Microsoft GH-600 : Developing in Agentic AI Systems

  • Exam Code: GH-600
  • Exam Name: Developing in Agentic AI Systems
  • Updated: Oct 04, 2026   Q&As: 111 Questions and Answers

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Microsoft GH-600 Exam Syllabus Topics:

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

                                                                                                                                    Microsoft Developing in Agentic AI Systems Sample Questions:

                                                                                                                                    Question #1

                                                                                                                                    You have a GitHub Actions workflow that starts multiple agent jobs in parallel.
                                                                                                                                    You need to prevent two runs in the same job from executing simultaneously on the same branch. The solution must ensure, at most, one running instance and one pending instance per branch.
                                                                                                                                    What should you add to the job?

                                                                                                                                    • A. jobs.<job_id>.concurrency.cancel-in-progress: ${{ !contains(github.ref, 'release/') }}
                                                                                                                                    • B. jobs.<job_id>.concurrency.group: ci-${{ github.ref }}
                                                                                                                                    • C. jobs.<job_id>.strategy.max-parallel: 1
                                                                                                                                    • D. jobs.<job_id>.strategy.matrix: [1]
                                                                                                                                    Reveal Solution  Discussion  0

                                                                                                                                    Correct Answer: B  🗳️

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                                                                                                                                    Question #2

                                                                                                                                    You have a GitHub repository that uses three GitHub Copilot coding agents named agent1, agent2, and agent3.
                                                                                                                                    During structured evaluation runs, agent1 frequently returns Markdown narratives instead of a machine-parsable result.
                                                                                                                                    You need to ensure that agent1 consistently returns only a predefined JSON structure without affecting the output of the other agents.
                                                                                                                                    Which file should you modify?

                                                                                                                                    • A. .github/instructions/agent1.instructions.md
                                                                                                                                    • B. .github/copilot-instructions.md
                                                                                                                                    • C. .github/agents/agent1.agent.md
                                                                                                                                    • D. .github/workflows/copilot-setup-steps.yml
                                                                                                                                    Reveal Solution  Discussion  0

                                                                                                                                    Correct Answer: C  🗳️

                                                                                                                                    Explanation: Only visible for TorrentVCE members. You can sign-up / login (it's free).

                                                                                                                                    Question #3

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

                                                                                                                                    Correct Answer: C  🗳️

                                                                                                                                    Explanation: Only visible for TorrentVCE members. You can sign-up / login (it's free).

                                                                                                                                    Question #4

                                                                                                                                    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  🗳️

                                                                                                                                    Explanation: Only visible for TorrentVCE members. You can sign-up / login (it's free).

                                                                                                                                    Question #5

                                                                                                                                    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. Create a .github/instructions/copilot.instructions.md file.
                                                                                                                                    • B. Modify the .github/pull_request_template.md file.
                                                                                                                                    • C. Create a .github/copilot-instructions.md file.
                                                                                                                                    • D. Update the instructions in the .github/agents/*.agent.md files.
                                                                                                                                    Reveal Solution  Discussion  0

                                                                                                                                    Correct Answer: C  🗳️

                                                                                                                                    Explanation: Only visible for TorrentVCE members. You can sign-up / login (it's free).

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