Governance is the platform problem worth solving

Governing AI agents in software delivery requires moving beyond human-centric policies toward automated, context-aware frameworks. As organizations integrate agents into DevOps, testing, and observability, the primary challenge shifts from writing code to ensuring secure, reliable, and compliant production deployments. Effective governance demands cross-functional collaboration—specifically aligning security, legal, and finance teams—to establish clear guardrails and identity management for agents. Rather than relying on generic metrics, engineering leaders should adopt a "theory of change" that maps AI activities to business outcomes, utilizing tools like DORA and SPACE to track velocity and quality. Ultimately, successful implementation relies on granular access controls, consistent policy enforcement, and a balanced measurement framework that prevents unauthorized agent behavior while maintaining developer experience and operational efficiency.