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Microsoft GH-600 Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Prepare agent architecture and SDLC processes15–20%- Observability and control
  • 1. Produce inspectable artifacts in GitHub
    • 2. Enable human-in-the-loop controls
      • 3. Define autonomy levels and guardrails
        - Integrate agents into SDLC workflows
        • 1. Define inputs, outputs, and success criteria
          • 2. Identify and mitigate agent anti-patterns
            • 3. Define agent steps in SDLC
              - Planning vs execution boundaries
              • 1. Prevent execution before approval
                • 2. Validate structured agent plans
                  • 3. Separate planning and execution phases
                    Topic 2: Evaluation, error analysis, and tuning15–20%- Tuning agent behavior
                    • 1. Optimize memory usage and constraints
                      • 2. Refine prompts, tools, and workflows
                        - Define evaluation criteria
                        • 1. Define success metrics and constraints
                          • 2. Generate automated evaluation signals
                            - Failure analysis
                            • 1. Classify reasoning, tool, and context errors
                              • 2. Analyze logs, traces, and artifacts
                                Topic 3: Implement guardrails and accountability10–15%- Guardrails and human-in-the-loop
                                • 1. Enforce least-privilege execution
                                  • 2. Require approvals for sensitive actions
                                    - Autonomy and risk levels
                                    • 1. Assign autonomy levels with compliance constraints
                                      • 2. Classify agent actions by risk
                                        Topic 4: Implement tool use and environment interaction20–25%- Safe execution and error handling
                                        • 1. Escalation paths and traceability
                                          • 2. Retries and rollback strategies
                                            - Development environment integration
                                            • 1. Scope agents to repositories or branches
                                              • 2. Enable CI-based agent execution
                                                • 3. Enable autonomous actions (PRs, branches)
                                                  - 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
                                                          Topic 5: Manage memory, state, and execution10–15%- Agent memory strategies
                                                          • 1. Short-term vs long-term memory selection
                                                            • 2. Memory scoping and expiration rules
                                                              - 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
                                                                      Topic 6: Orchestrate multi-agent coordination15–20%- Lifecycle management
                                                                      • 1. Add/replace/retire agents safely
                                                                        - Failure handling and recovery
                                                                        • 1. Implement rollback and recovery patterns
                                                                          • 2. Detect stalled or degraded agents
                                                                            - Observability and auditability
                                                                            • 1. Generate logs and artifacts for review
                                                                              • 2. Document agent handoffs and decisions
                                                                                - Multi-agent workflows
                                                                                • 1. Coordinate parallel agent execution
                                                                                  • 2. Resolve conflicts and overlaps

                                                                                    Microsoft GitHub Agentic AI Developer Sample Questions:

                                                                                    1. An agentic coding session in the terminal has grown too long, and you want to discard all prior conversation history and start clean, without summarization. Which slash command should you run?

                                                                                    A) /usage
                                                                                    B) /reset-context
                                                                                    C) /compact
                                                                                    D) /clear


                                                                                    2. You use a GitHub Actions workflow to orchestrate a multi-agent draft-review process for pull requests. The workflow uploads a single combined review-package artifact at the end of each run.
                                                                                    You discover that the review-package artifact is occasionally missing from the workflow run history, and you suspect that a user deleted it.
                                                                                    You need to identify which user manually deleted a workflow run artifact and when the deletion occurred.
                                                                                    What should you use?

                                                                                    A) the checks.delete_logs audit log event
                                                                                    B) the artifact.destroy audit log event
                                                                                    C) the merge commit history
                                                                                    D) the pull request description and comment history


                                                                                    3. Your team wants Copilot's suggestions to reflect knowledge of internal library APIs that are not publicly documented and not present in the codebase being edited. What is the most appropriate solution?

