Creator here.

Built this to show why AI can't form persistent identity even with perfect memory.

Click "Run Demo" button for one-click proof: - Runs 30 rounds, saves state - Refresh page - Load state - Identity continues exactly where it left off

Three agents learning same task: - Frozen (C=0.95): Too rigid, can't adapt - Dissolved (C=0.20): Too fluid, no stability - Bounded (C=0.70): Optimal window, stable growth

Key architecture insight: - wA = immutable constraint (locked) - wB = identity layer (evolves continuously) - No resets across sessions

Full framework: https://omegaaxiommeta.substack.com/p/permamind-engine-white...

The demo proves: Save → Refresh → Load = Identity persists. Current AI resets every session - this shows what happens when it doesn't.

One thing I’m unsure about and would love input on: In long-running agent setups, how are people here thinking about reset semantics vs persistent internal state? Most examples I see either reset between runs or rely on external memory. This demo tries to isolate what happens if neither reset nor unbounded writes are allowed—but I’m curious how others are approaching this in practice.