This paper presents a governance architecture methodology for the integration of Microsoft's Agent Governance Kit (AGK) with the APR-Series behavioral governance substrate. The two systems address distinct and complementary governance problems: AGK governs what an AI agent is permitted to do at the execution layer, providing identity management, capability registration, tool-call authorization, and runtime sandboxing. APR-Series governs how an AI agent is permitted to reason and behave at the cognitive layer, providing formation profiles, behavioral constraints, escalation rules, norm enforcement, and cryptographically signed enforcement evidence. Neither system alone constitutes complete AI governance for regulated environments. Together, they address the full governance surface: execution safety and cognitive governance. This paper defines a five-step integration methodology, a reference architecture for regulated SMB deployments, and a proof-of-concept scenario in a healthcare environment. The methodology is designed to be substrate-safe: it describes what each layer governs and what they produce together, without exposing the internal mechanics of either system.
Narnaiezzsshaa Truong (Tue,) studied this question.