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Microsoft GH-600 Exam Syllabus Topics:

SectionWeightObjectives
Design agentic AI solutions25%- Define requirements for agentic systems
  • 1. Plan for responsible AI and governance
    • 2. Identify use cases and scenarios
      • 3. Define functional and non-functional requirements
        - Design agent architecture
        • 1. Select agent patterns and topologies
          • 2. Plan tool integration and orchestration
            • 3. Design memory and state management
              Integrate tools, data, and services25%- Incorporate external tools and APIs
              • 1. Handle authentication and error resilience
                • 2. Design and register tool definitions
                  • 3. Implement function calling and service integration
                    - Connect data sources and knowledge bases
                    • 1. Ensure data security and access control
                      • 2. Integrate vector databases and search
                        • 3. Implement retrieval-augmented generation (RAG)
                          Test, deploy, and monitor agentic AI systems20%- Deploy and monitor agents at scale
                          • 1. Deploy to Azure AI and cloud environments
                            • 2. Optimize cost, latency, and throughput
                              • 3. Implement logging, telemetry, and observability
                                - Validate agent performance and safety
                                • 1. Test reasoning accuracy and consistency
                                  • 2. Evaluate quality metrics and iterate
                                    • 3. Apply guardrails and content safety
                                      Implement agents and multi-agent systems30%- Build agents with Azure AI tools and frameworks
                                      • 1. Integrate models and prompts
                                        • 2. Develop using Semantic Kernel and Azure AI Foundry
                                          • 3. Implement agent logic and reasoning
                                            - Orchestrate multi-agent collaboration
                                            • 1. Define communication protocols between agents
                                              • 2. Implement workflows and coordination strategies
                                                • 3. Manage agent handoffs and task distribution

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                                                  Microsoft Developing in Agentic AI Systems Sample Questions (Q73-Q78):

                                                  NEW QUESTION # 73
                                                  After several long agentic sessions, you notice degraded response quality and want the agent to retain a concise summary of prior progress rather than the full raw history, while continuing without interruption. Which approach addresses this?

                                                  Answer: D

                                                  Explanation:
                                                  /compact summarizes the existing conversation history via the model and replaces the raw history with the condensed summary, preserving continuity and prior progress while freeing up context window space -- unlike /clear, which discards everything.


                                                  NEW QUESTION # 74
                                                  You have a GitHub repository that uses a custom GitHub Copilot coding agent defined in the rollout-bot.agent.md file.
                                                  You need to update a workflow so that agent-profile changes can be rolled back by reverting a single commit and rerunning the workflow. The workflow must check out the exact commit being deployed and apply the agent profile from the repository at that commit.
                                                  How should you complete the workflow? To answer, drag the appropriate values to the correct targets. Each value may be used once, more than once, or not at all. You may need to drag the split bar between panes or scroll to view content.
                                                  NOTE: Each correct selection is worth one point.

                                                  Answer:

                                                  Explanation:


                                                  NEW QUESTION # 75
                                                  You have multiple GitHub Copilot coding agents that run tasks concurrently.
                                                  You are monitoring the agents from the terminal by using the GitHub CLI.
                                                  An agent appears stalled.
                                                  You need to live stream the session log output.
                                                  What should you do?

                                                  Answer: A

                                                  Explanation:
                                                  To live stream the session log output of a background agent, you must run the gh agent-task view
                                                  <task-id> --log --follow command.
                                                  Command Syntax
                                                  gh agent-task view <task-id> --log --follow
                                                  Parameter Breakdown
                                                  <task-id>: The unique identifier of the stalled agent task. If you do not know the ID, run gh agent- task list first to look it up.
                                                  --log: Instructs the GitHub CLI to pull the specific execution and reasoning logs rather than just a summary of the task state.
                                                  --follow: Tells the CLI to keep the connection open and live stream new log events to your terminal in real-time as they happen.
                                                  Reference:
                                                  https://docs.github.com/en/copilot/how-tos/copilot-on-github/use-copilot-agents/manage-and-track-agents


                                                  NEW QUESTION # 76
                                                  Your team uses a remote GitHub Model Context Protocol (MCP) server for workflows in the software development life cycle (SDLC).
                                                  You need to commit a workspace-scoped MCP configuration to ensure that GitHub Copilot can connect to the GitHub-hosted MCP endpoint and authenticate by using a GitHub personal access token (PAT).
                                                  How should you complete the mcp.json configuration file? To answer, drag the appropriate values to the correct targets. Each value may be used once, more than once, or not at all. You may need to drag the split bar between panes or scroll to view content.
                                                  NOTE: Each correct selection is worth one point.

                                                  Answer:

                                                  Explanation:


                                                  NEW QUESTION # 77
                                                  You have a GitHub repository that uses GitHub Actions to run an autonomous coding-agent workflow.
                                                  Your team requires that session logs be captured as workflow artifacts so that agent runs can be audited and traced back to a specific execution and code state.
                                                  How should you complete the workflow? To answer, drag the appropriate values to the correct targets.

                                                  Answer:

                                                  Explanation:


                                                  NEW QUESTION # 78
                                                  ......

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