For example there's evidence that typical use of AGENTS.md actually doesn't improve outcomes but just slows the LLMs down and confuses them.
In my personal testing and exploration I found that small (local) LLMs perform drastically better, both in accuracy and speed, with heavily pruned and focused context.
Just because you can fill in more context, doesn't mean that you should.
The worry I have is that common usage will lead to LLMs being trained and fined tuned in order to accommodate ways of using them that doesn't make a lot of sense (stuffing context, wasting tokens etc.), just because that's how most people use them.
