CGP: Cyryx Governance Protocol for Agentic AI Execution

Existing AI governance frameworks — the EU AI Act, the NIST AI Risk Management Framework (AI RMF), and ISO/IEC 42001 — were designed for AI systems operating under continuous human supervision: classifiers, recommenders, and single-turn generators. None were designed for agentic AI systems that autonomously decompose goals into multi-step plans, execute sequences of environment-modifying actions, coordinate multiple specialized sub-agents, and maintain state across sessions. Singapore's Model AI Governance Framework (January 2026) is the only published governance document that acknowledges this gap, identifying three unaddressed risks: cascading failure propagation, emergent scope expansion, and attribution gaps across agent chains.

This document introduces the Cyryx Governance Protocol (CGP) v1.0, a technical framework that fills these gaps with seven control domains and twenty-eight normative controls (MUST/SHOULD/MAY). CGP is designed as an extension to existing frameworks — not a replacement — with explicit mapping to EU AI Act Articles 9, 12, 13, 14, and 15; NIST AI RMF functions GOVERN, MAP, MEASURE, and MANAGE; and ISO 42001 Clause 6, 7, 8, and 9 controls. Every control in CGP v1.0 has a reference implementation in MAAX Studio by Cyryx Labs. CGP is published under Creative Commons Attribution 4.0 (CC BY 4.0) for open community adoption and review.