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Microsoft GitHub Agentic AI Developer : GH-600 Exam

GH-600 actual test
  • Exam Code: GH-600
  • Exam Name: GitHub Agentic AI Developer
  • Updated: Aug 21, 2026
  • Q & A: 85 Questions and Answers
  • PDF Demo
  • PC Test Engine
  • Online Test Engine
  • Total Price: $59.99  

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Microsoft GH-600 Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Orchestrate multi-agent coordination15–20%- 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
              - Lifecycle management
              • 1. Add/replace/retire agents safely
                Topic 2: Implement tool use and environment interaction20–25%- Agent tool configuration
                • 1. Select and configure tools
                  • 2. Configure tool permissions and scope
                    - 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. Scope agents to repositories or branches
                              • 2. Enable CI-based agent execution
                                • 3. Enable autonomous actions (PRs, branches)
                                  Topic 3: Evaluation, error analysis, and tuning15–20%- 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
                                          - Failure analysis
                                          • 1. Analyze logs, traces, and artifacts
                                            • 2. Classify reasoning, tool, and context errors
                                              Topic 4: Manage memory, state, and execution10–15%- Agent memory strategies
                                              • 1. Memory scoping and expiration rules
                                                • 2. Short-term vs long-term memory selection
                                                  - Cross-tool continuity
                                                  • 1. Prevent stale or conflicting context
                                                    • 2. Share state across tools and environments
                                                      - State persistence and drift control
                                                      • 1. Detect and correct context drift
                                                        • 2. Persist task progress as artifacts
                                                          Topic 5: 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. Enforce least-privilege execution
                                                                • 2. Require approvals for sensitive actions
                                                                  Topic 6: Prepare agent architecture and SDLC processes15–20%- 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
                                                                        - Planning vs execution boundaries
                                                                        • 1. Separate planning and execution phases
                                                                          • 2. Prevent execution before approval
                                                                            • 3. Validate structured agent plans
                                                                              - Observability and control
                                                                              • 1. Define autonomy levels and guardrails
                                                                                • 2. Enable human-in-the-loop controls
                                                                                  • 3. Produce inspectable artifacts in GitHub

                                                                                    Microsoft GitHub Agentic AI Developer Sample Questions:

                                                                                    1. 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.


                                                                                    2. 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) Add the internal docs as copilot-instructions.md
                                                                                    C) Connect an MCP server that exposes the internal documentation
                                                                                    D) Enable plan mode


                                                                                    3. You have a GitHub Enterprise repository.
                                                                                    An agent opens pull requests to the main branch.
                                                                                    You need to ensure that changes to .github/workflows/* and /infra/* require approval from designated reviewers before merge.
                                                                                    What should you configure?

                                                                                    A) a ruleset and a .copilotignore file
                                                                                    B) a branch protection rule and copilot-instructions.md
                                                                                    C) a branch protection rule and a CODEOWNERS file
                                                                                    D) a ruleset and an agents.md file


                                                                                    4. Hotspot Question
                                                                                    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 of the following statements, select Yes if the statement is true. Otherwise, select No.
                                                                                    NOTE: Each correct selection is worth one point.


                                                                                    5. You have a GitHub repository.
                                                                                    You use the GitHub Copilot CLI to run an agentic workflow from the terminal.
                                                                                    During execution, the conversation history approaches the context limit. The agent cannot continue the current session unless the amount of retained context is reduced.
                                                                                    You need to continue the current session without losing all the prior progress.
                                                                                    Which Copilot CLI slash command should you run?

                                                                                    A) /context
                                                                                    B) /clear
                                                                                    C) /yolo
                                                                                    D) /compact


                                                                                    Solutions:

                                                                                    Question # 1
                                                                                    Answer: Only visible for members
                                                                                    Question # 2
                                                                                    Answer: C
                                                                                    Question # 3
                                                                                    Answer: C
                                                                                    Question # 4
                                                                                    Answer: Only visible for members
                                                                                    Question # 5
                                                                                    Answer: D

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