                                                                                    A) Use .copilotignore to hide public APIs
                                                                                    B) Connect an MCP server that exposes the internal documentation
                                                                                    C) Add the internal docs as copilot-instructions.md
                                                                                    D) Enable plan mode


                                                                                    4. Case Study 2
                                                                                    Existing Environment
                                                                                    GitHub Environment
                                                                                    The GitHub environment contains the following:
                                                                                    - Three repositories named product-api, billing-service, and infra-terraform.
                                                                                    - Branch protection on the main branch in all repositories that requires at least one pull request review before merging
                                                                                    - GitHub Actions runners used across all workflows
                                                                                    - A GitHub team named SG_Dev that contains developers
                                                                                    - A GitHub team named SG_Review that contains senior engineers and a security team
                                                                                    - A .github/copilot-instructions.md file that includes general coding conventions for all features Agent environment The product-api repository uses a GitHub Copilot coding agent named agent1 that has the following configurations:
                                                                                    - No custom agent profile is defined.
                                                                                    - A Model Context Protocol (MCP) server named MCP1 is deployed to
                                                                                    https://mcp.litwareinc.internal and provides access to internal ticketing and deployment APIs.
                                                                                    MCP1 requires an API key for authentication.
                                                                                    A second Copilot coding agent named agent2 handles changes in infra-terraform and runs in parallel with agent1 when both agents have open assigned issues.
                                                                                    Copilot memory is NOT enabled for the organization.
                                                                                    Problem Statements
                                                                                    Litware identifies the following issues:
                                                                                    - During two recent sessions, agent1 accessed files in billing-service, which is outside the agent's intended scope.
                                                                                    - agent1 makes code changes immediately after receiving a task.
                                                                                    - A developer named Ben, who is on the SG_Dev team, reports that agent1 completed a session with a successful status and opened a pull request, but the pull request contains no file changes.
                                                                                    Other developers report this intermittently as well.
                                                                                    - Both agent1 and agent2 modified shared/config.yaml in a parallel test run, generating conflicting outputs.
                                                                                    agent1 consistently uses raw try-catch blocks for error handling, which violates the defined implementation guidelines of SG_Dev.
                                                                                    Requirements
                                                                                    Planned Changes
                                                                                    Litware plans to make the following changes:
                                                                                    - Ensure that agent1 can access all the tools in the environment.
                                                                                    - Provide product-api with specific instructions to agent1 without affecting Copilot Chat or Copilot code review.
                                                                                    - Configure MCP1 as a tool for agent1 by modifying the product-api repository MCP configuration.
                                                                                    - Ensure that Copilot retains details that it has learned and uses that knowledge for future work.
                                                                                    This must be applied to all licensed members of the organization.
                                                                                    Implementation guidelines
                                                                                    The development team at Litware identifies the following implementation guidelines:
                                                                                    - Agent workflows must be able to run in parallel.
                                                                                    - Application error handling must use the repository ErrorHandler class.
                                                                                    - agent1 and agent2 must run on isolated branches during parallel execution. File-level conflicts must be detected before merges, and both agents must be able to run concurrently.
                                                                                    Security requirements
                                                                                    Litware identifies the following security requirements:
                                                                                    - Only the members of SG_Review must be able to approve agent1 plan outputs.
                                                                                    - All API keys must be stored and accessed securely.
                                                                                    - The developers must NOT be able to self-approve.
                                                                                    Agent configuration

                                                                                    You need to troubleshoot the issue reported by Ben.
                                                                                    What should you review?

                                                                                    A) the GitHub Actions runner log for the session job
                                                                                    B) the GITHUB_TOKEN permissions block in the agent1 workflow
                                                                                    C) the GitHub Actions usage metrics of repo1
                                                                                    D) the agent session log in the Agents panel


                                                                                    5. You want the GitHub Copilot coding agent to follow project-specific conventions (coding style, testing requirements, folder structure) on every task it performs in a repository. What should you create?

                                                                                    A) A CODEOWNERS file
                                                                                    B) A copilot-instructions.md file in .github/
                                                                                    C) A .copilotignore file
                                                                                    D) A agents.yml workflow file


                                                                                    Solutions:

                                                                                    Question # 1
                                                                                    Answer: D
                                                                                    Question # 2
                                                                                    Answer: B
                                                                                    Question # 3
                                                                                    Answer: B
                                                                                    Question # 4
                                                                                    Answer: D
                                                                                    Question # 5
                                                                                    Answer: B

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