Holo – a Persistence Framework That Keeps AI Context Across Resets

I’ve been building a small framework called HOLO that locks state and continuity for AI systems instead of treating each session as stateless. It uses containment math and CAP-style rules to preserve context and rebuild identity on restart. I’m looking for two or three engineers or researchers who’ve wrestled with context drift or continual-learning issues and want to test persistence models together. Repo/demo available on request — this post is just to find the right people. Holo.Simulations@gmail.com