> Is there any task that actually doesn't require human intervention in-between, even if its just to setup stuff?

The goal is none. The current situation: everything that matters requires human intervention.

I think the end situation will be that LLMs will be able to perform decently well in a highly controlled and predictable environment.

> in a highly controlled and predictable environment

Why this constraint? A common sentiment I see online (sorry, to group you in) is "[tool] will be capable, actually, but only in a context that trivializes its usefulness."

I think modern post-training like RLVR + inference-time output token scaling can _probably_ scale so the agents can solve any computable task, even when placed in noisy or misconfigured environments. But it won't be economical for a long while. But it already seems largely capable of that today.

Porting large amount of code.