It feels to me like the discretion of the humans is the main problem in your solution space example.
Some tasks require more structure than others. Sometimes, the constraint a human faces is “you must do the work in this module or on this function”.
If the prompt says “only change this function” then the human has a good reason for that. If the LLM can’t figure it out then letting them cook on it feels like a waste of my time and tokens.
Too often I’ve sent Opus or Fable now on what I thought was a simple task to find it chasing its tail.
Fortunately I find more success than tail-chasing with the LLMs but I’m dubious of any suggestion to just let them cook.
However, a solution to the tail-chasing for certain could be to intentionally expand the solution space and to consider how my prompts might be restricting the LLM’s options.
Enjoyed the blog thanks for sharing!