Agentic AI is rapidly transforming DevOps—from code generation to incident response—but enterprises face a critical challenge: how to adopt these systems without introducing new risks. This session presents a practical, production-focused framework for evaluating and implementing agentic AI in enterprise DevOps environments.
Drawing from real-world architecture and release governance practices, we explore how to assess agentic systems across key dimensions such as security, reliability, cost, and operational fit. The session also introduces actionable guardrails, including role-based access control, approval workflows, auditability, and release readiness validation, ensuring that autonomous actions remain controlled and compliant.
Attendees will gain a clear approach to classify agent behaviors, define accountability metrics, and integrate AI safely into CI/CD pipelines without compromising stability or trust. The goal is to move beyond experimentation and enable confident, scalable adoption of agentic AI in enterprise DevOps.