Microsoft GH-600 Q&A - in .pdf

  • GH-600 pdf
  • Exam Code: GH-600
  • Exam Name: Developing in Agentic AI Systems
  • Updated: Oct 13, 2026
  • Q & A: 111 Questions and Answers
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Microsoft GH-600 Exam Syllabus Topics:
SectionWeightObjectives
Manage memory, state, and execution10-15%- Persist agent state and manage context drift
  • 1. Detect and correct drift during extended agent execution
    • 2. Resume agent work without repeating steps or diverging from prior decisions
      • 3. Capture task progress and decisions as durable artifacts
        - Implement agent memory strategies
        • 1. Scope agent memory to task-relevant information
          • 2. Choose between short-term, long-term, and external memory
            • 3. Define memory expiration, pruning, and reset rules
              - Ensure continuity of agent memory and state across tools and environments
              • 1. Prevent stale context
                • 2. Share agent state
                  • 3. Prevent conflicting context
                    Implement guardrails and accountability10-15%- Implement guardrails and human-in-the-loop workflows
                    • 1. Require explicit authorization or controlled paths for irreversible or compliance-sensitive changes
                      • 2. Scope permissions and execution contexts to enforce least-privilege access
                        • 3. Identify the subset of actions that require human judgment
                          • 4. Preserve execution velocity by minimizing approvals that do not materially reduce risk
                            • 5. Block actions that violate defined security, compliance, or Responsible AI policies
                              - Define autonomy levels
                              • 1. Assign autonomy levels to maximize delivery speed while remaining compliant with organizational security and Responsible AI standards
                                • 2. Classify agent actions by operational, security, and compliance risk to right-size human interventions
                                  Perform evaluation, error analysis, and tuning15-20%- Define success criteria and evaluation signals for agent tasks
                                  • 1. Generate evaluation signals by using automated scanning tools
                                    • 2. Specify expected outcomes and operational constraints for agent tasks
                                      • 3. Identify qualitative and quantitative evaluation signals to evaluate agents
                                        • 4. Align evaluation criteria with development intent
                                          - 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
                                              - Tune agent behavior based on evaluation results
                                              • 1. Refine tool usage and tool access
                                                • 2. Revise instructions, workflows, or constraints
                                                  • 3. Refine memory usage
                                                    Implement tool use and environment interaction20-25%- Configure MCP servers
                                                    • 1. Configure MCP allow lists
                                                      • 2. Configure the MCP registries
                                                        • 3. Configure a GitHub remote MCP server
                                                          • 4. Add an MCP server as a tool to an agent
                                                            - Integrate agents within development environments
                                                            • 1. Configure an agent to handle environment-specific constraints
                                                              • 2. Enable an agent to perform autonomous actions, including creating branches and pull requests
                                                                • 3. Configure an agent to use branch-based scope
                                                                  • 4. Evaluate the execution context for an agent
                                                                    • 5. Configure an agent to be invoked in a CI workflow
                                                                      • 6. Configure an agent's scope to a specific repository
                                                                        - Operate agents with safe execution paths and robust error handling
                                                                        • 1. Implement error handling
                                                                          • 2. Implement retries
                                                                            • 3. Implement escalation paths
                                                                              • 4. Implement traceability and accountability for agent actions
                                                                                • 5. Implement rollbacks
                                                                                  - Select and configure agent tools
                                                                                  • 1. Configure agent tool permissions
                                                                                    • 2. Configure agent tools
                                                                                      • 3. Identify required tools
                                                                                        Prepare agent architecture and SDLC processes15-20%- Integrate agents into the software development lifecycle (SDLC)
                                                                                        • 1. Identify and mitigate common anti-patterns in agents
                                                                                          • 2. Identify steps for agents to perform
                                                                                            • 3. Define inputs, outputs, and success criteria for agents
                                                                                              - Configure observability and control for autonomous agents
                                                                                              • 1. Plan and implement the degree of agent autonomy, including guardrails
                                                                                                • 2. Configure agents to produce inspectable artifacts within standard development tooling
                                                                                                  • 3. Configure human intervention for autonomous agents without slowing delivery
                                                                                                    - Define boundaries between planning, reasoning, and action
                                                                                                    • 1. Configure an agent to output a structured plan
                                                                                                      • 2. Prevent agent action until the agent checked and approved
                                                                                                        • 3. Configure agent planning to be distinct from agent execution
                                                                                                          • 4. Validate agent plans
                                                                                                            Orchestrate multi-agent coordination15-20%- Operate and manage multi-agent workflows
                                                                                                            • 1. Configure agent isolation for parallel execution
                                                                                                              • 2. Apply an orchestration pattern to coordinate multiple agents
                                                                                                                • 3. Detect and resolve agent conflicts, including overlapping code changes, duplicated effort, and contradictory outputs
                                                                                                                  - Detect and respond to multi-agent failures and degraded behavior
                                                                                                                  • 1. Identify failed, partial, or stalled agent executions
                                                                                                                    • 2. Respond to degraded behavior or coordination across agents
                                                                                                                      • 3. Implement multi-agent recovery patterns, including rollback and human-in-the-loop
                                                                                                                        - Configure observability for multi-agent behavior by using logs, artifacts, and operational signals
                                                                                                                        • 1. Document key decisions, handoffs, and outcomes across agents
                                                                                                                          • 2. Configure multi-agent workflows to produce artifacts suitable for review and audit
                                                                                                                            • 3. Perform post-hoc analysis of multi-agent behavior
                                                                                                                              - Manage the lifecycle of agents within multi-agent workflows
                                                                                                                              • 1. Add agents to existing multi-agent workflows
                                                                                                                                • 2. Retire agents while preserving auditability and workflow continuity
                                                                                                                                  • 3. Update, reconfigure, or replace agents without disrupting active workflows
                                                                                                                                    Microsoft Developing in Agentic AI Systems Sample Questions:
                                                                                                                                    Question #1

