Great insights. Specifically inverting the vibe coding flow to start with architecture and tests is 100% more effective and surfaceable into a real code base. This doesn't even require any special tooling besides changing your workflow habits (though tooling or standardized prompts would help).
Yeah, I started creating my own architect tool as this is what missing currently. Given good architecture you can really hand down implementation to AI these days.
One problem I see that these tools aren't good at reading logs of long running processes (like docker-compose)
But you need to:
* Research problems
* Describe features
* Define API contracts
* Define basic implementation plan
* Setup credentials
* Provide testing strategy and setup efficient testing setup/teardown
* Define libraries docs and references and find legit documentation for AI
* Also AI does a lot mistakes with imports etc. and long running processes
True. One understated positive of AI is that it operates best when best practices are observed - strong typing, clear architecture, testing, documentation. To the point where if you have all that, the coding becomes trivial (that's the point!).
