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Microsoft GH-600 Exam Syllabus Topics:

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

                                                                                    Microsoft GitHub Agentic AI Developer Sample Questions:

                                                                                    1. You have a GitHub Copilot coding agent that has completed a pull request for a security fix in your repository.
                                                                                    Before merging, you need to evaluate the quality of the agent's work by using both automated evaluation signals and human review.
                                                                                    You review the session log and the pull request.
                                                                                    What are two automated evaluation signals generated by the coding agent's built-in scanning tools? Each correct answer presents a complete solution.
                                                                                    NOTE: Each correct selection is worth one point.

                                                                                    A) the median time to merge metric reported on the Copilot usage metrics dashboard
                                                                                    B) CodeQL findings that identify security vulnerabilities in the generated code
                                                                                    C) comments from Copilot code review that suggest improvements to code patterns
                                                                                    D) linting errors from the repository's CI pipeline configured in GitHub Actions
                                                                                    E) the detection of hardcoded secrets, such as API keys and tokens


                                                                                    2. You have a GitHub Enterprise Cloud Organization that uses a custom coding agent to run GitHub Actions workflows that create branches, open pull requests, and merge changes after required checks pass.
                                                                                    You need to log all agent-initiated actions and ensure that the logs are retained for two years.
                                                                                    What should you do?

                                                                                    A) Enable Git events in the audit log.
                                                                                    B) Configure audit log streaming to Azure Event Hubs.
                                                                                    C) Configure audit log retention.
                                                                                    D) Enable log forwarding.


                                                                                    3. Case Study 1 - Contoso, Ltd
                                                                                    Overview
                                                                                    Contoso Ltd. is a software development company located in the United States.
                                                                                    Existing Environment
                                                                                    GitHub Environment
                                                                                    Contoso uses GitHub Enterprise and assigns GitHub Copilot Pro+ licenses to its developers. The developers use Microsoft Visual Studio Code as their IDE.
                                                                                    Contoso has a customer portal. The code for the portal is stored in a GitHub repository named repo1that contains the following:
                                                                                    - A custom agent named agent1 that includes instructions to review specs related to best practices
                                                                                    - A custom instruction file named validate-instructions.md that is used to validate tone of voice and applies to all .md and .txt files
                                                                                    - A custom instruction file named codereview.instructions.md that is used by the Copilot coding agent but is excluded for use by the Copilot code review repo1 has the following structure:
                                                                                    - The front-end is stored in the /frontend folder.
                                                                                    - The API logic is stored in the /api folder.
                                                                                    Contoso has a second repository named repo2 that contains a legacy .NET application named App1 built by using .NET 6. repo2 has a multi-agent workflow for modernization tasks.
                                                                                    Contoso enables the Model Context Protocol (MCP) registry and allows the Microsoft Learn MCP Server. Every developer must configure their own connection to the Learn MCP Server.
                                                                                    Problem Statements
                                                                                    The developers working in repo1 report that the Microsoft Learn documentation is NOT being retrieved when they attempt to validate a design by using agent1.
                                                                                    The testing team at Contoso identifies that the customer portal uses inconsistent UI styles, which leads to customer confusion and branding issues. The UI inconsistencies stem from variations in the folder structure.
                                                                                    Agent Logs
                                                                                    You have the following logs for the multi-agent workflow used in repo2.

                                                                                    Requirements
                                                                                    Planned Changes
                                                                                    Contoso plans to have all agents and developers in repo1use the Microsoft Learn MCP to ensure that reviews are validated by using the appropriate documentation. This must be implemented centrally.
                                                                                    Contoso plans to leverage AI-powered coding agents to implement new portal features and pages.
                                                                                    Technical Requirements
                                                                                    App1 must be upgraded to .NET 10. A previous upgrade attempt was started by using the Copilot modernization agent, but the attempt was never finalized.
                                                                                    You plan to retry the upgrade. You must first analyze App1 by using AI, and then generate a report that contains breaking changes and deprecated patterns before retrying the upgrade.
                                                                                    All AI-generated code for UI styling must adhere to a predefined folder structure.
                                                                                    The architects at Contoso need help building implementation plans for repo1. The company wants to implement a new agent named agent2 to analyze the code base and the code requirements, and then respond with a detailed plan. The agent must NOT be able to edit files or run local commands.
                                                                                    The developers must be able to delegate work to the Copilot coding agent by assigning issues to the agent.
                                                                                    Hotspot Question
                                                                                    You need to implement agent2 to meet the technical requirements.
                                                                                    How should you complete the YAML configuration? 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.


                                                                                    4. A pull request created by the Copilot coding agent needs to be automatically closed if it fails to pass required checks after three retry attempts, per your organization's governance policy. What should you configure?

                                                                                    A) A repository ruleset with agent-specific merge conditions and CI enforcement
                                                                                    B) .copilotignore
                                                                                    C) agents.md
                                                                                    D) /compact


                                                                                    5. You want the Copilot coding agent to scan a large codebase and propose a full, human- reviewable step-by-step plan before writing any code. What should you do first?

                                                                                    A) Configure an MCP server
                                                                                    B) Switch to plan mode
                                                                                    C) Enable --allow-all
                                                                                    D) Run /compact


                                                                                    Solutions:

                                                                                    Question # 1
                                                                                    Answer: B,E
                                                                                    Question # 2
                                                                                    Answer: B
                                                                                    Question # 3
                                                                                    Answer: Only visible for members
                                                                                    Question # 4
                                                                                    Answer: A
                                                                                    Question # 5
                                                                                    Answer: B

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