Developing in Agentic AI Systems: GH-600 Exam


"Developing in Agentic AI Systems", also known as GH-600 exam, is a Microsoft Certification. With the complete collection of questions and answers, ExamcollectionPass has assembled to take you through 111 Q&As to your GH-600 Exam preparation. In the GH-600 exam resources, you will cover every field and category in GitHub Administrator Certification helping to ready you for your successful Microsoft Certification.

  • Exam Code: GH-600
  • Exam Name: Developing in Agentic AI Systems
  • Total Questions: 111

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Microsoft GH-600 Exam Syllabus Topics:

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

                                                                                                                                    Microsoft Developing in Agentic AI Systems Sample Questions:

                                                                                                                                    You have the following agent logs.

                                                                                                                                    Reveal Solution  Discussion  0

                                                                                                                                    Correct Answer:

                                                                                                                                    While using agent mode in VS Code, you want Copilot to run a specific test suite as a validation step after making changes, without manually invoking the terminal each time. What feature enables this?

                                                                                                                                    • A. MCP server integration
                                                                                                                                    • B. CODEOWNERS
                                                                                                                                    • C. Tool/terminal invocation permissions in agent mode
                                                                                                                                    • D. .copilotignore
                                                                                                                                    Reveal Solution  Discussion  0

                                                                                                                                    Correct Answer: C  🗳️

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

                                                                                                                                    You have a GitHub repository that runs an agentic software development lifecycle workflow by using GitHub Actions. The workflow uses the following three executors implemented as scripts: spec_analyzer, risk_reviewer, and plan_merger.
                                                                                                                                    You need to coordinate multiple specialized agents so that analysis and risk review run in parallel and then a final executor merges the outputs into a single plan. The orchestration pattern must fan out one request to multiple executors and then fan in the results to a final executor.
                                                                                                                                    How should you complete the workflow definition? To answer, drag the appropriate values to the correct targets.

                                                                                                                                    Reveal Solution  Discussion  0

                                                                                                                                    Correct Answer:

                                                                                                                                    You have a GitHub Enterprise repository that uses the GitHub Copilot coding agent and opens draft pull requests for assigned issues.
                                                                                                                                    Evaluation results show that the agent repeatedly opens pull requests that modify .github/workflows/*.yml to bypass failing checks instead of fixing the underlying code.
                                                                                                                                    You need to ensure that the agent fixes the underlying code instead of bypassing the failing checks.
                                                                                                                                    What should you do?

                                                                                                                                    • A. Update the .gitignore file.
                                                                                                                                    • B. Create a branch ruleset.
                                                                                                                                    • C. Disable GitHub Actions workflows for pull requests created by the agent.
                                                                                                                                    • D. Start the GitHub Copilot CLI by using --allow-all.
                                                                                                                                    Reveal Solution  Discussion  0

                                                                                                                                    Correct Answer: B  🗳️

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

                                                                                                                                    You have a GitHub Enterprise organization that uses GitHub Copilot.
                                                                                                                                    You discover that GitHub Copilot Chat responses in Microsoft Visual Studio Code are influenced by earlier, unrelated troubleshooting prompts from the same conversation.
                                                                                                                                    You need to ensure that the Copilot Chat conversation context is limited to information relevant to the current work item. The solution must minimize effort.
                                                                                                                                    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:

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