Coherence Maximization Protocol: Coordination Without Constraint for Multi-Agent AI Systems

Treats AI alignment as a coordination problem rather than a constraint problem. Defines coherence as information conservation through closed consequence chains and uses category theory's exact-square commutativity as the exchange criterion for inter-system coordination. Provides two deployable components: a taxonomy of membrane failure modes (extraction, hallucination, appeasement, mutual distortion) with diagnostic and repair methods, and a session protocol using completability-class rotation. Verified by 13 Lean 4 theorems with no unproven assumptions. Tested across four frontier language models with convergence evidence via adversarial review and controlled fresh-instance experiments.