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implementation plan reveals unexpected high complexity <-- do these things have complexity evaluation intuitively ? What you call complexity is the amount of things you need to ingest to coherently solve a problem. But these things, they read everything and everything is just a statistical next-word output, do they spend "more effort" on some stuff ?

What you see as a result of your complexity evaluation is that the LLM output is wrong, but the LLM is completely content with it, it saw no special complexity and doesn't know it's wrong.

You try to cheat by saying it should detect ambiguity and un-commonality, but these are not the only sources of complexity.



The models already dynamically determine how much “thinking” to do and how many additional files are necessary for the agent harness to read in order to investigate/proceed, so the system ought to be able to evaluate complexity at least along these lines.




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