This is really well thought out. The git-like versioning approach for memory artifacts is something I’ve been advocating for after spending way too much time debugging agent state issues.

I’ve been working on AI memory backends and context management myself and the core insight here — that context needs to be versionable and inspectable, not just a growing blob — is spot on.

Tried UltraContext in my project TruthKeeper and it clicked immediately. Being able to trace back why an agent “remembered” something wrong is a game changer for production debugging.

One thing I’d love to see: any thoughts on compression strategies for long-running agents? I’ve been experimenting with semantic compression to keep context windows manageable without losing critical information. Great work, will be following this closely.