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Microsoft GH-600 Exam Overview:

Certification Vendor:Microsoft / GitHub
Exam Name:Developing in Agentic AI Systems (GH-600) - GitHub Agentic AI Developer
Exam Number:GH-600
Related Certifications:GitHub Copilot Certification
GitHub Advanced Security Certifications
Exam Duration:120 minutes
Exam Format:Multiple choice, Scenario-based questions, Drag and drop, Case studies, Interactive exam components
Certificate Validity Period:1 year (renewable annually)
Passing Score:700 (scaled score)
Available Languages:English
Recommended Training:Microsoft Learn - GH-600 Study Guide
GitHub Advanced Security learning paths
Exam Registration:Schedule exam (Pearson VUE via Microsoft credentials portal)
Official certification page (Microsoft Learn)
Sample Questions:Microsoft GH-600 Sample Questions
Exam Way:Online proctored exam via Pearson VUE; interactive and scenario-based tasks included.
Pre Condition:Experience with SDLC workflows, GitHub Actions, GitHub Copilot, and basic AI agent concepts (tool use, orchestration, and prompt-driven systems).
Official Syllabus URL:https://learn.microsoft.com/en-us/credentials/certifications/agentic-ai-developer/

Microsoft GH-600 Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: 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. Memory scoping and expiration rules
            • 2. Short-term vs long-term memory selection
              Topic 2: Evaluation, error analysis, and tuning15–20%- Failure analysis
              • 1. Classify reasoning, tool, and context errors
                • 2. Analyze logs, traces, and artifacts
                  - Tuning agent behavior
                  • 1. Optimize memory usage and constraints
                    • 2. Refine prompts, tools, and workflows
                      - Define evaluation criteria
                      • 1. Generate automated evaluation signals
                        • 2. Define success metrics and constraints
                          Topic 3: 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
                                - Planning vs execution boundaries
                                • 1. Prevent execution before approval
                                  • 2. Validate structured agent plans
                                    • 3. Separate planning and execution phases
                                      - Integrate agents into SDLC workflows
                                      • 1. Define agent steps in SDLC
                                        • 2. Identify and mitigate agent anti-patterns
                                          • 3. Define inputs, outputs, and success criteria
                                            Topic 4: Implement guardrails and accountability10–15%- Autonomy and risk levels
                                            • 1. Assign autonomy levels with compliance constraints
                                              • 2. Classify agent actions by risk
                                                - Guardrails and human-in-the-loop
                                                • 1. Require approvals for sensitive actions
                                                  • 2. Enforce least-privilege execution
                                                    Topic 5: Implement tool use and environment interaction20–25%- Agent tool configuration
                                                    • 1. Configure tool permissions and scope
                                                      • 2. Select and configure tools
                                                        - Safe execution and error handling
                                                        • 1. Escalation paths and traceability
                                                          • 2. Retries and rollback strategies
                                                            - MCP server configuration
                                                            • 1. Add MCP servers to agents
                                                              • 2. Configure registries and allow lists
                                                                - Development environment integration
                                                                • 1. Enable autonomous actions (PRs, branches)
                                                                  • 2. Scope agents to repositories or branches
                                                                    • 3. Enable CI-based agent execution
                                                                      Topic 6: Orchestrate multi-agent coordination15–20%- Failure handling and recovery
                                                                      • 1. Implement rollback and recovery patterns
                                                                        • 2. Detect stalled or degraded agents
                                                                          - 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. Generate logs and artifacts for review
                                                                                  • 2. Document agent handoffs and decisions

                                                                                    Microsoft GitHub Agentic AI Developer Sample Questions:

                                                                                    1. You are troubleshooting why a Copilot coding agent pull request keeps failing CI checks after every attempted fix. What is the most effective first step?

                                                                                    A) Enable Copilot memory
                                                                                    B) Switch the agent to --allow-all mode
                                                                                    C) Add clear, reproducible steps and expected behavior to the issue
                                                                                    D) Increase MCP server rate limits


                                                                                    2. You have a GitHub repository that uses GitHub Copilot code review on pull requests.
                                                                                    You plan to add repository-wide code review guidance that will apply to all files.
                                                                                    You need Copilot code review to consistently apply the guidance during pull request reviews.
                                                                                    What should you do?

                                                                                    A) Modify the .github/pull_request_template.md file.
                                                                                    B) Create a .github/copilot-instructions.md file.
                                                                                    C) Create a .github/instructions/copilot.instructions.md file.
                                                                                    D) Update the instructions in the .github/agents/*.agent.md files.


                                                                                    3. During a Copilot CLI session, an MCP tool call fails because the external service requires re- authentication. What is the most likely resolution path?

                                                                                    A) Run /compact to clear context
                                                                                    B) Re-authenticate the MCP server connector
                                                                                    C) Run /diff to inspect changes
                                                                                    D) Switch to plan mode


                                                                                    4. You have a GitHub Copilot coding agent named Orchestrator that runs a multi-phase workflow by using the following subagents:
                                                                                    - Explorer gathers context by using read-only tools.
                                                                                    - Modifier applies focused edits.
                                                                                    You are adding a new agent named Summarizer that generates a concise summary after modifications are complete. Summarizer includes the following YAML frontmatter.

                                                                                    The Orchestrator agent lists all three agents in its agents property.
                                                                                    After adding the Summarizer agent, Orchestrator successfully runs Explorer and Modifier but fails to run Summarizer.
                                                                                    What is a possible cause of the failure?

                                                                                    A) Summarizer is missing the editing tools required to complete the workflow.
                                                                                    B) Summarizer cannot be invoked as a subagent because disable-model-invocation is set to true.
                                                                                    C) Orchestrator is missing a handoff entry to trigger Summarizer.
                                                                                    D) Orchestrator cannot call Summarizer because user-invocable is set to false.


                                                                                    5. 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.


                                                                                    Solutions:

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

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