Microsoft GH-600 : Developing in Agentic AI Systems

  • Exam Code: GH-600
  • Exam Name: Developing in Agentic AI Systems
  • Updated: Oct 01, 2026
  • Q & A: 111 Questions and Answers

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Microsoft GH-600 Exam Syllabus Topics:

SectionWeightObjectives
Prepare agent architecture and SDLC processes15-20%- Define boundaries between planning, reasoning, and action
  • 1. Configure agent planning to be distinct from agent execution
    • 2. Configure an agent to output a structured plan
      • 3. Validate agent plans
        • 4. Prevent agent action until the agent checked and approved
          - 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
                - 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
                      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
                          - Define success criteria and evaluation signals for agent tasks
                          • 1. Specify expected outcomes and operational constraints for agent tasks
                            • 2. Align evaluation criteria with development intent
                              • 3. Identify qualitative and quantitative evaluation signals to evaluate agents
                                • 4. Generate evaluation signals by using automated scanning tools
                                  - Tune agent behavior based on evaluation results
                                  • 1. Refine memory usage
                                    • 2. Refine tool usage and tool access
                                      • 3. Revise instructions, workflows, or constraints
                                        Implement tool use and environment interaction20-25%- Integrate agents within development environments
                                        • 1. Configure an agent to use branch-based scope
                                          • 2. Configure an agent to handle environment-specific constraints
                                            • 3. Enable an agent to perform autonomous actions, including creating branches and pull requests
                                              • 4. Configure an agent's scope to a specific repository
                                                • 5. Evaluate the execution context for an agent
                                                  • 6. Configure an agent to be invoked in a CI workflow
                                                    - Operate agents with safe execution paths and robust error handling
                                                    • 1. Implement escalation paths
                                                      • 2. Implement rollbacks
                                                        • 3. Implement traceability and accountability for agent actions
                                                          • 4. Implement error handling
                                                            • 5. Implement retries
                                                              - Configure MCP servers
                                                              • 1. Add an MCP server as a tool to an agent
                                                                • 2. Configure the MCP registries
                                                                  • 3. Configure MCP allow lists
                                                                    • 4. Configure a GitHub remote MCP server
                                                                      - Select and configure agent tools
                                                                      • 1. Configure agent tool permissions
                                                                        • 2. Identify required tools
                                                                          • 3. Configure agent tools
                                                                            Manage memory, state, and execution10-15%- 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. 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
                                                                                        - 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
                                                                                              Orchestrate multi-agent coordination15-20%- Manage the lifecycle of agents within multi-agent workflows
                                                                                              • 1. Update, reconfigure, or replace agents without disrupting active workflows
                                                                                                • 2. Retire agents while preserving auditability and workflow continuity
                                                                                                  • 3. Add agents to existing multi-agent 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
                                                                                                          - Configure observability for multi-agent behavior by using logs, artifacts, and operational signals
                                                                                                          • 1. Perform post-hoc analysis of multi-agent behavior
                                                                                                            • 2. Configure multi-agent workflows to produce artifacts suitable for review and audit
                                                                                                              • 3. Document key decisions, handoffs, and outcomes across agents
                                                                                                                - 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
                                                                                                                      Implement guardrails and accountability10-15%- 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
                                                                                                                          - Implement guardrails and human-in-the-loop workflows
                                                                                                                          • 1. Scope permissions and execution contexts to enforce least-privilege access
                                                                                                                            • 2. Preserve execution velocity by minimizing approvals that do not materially reduce risk
                                                                                                                              • 3. Block actions that violate defined security, compliance, or Responsible AI policies
                                                                                                                                • 4. Identify the subset of actions that require human judgment
                                                                                                                                  • 5. Require explicit authorization or controlled paths for irreversible or compliance-sensitive changes

                                                                                                                                    Microsoft Developing in Agentic AI Systems Sample Questions:

                                                                                                                                    Question #1

                                                                                                                                    You have a GitHub Enterprise Cloud organization that uses the GitHub Copilot coding agent to resolve issues asynchronously.
                                                                                                                                    When an issue is assigned to GitHub Copilot, the agent creates a draft pull request, but your team cannot always tell whether the agent is actively working, has completed its session, or is awaiting workflow approval.
                                                                                                                                    Which execution context does each signal indicate? To answer, drag the appropriate context to the correct signals.

                                                                                                                                    Reveal Solution  Discussion  0

                                                                                                                                    Correct Answer:

                                                                                                                                    Question #2

                                                                                                                                    You have a GitHub Enterprise Cloud organization that has Copilot agents enabled.
                                                                                                                                    You discover activity in a repository.
                                                                                                                                    You need to identify whether the activity was initiated by an agent.
                                                                                                                                    Which two audit log fields can you use? Each correct answer presents a complete solution.

                                                                                                                                    • A. user
                                                                                                                                    • B. agent_session_id
                                                                                                                                    • C. actor_is_agent
                                                                                                                                    • D. action
                                                                                                                                    Reveal Solution  Discussion  0

                                                                                                                                    Correct Answer: B,C  🗳️

                                                                                                                                    Question #3

                                                                                                                                    You have a GitHub Actions workflow that runs two jobs named agent-plan and agent-implement on pull requests.
                                                                                                                                    The agent-plan job generates an implementation plan that downstream jobs must consume, but the job currently writes the plan only to the console.
                                                                                                                                    You need to capture the implementation plan as a step output and configure the workflow so that downstream jobs can reference the output.
                                                                                                                                    How should you configure the workflow? 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 #4

                                                                                                                                    You have a GitHub repository that uses the following GitHub Copilot CLI command in a Bash script.
                                                                                                                                    #!/usr/bin/env bash
                                                                                                                                    set -euo pipefail
                                                                                                                                    PROMPT="Update dependencies, run tests, and open a pull request if changes are needed." copilot --autopilot --yolo --max-autopilot-continues 10 -p "$PROMPT" For each of the following statements, select Yes if the statement is true. Otherwise, select No.
                                                                                                                                    NOTE: Each correct selection is worth one point.

                                                                                                                                    Reveal Solution  Discussion  0

                                                                                                                                    Correct Answer:

                                                                                                                                    Question #5

                                                                                                                                    You have a GitHub repository that uses the GitHub Copilot coding agent to resolve issues and create draft pull requests. The repository has a ruleset named ruleset1 that enforces the following:
                                                                                                                                    Signed commits
                                                                                                                                    Branch protections that require status checks to pass before merge
                                                                                                                                    The agent is blocked from operating in the repository because it fails to comply with the signed-commits rule.
                                                                                                                                    You need to ensure that the agent can create and push changes to copilot/ branches. The solution must enforce the signed-commits rule for human developers on protected branches.
                                                                                                                                    What should you do?

                                                                                                                                    • A. Remove the Require signed commits rule from ruleset1.
                                                                                                                                    • B. Make Copilot an owner of the repository.
                                                                                                                                    • C. Grant the Copilot coding agent permission to push directly to the copilot/ branches.
                                                                                                                                    • D. Add Copilot as a bypass actor for ruleset1.
                                                                                                                                    Reveal Solution  Discussion  0

                                                                                                                                    Correct Answer: D  🗳️

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