Building an AI agent is the easy part. Deciding how to host it, how much control you need over its behavior, how to extend it with tools, and how to understand what it is doing at runtime is where things get interesting.

In this developer-focused session, we’ll use Microsoft Foundry to explore the engineering decisions involved in moving an agent beyond the prototype. We’ll compare prompt-based agents with code-based hosted agents, examine when greater control is worth the additional complexity, and use Microsoft Agent Framework to build and deploy a code-based agent.

We’ll then extend our agents with tools and dig into runtime observability by tracing requests, inspecting tool calls, debugging unexpected behavior, and understanding how an agent reached a result.

Through code and practical demos, you’ll leave with a clearer mental model for choosing an agent architecture and the techniques needed to build, extend, debug, and operate agents beyond the initial prompt.