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The article addresses this:

> This made sense when agents were unreliable. You’d never let GPT-3 decide how to decompose a project. But current models are good at planning. They break problems into subproblems naturally. They understand dependencies. They know when a task is too big for one pass.

> So why are we still hardcoding the decomposition?


Sure, decomposition is already in the pre-training corpus. and then we can do some "instruction-tuning" on top. This is fine for the last mile, but that's it. I would consider this unaddressed and after with the root comment.


Not necessarily - I've been having a lot of success with an event-delegation model.

https://github.com/mikeyobrien/ralph-orchestrator


My gut says you are correct though cycles can be permitted given a boundary condition.



Where is the doc/source for such boundary conditions?




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