. So it was super confusing in the early days of the internet, and I think it was super confusing in the early days of mobile, where everybody, you know, had these ideas about what was gonna be valuable, and very few of those ideas were actually the durable ones that proved all the way through.

In, in those moments of transition where there is this confusion, what have you learnt is the right action to do? Is it to be active, to iterate and learn, but you'll make so many mistakes that you regret, or should you sit on your hands and watch others make those mistakes?

Oh, God, no. Like, you definitely shouldn't do the latter. Um, so, like, this is the best time to be alive if you have an entrepreneurial spirit. Um, and, like, the thing, the thing I think that you have to do in these moments is not forget the things that you've learned from the past moments about what works. And it's not like, okay, well, like, it's do this specific thing, but it's, like, how you go about doing, uh, you know, that exploration that you just described. Which is, you know, product matters. Uh, you know, I've, I've been saying this for the past couple of years, that models aren't products, uh, because everybody, like, was just so fascinated by the infrastructure itself, and, you know, like, "Oh, we..." A- and, and, like, this is also a characteristic of the beginning of these cycles, is you have technical people who get just swept up in the technical bits, and they kind of forget that the only thing that really matters is making good product. And, like, that's where we're at right now. Like, you have to make good product, and, um, you know, you have to have ideas and have conviction, and then you have to go get stuff done really fast, uh, so that you can see whether you're full of crap or not about the conviction that you have. And y- you're not... You have very few patterns at the beginning of a cycle to go snap to. Like, you're not looking at someone else's success and saying, "Okay, well, like, I'm gonna do that, but just a little bit better." Like, you're trying to figure out something completely new, and the only way to figure that out is, like, you gotta launch stuff, and gather data, and iterate, and, you know, be super, super brutal with your own self about what you're seeing. Like, you can't love your idea so much that you overlook what it is you're seeing about the data and the feedback that you're getting.