Architect multi-agent solutions
15–20% - Decompose goals into agents, tools, workflows, memory, and human-in-the-loop controls.
- Specify protocols, Zero Trust identity scoping, and persistence for session, team, and long-term memory.
- Choose compute, observability, and developer tooling for production multi-agent systems.
Practice Architect Multi-Agent Solutions Questions →
Develop multi-agent solutions in Azure
30–35% - Implement prompt, memory, RAG, and knowledge strategies across agents.
- Build MCP servers and clients, tool validation, and fallback handling.
- Orchestrate hub-and-spoke, sequential, parallel, and Agent2Agent patterns with Agent Framework, LangChain, or LangGraph.
Practice Develop Multi-Agent Solutions Questions →
Evaluate, optimise, and monitor multi-agent solutions
20–25% - Design human review, memory, tool, and prompt evaluations in Foundry.
- Diagnose context-window issues, token cost, drift, and quality regression.
- Implement tracing, SLAs, and continuous improvement loops.
Practice Evaluate, Optimize & Monitor Questions →
Secure, govern, and deploy multi-agent solutions
20–25% - Implement identity, OAuth, Key Vault, and shift-left security including red teaming.
- Design guardrails for inputs, tool calls, and outputs.
- Release with DTAP, blue/green or canary, CI/CD, and automated tests.
Practice Secure, Govern & Deploy Questions →