Microsoft GH-600 Q&A - in .pdf

  • GH-600 pdf
  • Exam Code: GH-600
  • Exam Name: Developing in Agentic AI Systems
  • Updated: Sep 25, 2026
  • Q & A: 111 Questions and Answers
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Microsoft GH-600 Q&A - Testing Engine

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  • Exam Code: GH-600
  • Exam Name: Developing in Agentic AI Systems
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  • Q & A: 111 Questions and Answers
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Microsoft GH-600 Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Orchestrate multi-agent coordination15–20%- Operate and manage multi-agent workflows
  • 1. Apply an orchestration pattern to coordinate multiple agents
    • 2. Detect and resolve agent conflicts, including overlapping code changes, duplicated effort, and contradictory outputs
      • 3. Configure agent isolation for parallel execution
        - Detect and respond to multi-agent failures and degraded behavior
        • 1. Identify failed, partial, or stalled agent executions
          • 2. Implement multi-agent recovery patterns, including rollback and human-in-the-loop
            • 3. Respond to degraded behavior or coordination across agents
              - Configure observability for multi-agent behavior by using logs, artifacts, and operational signals
              • 1. Configure multi-agent workflows to produce artifacts suitable for review and audit
                • 2. Document key decisions, handoffs, and outcomes across agents
                  • 3. Perform post-hoc analysis of multi-agent behavior
                    - Manage the lifecycle of agents within multi-agent workflows
                    • 1. Retire agents while preserving auditability and workflow continuity
                      • 2. Update, reconfigure, or replace agents without disrupting active workflows
                        • 3. Add agents to existing multi-agent workflows
                          Topic 2: Manage memory, state, and execution10–15%- Persist agent state and manage context drift
                          • 1. Detect and correct drift during extended agent execution
                            • 2. Capture task progress and decisions as durable artifacts
                              • 3. Resume agent work without repeating steps or diverging from prior decisions
                                - Ensure continuity of agent memory and state across tools and environments
                                • 1. Prevent conflicting context
                                  • 2. Share agent state
                                    • 3. Prevent stale context
                                      - Implement agent memory strategies
                                      • 1. Define memory expiration, pruning, and reset rules
                                        • 2. Choose between short-term, long-term, and external memory
                                          • 3. Scope agent memory to task-relevant information
                                            Topic 3: Prepare agent architecture and SDLC processes15–20%- Integrate agents into the software development lifecycle (SDLC)
                                            • 1. Identify steps for agents to perform
                                              • 2. Define inputs, outputs, and success criteria for agents
                                                • 3. Identify and mitigate common anti-patterns in agents
                                                  - Define boundaries between planning, reasoning, and action
                                                  • 1. Prevent agent action until the agent checks and approves
                                                    • 2. Configure agent planning to be distinct from agent execution
                                                      • 3. Configure an agent to output a structured plan
                                                        • 4. Validate agent plans
                                                          - Configure observability and control for autonomous agents
                                                          • 1. Configure agents to produce inspectable artifacts within standard development tooling
                                                            • 2. Configure human intervention for autonomous agents without slowing delivery
                                                              • 3. Plan and implement the degree of agent autonomy, including guardrails
                                                                Topic 4: Implement tool use and environment interaction20–25%- Integrate agents within development environments
                                                                • 1. Enable an agent to perform autonomous actions, including creating branches and pull requests
                                                                  • 2. Configure an agent to handle environment-specific constraints
                                                                    • 3. Configure an agent's scope to a specific repository
                                                                      • 4. Evaluate the execution context for an agent
                                                                        • 5. Configure an agent to be invoked in a CI workflow
                                                                          • 6. Configure an agent to use branch-based scope
                                                                            - Operate agents with safe execution paths and robust error handling
                                                                            • 1. Implement error handling
                                                                              • 2. Implement traceability and accountability for agent actions
                                                                                • 3. Implement rollbacks
                                                                                  • 4. Implement retries
                                                                                    • 5. Implement escalation paths
                                                                                      - Configure MCP servers
                                                                                      • 1. Configure a GitHub remote MCP server
                                                                                        • 2. Add an MCP server as a tool to an agent
                                                                                          • 3. Configure MCP allow lists
                                                                                            • 4. Configure MCP registries
                                                                                              - Select and configure agent tools
                                                                                              • 1. Configure agent tool permissions
                                                                                                • 2. Configure agent tools
                                                                                                  • 3. Identify required tools
                                                                                                    Topic 5: Implement guardrails and accountability10–15%- Define autonomy levels
                                                                                                    • 1. Classify agent actions by operational, security, and compliance risk to right-size human interventions
                                                                                                      • 2. Assign autonomy levels to maximize delivery speed while remaining compliant with organizational security and Responsible AI standards
                                                                                                        - Implement guardrails and human-in-the-loop workflows
                                                                                                        • 1. Preserve execution velocity by minimizing approvals that do not materially reduce risk
                                                                                                          • 2. Identify the subset of actions that require human judgment
                                                                                                            • 3. Require explicit authorization or controlled paths for irreversible or compliance-sensitive changes
                                                                                                              • 4. Scope permissions and execution contexts to enforce least-privilege access
                                                                                                                • 5. Block actions that violate defined security, compliance, or Responsible AI policies
                                                                                                                  Topic 6: Perform evaluation, error analysis, and tuning15–20%- Tune agent behavior based on evaluation results
                                                                                                                  • 1. Revise instructions, workflows, or constraints
                                                                                                                    • 2. Refine memory usage
                                                                                                                      • 3. Refine tool usage and tool access
                                                                                                                        - Analyze agent failures and identify root causes
                                                                                                                        • 1. Identify failures by using logs, plans, traces, outputs, and workflow artifacts
                                                                                                                          • 2. Classify root causes, including reasoning errors, tool misuse, and context or environment issues
                                                                                                                            - Define success criteria and evaluation signals for agent tasks
                                                                                                                            • 1. Identify qualitative and quantitative evaluation signals to evaluate agents
                                                                                                                              • 2. Specify expected outcomes and operational constraints for agent tasks
                                                                                                                                • 3. Align evaluation criteria with development intent
                                                                                                                                  • 4. Generate evaluation signals by using automated scanning tools