                                                                                                                                    You have a GitHub repository that uses GitHub Actions to run an autonomous agent job. The job summarizes a pull request and posts the summary as a pull request comment.
                                                                                                                                    Your company stores required configuration values, such as JOB_NAME and RUNNER, as organization-level configuration variables and exposes them in workflows by using the vars context.
                                                                                                                                    You discover that the agent job runs on push events and creates comments that are NOT tied to a pull request.
                                                                                                                                    You need to ensure that the agent job runs only when the workflow run is triggered by a pull request. The solution must keep the job name and runner selection configured by using variables.
                                                                                                                                    What should you do in the workflow?

                                                                                                                                    • A. Set jobs.agent.if: ${{ env.GITHUB_EVENT_NAME == 'pull_request' }}. Set jobs.agent.name and jobs.agent.runs-on by using the env context.
                                                                                                                                    • B. Set jobs.agent.if: ${{ github.event_name == 'push' }}. Set jobs.agent.name and jobs.agent.runs-on by using the vars context.
                                                                                                                                    • C. Set jobs.agent.if: ${{ github.event_name == 'pull_request' }}. Set jobs.agent.name and jobs.agent.runs-on by using the vars context.
                                                                                                                                    • D. Set jobs.agent.if: ${{ github.ref == 'refs/heads/main' }}. Set jobs.agent.name and jobs.agent.runs-on by using the vars context.
                                                                                                                                    Reveal Solution  Discussion  0

                                                                                                                                    Correct Answer: C  🗳️

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                                                                                                                                    Question #2

                                                                                                                                    You have a GitHub repository that uses the GitHub Copilot coding agent to resolve issues and create draft pull requests.
                                                                                                                                    You assign an issue to Copilot. Copilot creates a draft pull request. The pull request timeline shows Copilot started work, followed by status updates. The most recent status update is 55 minutes old.
                                                                                                                                    You discover that the agent is no longer making progress.
                                                                                                                                    You need to ensure that the work resumes without redoing the completed steps or changing the previously chosen approach.
                                                                                                                                    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

                                                                                                                                    You have a GitHub repository that uses the GitHub Copilot CLI to run autonomous tasks.
                                                                                                                                    You need to validate each generated command before it runs. Any commands that attempt to modify paths outside the repository must be blocked.
                                                                                                                                    How should you complete the YAML? 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.

                                                                                                                                    Reveal Solution  Discussion  0

                                                                                                                                    Correct Answer:

                                                                                                                                    Question #4

                                                                                                                                    You want to prevent GitHub Copilot from ever suggesting completions or making edits inside a directory containing sensitive credentials templates. What should you configure?

                                                                                                                                    • A. A CODEOWNERS file
                                                                                                                                    • B. Branch protection rules
                                                                                                                                    • C. A repository ruleset
                                                                                                                                    • D. A .copilotignore file
                                                                                                                                    Reveal Solution  Discussion  0

                                                                                                                                    Correct Answer: D  🗳️

                                                                                                                                    Question #5

                                                                                                                                    You have a GitHub Enterprise organization that has Copilot memory enabled.
                                                                                                                                    You create a new repository.
                                                                                                                                    What are two ways that memories will be deleted from the repository? Each correct answer presents a complete solution.
                                                                                                                                    NOTE: Each correct selection is worth one point.

                                                                                                                                    • A. automatically after 28 days
                                                                                                                                    • B. when the code that created the memory is deleted
                                                                                                                                    • C. when the repository is archived
                                                                                                                                    • D. when pull requests are merged
                                                                                                                                    • E. manually by repository members
                                                                                                                                    Reveal Solution  Discussion  0

                                                                                                                                    Correct Answer: A,E  🗳️

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