Microsoft AI-500 Exam : Designing and Implementing Multi-Agent AI Solutions

AI-500
  • Exam Code: AI-500
  • Exam Name: Designing and Implementing Multi-Agent AI Solutions
  • Updated: Jul 29, 2026
  • Q & A: 0 Questions and Answers

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Microsoft AI-500 Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Architect multi-agent solutions15–20%- Design logical architecture for multi-agent systems
  • 1. Specify autonomy levels and guardrails
    • 2. Design agent communication and handoff protocols
      • 3. Define agent patterns and roles
        - Design workflow and tool integration
        • 1. Apply responsible AI principles
          • 2. Incorporate human-in-the-loop oversight
            • 3. Plan tool ecosystems and permissions
              Topic 2: Evaluate, optimize, and monitor multi-agent solutions20–25%- Assess performance and reliability
              • 1. Optimize latency and scalability
                • 2. Diagnose failures and bottlenecks
                  • 3. Define and measure success metrics
                    - Implement observability
                    • 1. Monitor agent interactions and outcomes
                      • 2. Enable logging and tracing
                        • 3. Use Azure-native monitoring tools
                          Topic 3: Develop multi-agent solutions in Azure30–35%- Manage state and memory
                          • 1. Use frameworks like Microsoft Agent Framework and MCP
                            • 2. Handle multi-turn conversations
                              • 3. Configure short-term and long-term memory
                                - Implement agents using Azure AI services
                                • 1. Integrate tools, plugins, and APIs
                                  • 2. Build agents with Azure AI Agent Service
                                    • 3. Orchestrate workflows with Azure AI Foundry
                                      Topic 4: Secure, govern, and deploy multi-agent solutions20–25%- Deploy and maintain solutions
                                      • 1. Implement versioning and update strategies
                                        • 2. Manage lifecycle and retirement
                                          • 3. Deploy agents to production environments
                                            - Apply security and compliance
                                            • 1. Configure authentication and access control
                                              • 2. Manage governance and audit requirements
                                                • 3. Enforce data protection and privacy

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