This is the way. This exact workflow is my sweet spot.

In my coding agent std::slop I've optimized for this workflow https://github.com/hsaliak/std_slop/blob/main/docs/mail_mode... basically the idea is that you are the 'maintainer' and you get bisect safe, git patches that you review (or ask a code reviewer skill or another agent to review). Any change re-rolls the whole stack. Git already supports such a flow and I added it to the agent. A simple markdown skill does not work because it 'forgets'. A 'github' based PR flow felt too externally dependent. This workflow is enforced by a 'patcher' skill, and once that's active, tools do not work unless they follow the enforced flow.

I think a lot of people are going to feel comfortable using agents this way rather than going full blast. I do all my development this way.

This is broadly how I worked when I was still using chat instead of cli agents for LLM support. The downside, I feel, is that unless this is a codebase / language / architecture I do not know, it feels faster to just code by hand with the AI as a reviewer rather than a writer.

your patch queue approach is very clever. Solves a huge tech debt poblem with llm code gen. Should work with jujitsu too probably.

Would be curious to see more about how you save tokens with lua too.

Do you blog?