Focus on this objective today: Plan an agent solution: Design agents for internal or external audiences. Explain it in your own words, apply it to one realistic scenario, and verify the details against the official source. Source context: Read in English Design advanced prompting strategies for production AI agents Module 10 Units Feedback Advanced AI Engineer Solution Architect Developer Azure Microsoft Foundry Design advanced prompting strategies for production AI agents in Microsoft Foundry. Implement multiturn reasoning architectures with dynamic context injection, build layered prompt injection defenses for untrusted input environments, design system prompt frameworks for complex agent persona and constraint control, and implement prompt versioning and optimization workflows. Learning objectives By the end of this module, you'll be able to: Design multiturn prompt architectures with dynamic context injection for complex agent reasoning tasks Implement layered prompt injection prevention strategies for agents processing untrusted content Build system prompt frameworks that control agent persona, behavior boundaries, autonomy levels, and escalation behavior Design multi-intervention guardrail architectures covering input, tool-call, tool-response, and output surfaces Apply prompt versioning and optimization workflows to maintain and improve agent quality over time Design fine-tuning strategies and data preparation pipelines for domain-specialized agent models Add Prerequisites Before starting this module, you should have: Experience designing system prompts and agent instructions in Microsoft Foundry Familiarity with chain-of-thought prompting and few-shot learning patterns Experience building agents with Microsoft Foundry Agent Service Proficiency in Python Get started with Azure Choose the Azure account that's right for you.
Objective
Plan an agent solution: Design agents for internal or external audiences