I really think this is very powerful. RLMs just kind of blew my mind when they first came out. And again, as you can probably see through this talk, I've been absolutely obsessed with applying the ideas of RLMs to coding agents. The three things that I hope you'll take away from this is one, like, trust is reliability. Like, how can we how can we trust something that isn't reliable? And again, my argument and this idea of the mismanaged genius is um, that the next step is not, um, more raw intelligence. It's actually, uh, behavioral. It's actually orchestration. I personally believe that, um, RLMs represent this new paradigm of test time compute, inference time compute, uh, where tool calling and reasoning are unified. And we reason through tool calling and we can, uh, recursively iterate. And one of those tools is to call another agent to go do it on some other specific task or subset of the problem. Uh, and then also, I hope we settle a little bit of this drama around like wait, like are are LLMs actually new? Aren't they just coding agents? Yes, coding agents can be LLMs. They aren't automatically LLMs. And so I've showed a couple of different Claude code dynamic workflows that can turn Claude code into an LLM as well as some ways of doing this with