Agentic coding achieved absolute product-market fit this year, with customers pulling it out of developers' hands, which is why the whole industry's focus has narrowed onto it while other use cases remain unproven.
Benedict Evans says agentic coding is the one AI use case with undeniable product-market fit, which is why the industry's attention has narrowed sharply onto it even as the resulting demand has caused a supply/price crunch. ✦ AI generated
Benedict Evans · a16z Podcast · 2026-06-08 · original ↗
starts at this moment · 1:44
“what have we learned since you originally uh made the presentation what's played out”
clearly agentic coding started working and so all the focus in tech has kind of narrowed in massively onto that as something that has absolute product market fit in the sense that like the customers are pulling it out of your hands.
verbatim transcript · starts at 1:44
1:44tech has kind of narrowed in massively onto that as something that has absolute product market fit in the sense that like the customers are pulling it out of your hands. Um and um and of course that comes with the supply crunch around capacity and price imbalance imbalance of supply demand capacity capex pricing that we see at the moment. Um so that's kind of the big shift like we had a
2:06moment of like this is kind of sort of working and kind of exciting but we're not quite sure what we're going to do with it to like right it works for coding um will it work for anything else like yes almost certainly but that's what's working right now and so that's become we've got this kind of much narrower focus. Um otherwise um you know the chartman numbers keep coming up, the
2:24models keep getting bigger, the capex keeps growing, the usage keeps growing, people using this more. But most of the sort of fundamental questions you might have had two or three years ago didn't really have answers. Like we don't know if there'll be a winner in the models. We don't know if they can capture value up the stack. We don't know how much the models can do. Um we don't see a way
2:44that consumers will use this daily rather than weekly with the technology we have right now. So all all of those questions are still open. >> Yeah. And just on on the on the coding, how could could we have figured could we have foreseen that that would have been the the the use case that really would have taken off or what's sort of a reflection on that? >> Well, um you deterministically you could
3:08have said, well look who's messing about with this stuff? Software developers. What are software developers going to try and make work software development? Um so you know at a very kind of simplistic naive level well yeah the stuff that should work is software develop first is software development just as like kind of I often compare this moment to like the internet in like 9798 but it's also like the PCs in the
3:29early 80s or the late '7s. It's incredibly exciting but it's not quite clear what it's for and it doesn't quite work yet and clearly the first thing that people did with PCs was make computers. Um, and the first thing that people are doing with LLMs, in a sense, LLMs are computers, is to make more compute. Um, and so that's not terribly surprising. I think the shift is been at