                                                                                                                                    Microsoft Developing in Agentic AI Systems Sample Questions:

                                                                                                                                    Question #1

                                                                                                                                    You have a GitHub Actions workflow that runs GitHub Copilot-driven integration tests across multiple jobs.
                                                                                                                                    You need to persist the agent memory/state so that it remains available across the jobs.
                                                                                                                                    What should you do?

                                                                                                                                    • A. Upload the agent state as a workflow artifact and download the artifact in subsequent jobs.
                                                                                                                                    • B. Add the agent state directory to the repository and commit the changes at the end of each job.
                                                                                                                                    • C. Use the runner's memory to retain the workspace between jobs.
                                                                                                                                    • D. Write the agent state to environment variables.
                                                                                                                                    Reveal Solution  Discussion  0

                                                                                                                                    Correct Answer: A  🗳️

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                                                                                                                                    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.
                                                                                                                                    NOTE: Each correct selection is worth one point.

                                                                                                                                    Reveal Solution  Discussion  0

                                                                                                                                    Correct Answer:

                                                                                                                                    Question #3

                                                                                                                                    While upgrading App1, the agent identifies 47 issues, including a security vulnerability, and 46 API incompatibilities across different projects.
                                                                                                                                    Which two actions are unsafe to delegate to the agent and require human involvement? Each correct answer presents a complete solution.
                                                                                                                                    NOTE: Each correct selection is worth one point.

                                                                                                                                    • A. Approve all Git commits.
                                                                                                                                    • B. Validate whether the tasks.md file exists.
                                                                                                                                    • C. Validate the assessment.md file for accuracy.
                                                                                                                                    • D. Review the plan.md file for dependencies.
                                                                                                                                    • E. Generate the assessment.md file.
                                                                                                                                    Reveal Solution  Discussion  0

                                                                                                                                    Correct Answer: A,C  🗳️

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                                                                                                                                    Question #4

                                                                                                                                    You need to provide access to the API key of MCP1. The solution must meet the security requirements.
                                                                                                                                    What should you do?

                                                                                                                                    • A. In product-api, add the API key as a GitHub Actions encrypted secret and reference the secret by using ${{ secrets.KEY }} in the workflow YAML of agent1.
                                                                                                                                    • B. Store the API key as a GitHub Codespaces user secret scoped to product-api.
                                                                                                                                    • C. In the product-api repository settings, add the API key directly to the .mcp/server.json file by using a plaintext apiKey field.
                                                                                                                                    • D. Store the API key as a secret in the Copilot environment of product-api by using a name prefix of COPILOT_MCP_, and then reference the variable name in the mcp.json configuration.
                                                                                                                                    Reveal Solution  Discussion  0

                                                                                                                                    Correct Answer: D  🗳️

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                                                                                                                                    Question #5

                                                                                                                                    You have a GitHub Copilot coding agent named CodeAgent. The .agent.md file of CodeAgent contains the following YAML frontmatter.
                                                                                                                                    name: CodeAgent
                                                                                                                                    description: Performs repository analysis and code review tasks.
                                                                                                                                    tools: ['edit', 'execute', 'read', 'search']
                                                                                                                                    You need to issue a GitHub Copilot CLI command that preserves execution velocity for read-only tasks by eliminating approval prompts for low-risk tools. The solution must ensure that high-risk tools that can make changes remain available but still require explicit user approval before running.
                                                                                                                                    Which command should you run?

                                                                                                                                    • A. copilot agent run CodeAgent --allow-all-tools
                                                                                                                                    • B. copilot agent run CodeAgent --allow-tool 'read,search'
                                                                                                                                    • C. copilot agent run CodeAgent --deny-tool 'edit,execute'
                                                                                                                                    • D. copilot agent run CodeAgent
                                                                                                                                    Reveal Solution  Discussion  0

                                                                                                                                    Correct Answer: B  🗳️

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