Layered Project Memory

I've done a fair amount of AI assisted projects (green and brownfield, large repos). I kept running up against all the usual issues, so I made a system for AI assisted dev (it's free/open source). It's layers of markdown documents (no software, tool agnostic) and a workflow. The central idea is start clean sessions often, store project memory outside of the session, load only what's needed. Some of the features; * Save the final project shape not the road map. Once your prototype survives some pivots, you can then rebuild cleanly. * Human gates. At major subsystem boundaries and APIs, the agent will craft the interfaces and some non functioning tests that demonstrate the intended usage. A human has to approve. Same for detailed phase plans. * Project brainstorming and design are done via a web AI and when ready, there is a document to drop into that session. The AI will then produce the project memory files (reqs, arch, plan...) for the implementation agent. * A code map generation and workflow as well. Implementation sessions will also maintain code map memory. I used several models heavily to refine the system, but a few of the better ideas came from actually getting burned on real projects. Those include: * The rebuild target concept. * Human gates. * Separating public vs extension code maps. It's free, no software to install, and probably can be improved. I'd love your ideas. I'll provide the github link in the comments if asked.