Design stateful agentic loops with Microsoft Foundry Agent Service
Advanced
AI Engineer
Solution Architect
Azure
Microsoft Foundry
Foundry Agent Service
Design stateful agentic loops for production AI systems. Implement run-status handling and context accumulation, configure agent reflection and planning cycles, architect session state persistence, build fork-based session patterns, and migrate Agents v1 workloads to the Agents v2 Responses API.
Learning objectives
By the end of this module, you'll be able to:
- Design agentic loop patterns that handle run-status signals and accumulate context across iterations
- Implement agent reflection and planning cycles for multi-step reasoning
- Architect session state management strategies for persistent multi-turn agent interactions
- Build fork-based session patterns to support conversation branching and resumption
- Describe the Agents v2 runtime model including agents, conversations, responses, and items
- Migrate stateful agentic loop code from Agents v1 to Agents v2 using the azure-ai-projects 2.x SDK
Prerequisites
Before starting this module, you should have:
- Experience building and deploying AI agents with Microsoft Foundry Agent Service
- Familiarity with agent runs, threads, and message management in the Microsoft Foundry Agent Service SDK
- Proficiency in Python
- 4+ years of AI/ML development experience
- No prior experience with Agents v2 or the Responses API is required — this module teaches those concepts from the ground up.
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