Ya, that's pretty much my workflow as well. Though for my little web app, I could give it the whole ball of html/css/js each time.
I haven't seen anyone else describing this workflow. Feed it the existing code, ask it to modify/improve/fix the code and output a new version of all the input code, review diffs.
It has downsides, because you can easily run out of context window of chatgpt-3.5-turbo. But I am getting much better code out of it versus other approaches I've tried. And it's a very efficient and natural workflow -- we're used to getting and reviewing diffs/PRs from human collaborators.
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#import ~/work/gish/tasks/coding.txt
Change the following so that it looks for the open AI key in the following fashion:
1. env variable
2. os.home()/.openai
3. Throws an exception telling the user to put it in one of the above, and then exits
#diff ~/work/gish/src/LLM.ts
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Puts me in vimdiff comparing the old code with the generated code letting me review and cherry pick the changes.