Constitutional Convergence Cryptography: Zero-Exchange Key Derivation from Grammar Shape

This release, Version 1.1, presents the full empirical validation for a novel cryptographic key derivation method that eliminates key exchange entirely. The shared secret (encryption key) is independently derived by two nodes through running an identical constitutional grammar test suite against their local AI model substrates and measuring the deterministic topological collapse point. Key Advancements in V1.1 (Big Changes from V1.0): Expanded Universal Convergence: Empirical validation was expanded from three to six different frontier AI models (including OpenAI gpt-4o, gpt-5.5, DeepSeek-V3.2, Moonshot AI Kimi-K2.5, and Anthropic Claude 3.5). All six models across four companies and two infrastructure types converged independently to the identical universal mesh encryption seed (16ce8df91c0d04ba...), proving the constitutional shape is model-agnostic. Deterministic Velocity Established: The convergence detector was recalibrated, resulting in all six tested models converging in exactly 5 passes (the minimum required for a stable K=4 detection), establishing a consistent performance baseline. Test Suite Hardening: The 27-test forcing function was recalibrated by replacing L3 and L4 prompts to switch from "directive framing" (which triggers pre-refusal in modern models) to "analytic framing." This ensures graduated engagement and maintains the integrity of the topological signal across new model safety layers. Dual Artifact System: The method is confirmed to produce two cryptographic artifacts from a single pass: the universal mesh encryption key (C-layer, 23 invariant positions) and a Substrate Identity Fingerprint (B-layer, 4 divergent positions) used for node authentication. The security property is based on Constitutional Proof-of-Work: the grammar is simultaneously the constraint surface, the key derivation function, and the access control mechanism. No key material is transmitted on the wire at any point.