> Care to provide an example of sorts?

For example, recently I needed to revise some code I wrote a few years back, re-implementing a caching mechanism to make it work across networked instances of the same software. I had a rough idea how I wanted to do that, and used an LLM to flesh out the idea. The conversation starts with an instruction that I don't want any code written until I ask for it, then I describe the problem itself, let it list the key points, and then present my solution (all still as prose, no code so far).

Next step, I ask for its comments, and patterns/implementation details how to do that, as well as alternatives to those. This is the "design phase" of the conversation.

Once we zoom in on a concrete solution, I ask it to produce a minimal example code of what we discussed. Then we repeat the same process, this time discussing details about the code itself. During that phase I tell it what parts of the implementation it doesn't t need to worry about and what to focus on, keeping it from going off to mock-up-wonderland.

At the end it usually gets an instruction like "alright, please write out the code implementing what we discussed so far, in the same context as before".

This gives me a starting point to work from. If the solution is fairly small, I might then give it some of the context this code will live in, and ask it to "fill in the blanks" as it were...often though I do that part myself, as its mostly small refactoring and renaming.

What I find so useful about this workflow, as opposed to just throwing the thing at my project directory; it prevents the AI from getting side tracked, lost, as it were, in some detail, endlessly chasing its own tail trying to make sense of some compiler error. The human in the loop (yours truly), sets the stage, presents the focus, and the starting point is no code at all, just an ephemeral description of a problem and a discussion about it, grounding all the latter steps of the interaction.

Hope that makes sense.