Here’s how I do the same thing, just with a slightly different wrapper: I’m running my own stepwise runtime where agents are plugged into defined slots.

I’ll usually work out the big decisions in a chat pane (sometimes a couple panes) until I’ve got a solid foundation: general guidelines, contracts, schemas, and a deterministic spec that’s clear enough to execute without interpretation.

From there, the runtime runs a job. My current code-gen flow looks like this: 1. Sync the current build map + policies into CLAUDE|COPILOT.md 2. Create a fresh feature branch 3. Run an agent in “dangerous mode,” but restricted to that branch (and explicitly no git commands) 4. Run the same agent again—or a different one—another 1–2 times to catch drift, mistakes, or missed edge cases 5. Finish with a run report (a simple model pass over the spec + the patch) and keep all intermediate outputs inspectable

And at the end, I include a final step that says: “Inspect the whole run and suggest improvements to COPILOT.md or the spec runner package.” That recommendation shows up in the report, so the system gets a little better each iteration instead of just producing code.

I keep tweaking the spec format, agent.md instructions and job steps so my velocity improves over time.

--- To answer the original article's question. I keep all the run records including the llm reasoning and output in the run record in a separate store, but it could be in repo also. I just have too many repos and want it all in one place.