I disagree. LLMs might create incoherence not because of context size limit is too low, but because it's too high. The limit is vastly higher than for humans.

But to overcome the limit, one needs to adopt simpler, more coherent models of reality, which is what I believe humans do. But there is little motivation to do so if your context window allows you to understand the situation in full.

So it seems there is a tradeoff. Some solutions (proofs of complicated statements) might require context of certain minimal size. So human solution doesn't scale.

Maybe we should try to adapt the context window to the system being worked on, to ensure that the system architecture has the structure viable in the minimal context size required.