Many AI agent architectures fail not because of model quality, but because they start too complex too early. In this session, we take a stage-based approach to building AI agents using Azure AI Foundry, focusing on maximum efficiency in design and implementation.

We’ll start with a single, task-focused agent and evolve it step by step into a central orchestrator agent that owns the UI and coordination logic, while delegating specialized work to backend agents. You’ll learn when a single agent is enough, when orchestration becomes necessary, and how to introduce additional agents without rewriting your system.

The session emphasizes practical architecture evolution, showing how to minimize cognitive load, reduce prompt complexity, and improve maintainability — all while staying fully aligned with the Microsoft AI stack