AIE Europe Debrief + Agent Labs Thesis: Unsupervised Learning x Latent Space Crossover Special (2026)

**swyx** (0:00)
Isn't that crazy? That number is just mind-boggling.

**Jacob Effron** (0:03)
What is the state of the AI coding wars today?

**swyx** (0:05)
We're in a phase of capability exploration. The general thesis that I have been pursuing now is that the same way that 2025 was a year of coding agents, 2026 is coding agents breaking containment, do everything else.

**Jacob Effron** (0:16)
Do you worry about the foundation models just eating into a bunch of these startup categories?

**swyx** (0:21)
Mid-sized startups, yes.

**Jacob Effron** (0:23)
What do you think the end state of this market is?

**swyx** (0:25)
For the market structure to significantly change, there would be...

**Jacob Effron** (0:28)
Today on Unsupervised Learning, we had a fun episode on what's really become an annual tradition, a crossover episode with our friends at Latent Space. Swicks and I sat down and we talked about everything happening in the AI ecosystem today, what we thought of the various changes at the model layer, what's happening in the Infraworld, the coding wars, and a bunch of other things. It's a ton of fun to do this with someone I really respect and another great podcaster in the game. Without further ado, here's our episode.
Well, Swicks, this is super fun to be back with another Unsupervised Learning x Latent Space Crossover episode. I feel like a lot of places we could start, but one thing I always find fascinating about the way you spend your time is you obviously are at the epicenter of this engineering movement and community, and you run these events and conferences and put on these awesome talks, and I think just have a great pulse on the zeitgeist of what's going on. Maybe to start just, what are the biggest topics people are thinking about right now?

**swyx** (1:21)
Yeah, so I just came back from London where we did AIE Europe, and we're doing roughly one per quarter now, which really upped the pace. We're trying to match AI speed.

**Jacob Effron** (1:30)
Yeah, exactly. The topics will be completely different, I imagine.

**swyx** (1:33)
I definitely curate the tracks. You can see what I think when you see the track list and the speakers that I invite. Obviously, OpenClaw is the story of the last four or five months. And then just below that, I would consider Harness Engineering and Context Engineering to be two related topics in Agents and RAG. And then there's a long tail of evergreen stuff, like EVALs, Observability, GPUs, and LLM Infra just in general. We also have other updates on multi-modality and generative media, let's call it.
But definitely the first three that I mentioned are top of mind people.

**Jacob Effron** (2:13)
I think Harness is particularly so interesting. There was this tweet from Harrison Chase, the lane chain CEO that caught my eye recently, where he said, it finally feels like we have stability around the infrastructure for, around AI. And I think what he basically was implying is like look over the past two, three years as a company at the epicenter of AI infrastructure, it was a bit like playing whack-a-mole, right? You were constantly moving around with however the building patterns were evolving.

**swyx** (2:36)
For Harrison, for sure, right? He's basically had to reinvent the company every year since he started lane chain, right? It was lane chain, lane graph, and all deep agents. And I think he's one of the most nimble, adept, sharp people about this.

**Jacob Effron** (2:49)
Yeah, but he's like, now is finally the time for stability. Do you buy that or what have you kind of make of that take?

**swyx** (2:56)
I think that it's very expensive to say this time is different sometimes. But when you're just writing code, it's actually okay to just try to make a call. And I think it may not even matter if this call is right or not. I just don't even care that much because you can be right on the thesis, but if you don't figure out how to monetize the thesis, then who cares if you said something first? That said, it does feel like, for example, we went through a lot of different ways of packaging integrations up with agents. And it feels like we've landed at skills, which is like the minimal viable format, which is just a markdown file with some scripts attached to it. And I don't see how it can be more simple than that. And so there is some justification for the stability around harnesses. I feel like there may be more adaptation with regards to maybe like the real-time elements or subagents or memory or any of those agent disciplines, let's call it, in agent engineering.