Sure. This is an internal web app that uses react on the front end and rails on the back end. Typical examples I see LLM success with are writing and writing up routes/controllers/models, writing specs for those, abstracting components, writing front-end vitest/storybook entries. A typical request (filenames and such redacted) is like: "We recently added <link to model>. We refactored our approach for <goal> to <link to different model file>. We need to refactor <A> to be like <B> in these ways. Do that, then update the spec to match the pattern in <file Y>. Run rspec and rubocop when done, and address any issues". I then either wait or go do something else, then review the code and either ask for follow up, or fix minor issues. Sometimes it follows the wrong pattern and I ask it to adjust, or simply git checkout -- and say try again you did Y wrong.

Roughly speaking that is how I think through my work, and when I get to the point of actually writing the code having most of the plan (context) in my head, I simply copy that context to the LLM then go to do something else. I only do this if I believe the LLM can do it effectively, so some tasks I do not ask for help at all on (IMHO this is important).

I also have it help with scripts, especially script that munge and summarize data. I know SQL very very well, but find it still a bit faster to prompt the LLM if it has the schema on hand.

Do you find ^ helpful? i.e does that match how you prompt and if not, in what ways does it differ? If it does, in what ways do you get different results and at what step?

right? The irony is so thick you could cut it with a butter knife