This chapter explores the challenges of transitioning agentic AI systems from controlled laboratory environments to live enterprise production. Using the continuous case study of a logistics firm deploying an agent named “Logi-Agent,” it deconstructs the “deployment chasm” between developer optimism and the unforgiving realities of corporate security and compliance. The chapter provides a practical framework for this transition, detailing the necessary evolution of a Security Operations Center (SOC) to become “agent-aware” through contextual logging and advanced threat detection. It advocates for the adoption of secure, standardized protocols like MCP for agent-to-tool interaction and A2A for inter-agent communication, and it outlines patterns for safely integrating agents with brittle legacy systems. Central to this framework is the establishment of robust governance, including an Agent Review Board and tiered human-in-the-loop controls to ensure auditable autonomy. Finally, it synthesizes these technical and procedural pillars into a cohesive “Secure AgentOps” pipeline and emphasizes the critical importance of organizational change management, including the upskilling of staff to become effective “agent handlers” and “AI detectives.”