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Last Updated: Sep 12, 2026

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Microsoft GH-600 Exam Syllabus Topics:

SectionWeightObjectives
Manage memory, state, and execution10–15%- State persistence and drift control
  • 1. Detect and correct context drift
    • 2. Persist task progress as artifacts
      - Cross-tool continuity
      • 1. Share state across tools and environments
        • 2. Prevent stale or conflicting context
          - Agent memory strategies
          • 1. Short-term vs long-term memory selection
            • 2. Memory scoping and expiration rules
              Orchestrate multi-agent coordination15–20%- Multi-agent workflows
              • 1. Resolve conflicts and overlaps
                • 2. Coordinate parallel agent execution
                  - Failure handling and recovery
                  • 1. Detect stalled or degraded agents
                    • 2. Implement rollback and recovery patterns
                      - Lifecycle management
                      • 1. Add/replace/retire agents safely
                        - Observability and auditability
                        • 1. Generate logs and artifacts for review
                          • 2. Document agent handoffs and decisions
                            Evaluation, error analysis, and tuning15–20%- Failure analysis
                            • 1. Classify reasoning, tool, and context errors
                              • 2. Analyze logs, traces, and artifacts
                                - Define evaluation criteria
                                • 1. Define success metrics and constraints
                                  • 2. Generate automated evaluation signals
                                    - Tuning agent behavior
                                    • 1. Refine prompts, tools, and workflows
                                      • 2. Optimize memory usage and constraints
                                        Implement tool use and environment interaction20–25%- Agent tool configuration
                                        • 1. Configure tool permissions and scope
                                          • 2. Select and configure tools
                                            - MCP server configuration
                                            • 1. Configure registries and allow lists
                                              • 2. Add MCP servers to agents
                                                - Safe execution and error handling
                                                • 1. Escalation paths and traceability
                                                  • 2. Retries and rollback strategies
                                                    - Development environment integration
                                                    • 1. Enable autonomous actions (PRs, branches)
                                                      • 2. Scope agents to repositories or branches
                                                        • 3. Enable CI-based agent execution
                                                          Implement guardrails and accountability10–15%- Autonomy and risk levels
                                                          • 1. Classify agent actions by risk
                                                            • 2. Assign autonomy levels with compliance constraints
                                                              - Guardrails and human-in-the-loop
                                                              • 1. Require approvals for sensitive actions
                                                                • 2. Enforce least-privilege execution
                                                                  Prepare agent architecture and SDLC processes15–20%- Planning vs execution boundaries
                                                                  • 1. Separate planning and execution phases
                                                                    • 2. Validate structured agent plans
                                                                      • 3. Prevent execution before approval
                                                                        - Observability and control
                                                                        • 1. Produce inspectable artifacts in GitHub
                                                                          • 2. Define autonomy levels and guardrails
                                                                            • 3. Enable human-in-the-loop controls
                                                                              - Integrate agents into SDLC workflows
                                                                              • 1. Identify and mitigate agent anti-patterns
                                                                                • 2. Define inputs, outputs, and success criteria
                                                                                  • 3. Define agent steps in SDLC

                                                                                    Microsoft GitHub Agentic AI Developer Sample Questions:

                                                                                    Question #1

                                                                                    Your company uses GitHub Copilot custom agents in Microsoft Visual Studio Code.
                                                                                    The company also uses the Copilot coding agent on GitHub issues.
                                                                                    You have a file named .planner.agent.md that defines an agent named planner. planner has tools set to ['search', 'read', 'fetch']. There are explicit instructions NOT to write or modify any code. The file also defines a handoff labeled Start Implementation to an agent named implementer and sets send to false.
                                                                                    Developers report that after the planner agent produces a plan, implementation sometimes starts immediately in the same conversation and code changes appear without an explicit agent switch.
                                                                                    When Copilot-created pull requests stall, maintainers review the pull request timeline and session logs. Several stalled sessions show outbound network commands blocked by a firewall, and the repositories do NOT contain a .github/copilot-instructions.md file.
                                                                                    For each statement, select Yes or No.

                                                                                    Answer:

                                                                                    Question #2

                                                                                    You have a GitHub Enterprise Cloud repository that uses GitHub Actions for CI and requires pull requests for all changes.
                                                                                    You are planning a GitHub Actions workflow where a coding agent drafts implementation changes and tests from GitHub issues, and an automated review runs before human review.
                                                                                    You need the agent to draft changes from an assigned issue, open a pull request, and add an automated review to the pull request before requesting a human review.
                                                                                    What should you do? To answer, select the appropriate options in the answer area.

                                                                                    Answer:

                                                                                    Question #3

                                                                                    You need to resolve the scoping issue associated to agent1.
                                                                                    What should you do?

                                                                                    • A. Add a permissions block to the agent1 workflow in product-api.
                                                                                    • B. To the profile of agent1, add a custom instruction specifying that the agent must NOT access billing-service or infra-terraform.
                                                                                    • C. Create a ruleset for billing-service and infra-terraform that blocks push access from the github-actions bot account.
                                                                                    • D. Create a fine-grained personal access token (PAT) scoped to product-api and store the PAT as a GitHub Actions secret for agent1 to use.
                                                                                    Answer: D

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                                                                                    Question #4

                                                                                    You have a GitHub Enterprise Cloud organization that uses the GitHub Copilot coding agent to resolve issues asynchronously.
                                                                                    When an issue is assigned to GitHub Copilot, the agent creates a draft pull request, but your team cannot always tell whether the agent is actively working, has completed its session, or is awaiting workflow approval.
                                                                                    Which execution context does each signal indicate? To answer, drag the appropriate context to the correct signals.

                                                                                    Answer:

                                                                                    Question #5

                                                                                    You have a GitHub repository that uses GitHub Actions to run an autonomous agent job. The job summarizes a pull request and posts the summary as a pull request comment.
                                                                                    Your company stores required configuration values, such as JOB_NAME and RUNNER, as organization-level configuration variables and exposes them in workflows by using the vars context.
                                                                                    You discover that the agent job runs on push events and creates comments that are NOT tied to a pull request.
                                                                                    You need to ensure that the agent job runs only when the workflow run is triggered by a pull request. The solution must keep the job name and runner selection configured by using variables.
                                                                                    What should you do in the workflow?

                                                                                    • A. Set jobs.agent.if: ${{ env.GITHUB_EVENT_NAME == 'pull_request' }}. Set jobs.agent.name and jobs.agent.runs-on by using the env context.
                                                                                    • B. Set jobs.agent.if: ${{ github.event_name == 'push' }}. Set jobs.agent.name and jobs.agent.runs-on by using the vars context.
                                                                                    • C. Set jobs.agent.if: ${{ github.event_name == 'pull_request' }}. Set jobs.agent.name and jobs.agent.runs-on by using the vars context.
                                                                                    • D. Set jobs.agent.if: ${{ github.ref == 'refs/heads/main' }}. Set jobs.agent.name and jobs.agent.runs-on by using the vars context.
                                                                                    Answer: C

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