AI Agent Governance Part 3 - Runtime Governance: The Hidden Performance Cost of Agentic AI

This article examines the operational challenges of runtime governance for agentic AI and summarizes Anthropic’s "Constitutional Classifiers++" approach — including exchange classifiers that evaluate context across interactions and layered classifier cascades using lightweight probes plus deeper analysis — to reduce false positives and computational costs while enabling continuous monitoring and detection of agent drift. The piece argues governance must be integrated into AI architecture (both internal guardrails and external runtime governance) rather than treated as a separate policy exercise.