Engineering teams can build impressive AI agent prototypes in a few days. The real challenge starts when that agent needs to call internal tools, retrieve company knowledge, respect user permissions, ask for approval, and leave an audit trail that security and compliance teams can trust. Enterprise-ready agentic capabilities are less about one clever prompt and more about platform architecture.

This session is for platform engineers who need to turn isolated agent experiments into reusable enterprise capabilities. We will walk through a practical reference architecture for an agent platform built around MCP servers, retrieval and context layers, memory, permissions, approval flows, monitoring, and evaluation. Instead of showing another single-agent demo, this session focuses on the platform decisions behind production use: what should be shared across teams, how to avoid duplicated implementations, how to prevent tool sprawl, and how to keep governance from becoming a delivery bottleneck.

Attendees will leave with a reference model for building agent capabilities that are reusable, governable, and safe to operate. They will also get a checklist for deciding what belongs in the platform, what belongs in each agent, and where human-in-the-loop is still required.