AI agent governance at scale: from 5 agents to a 500-agent workforce

This post expands on the concept of agentic AI governance by detailing the infrastructure required to scale from a few agents to hundreds. It introduces the critical need for centralized agent identity, reusable policy propagation, and cross-environment enforcement. The post outlines specific control areas such as agent registry, identity, policy propagation, permission scope, tool access, component lineage, runtime enforcement, monitoring, audit trails, and review triggers. It highlights how these infrastructure components address the breakdown of manual governance as agent workforces grow and spread across teams, tools, data sources, and environments.