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Microsoft GH-600 Exam Syllabus Topics:

SectionWeightObjectives
Implement tool use and environment interaction20-25%- Select and configure agent tools
  • 1. Configure agent tool permissions
    • 2. Identify required tools
      • 3. Configure agent tools
        - 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 to use branch-based scope
              • 4. Configure an agent to be invoked in a CI workflow
                • 5. Configure an agent's scope to a specific repository
                  • 6. Evaluate the execution context for an agent
                    - Operate agents with safe execution paths and robust error handling
                    • 1. Implement rollbacks
                      • 2. Implement retries
                        • 3. Implement traceability and accountability for agent actions
                          • 4. Implement error handling
                            • 5. Implement escalation paths
                              - Configure MCP servers
                              • 1. Add an MCP server as a tool to an agent
                                • 2. Configure MCP allow lists
                                  • 3. Configure a GitHub remote MCP server
                                    • 4. Configure the MCP registries
                                      Orchestrate multi-agent coordination15-20%- 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
                                            - 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
                                                  - Detect and respond to multi-agent failures and degraded behavior
                                                  • 1. Implement multi-agent recovery patterns, including rollback and human-in-the-loop
                                                    • 2. Identify failed, partial, or stalled agent executions
                                                      • 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
                                                              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. Require explicit authorization or controlled paths for irreversible or compliance-sensitive changes
                                                                    • 4. Block actions that violate defined security, compliance, or Responsible AI policies
                                                                      • 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
                                                                            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. Prevent agent action until the agent checked and approved
                                                                                  • 4. Validate agent plans
                                                                                    - Configure observability and control for autonomous agents
                                                                                    • 1. Configure agents to produce inspectable artifacts within standard development tooling
                                                                                      • 2. Plan and implement the degree of agent autonomy, including guardrails
                                                                                        • 3. Configure human intervention for autonomous agents without slowing delivery
                                                                                          - 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%- Define success criteria and evaluation signals for agent tasks
                                                                                                • 1. Generate evaluation signals by using automated scanning tools
                                                                                                  • 2. Align evaluation criteria with development intent
                                                                                                    • 3. Specify expected outcomes and operational constraints for agent tasks
                                                                                                      • 4. Identify qualitative and quantitative evaluation signals to evaluate agents
                                                                                                        - 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. Refine tool usage and tool access
                                                                                                              • 2. Revise instructions, workflows, or constraints
                                                                                                                • 3. Refine memory usage
                                                                                                                  Manage memory, state, and execution10-15%- Ensure continuity of agent memory and state across tools and environments
                                                                                                                  • 1. Prevent conflicting context
                                                                                                                    • 2. Prevent stale context
                                                                                                                      • 3. Share agent state
                                                                                                                        - Persist agent state and manage context drift
                                                                                                                        • 1. Resume agent work without repeating steps or diverging from prior decisions
                                                                                                                          • 2. Capture task progress and decisions as durable artifacts
                                                                                                                            • 3. Detect and correct drift during extended agent execution
                                                                                                                              - Implement agent memory strategies
                                                                                                                              • 1. Choose between short-term, long-term, and external memory
                                                                                                                                • 2. Define memory expiration, pruning, and reset rules
                                                                                                                                  • 3. Scope agent memory to task-relevant information

                                                                                                                                    Microsoft Developing in Agentic AI Systems Sample Questions:

                                                                                                                                    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:

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

                                                                                                                                    Correct Answer: C  🗳️

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

                                                                                                                                    You need to enable Copilot memory to support the planned changes.
                                                                                                                                    What should you configure?

                                                                                                                                    • A. The agent profile of agent1
                                                                                                                                    • B. The Copilot settings of the organization
                                                                                                                                    • C. The Copilot settings of each repository
                                                                                                                                    • D. The personal Copilot settings of each developer
                                                                                                                                    Reveal Solution  Discussion  0

                                                                                                                                    Correct Answer: B  🗳️

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

                                                                                                                                    You have a GitHub repository that contains the following custom agent files:
                                                                                                                                    A file named planner.agent.md that includes YAML frontmatter with a handoffs entry that has label: Start Implementation, agent: implementer, and prompt: Now implement the plan outlined above.
                                                                                                                                    A file named implementer.agent.md that is in the same directory as planner.agent.md and includes YAML frontmatter that has name: IMPLEMENTER.
                                                                                                                                    You add a third agent file named review.agent.md that includes name: code-review in the YAML frontmatter.
                                                                                                                                    You make the following changes to planner.agent.md:
                                                                                                                                    Update the existing handoff to include send: true and model: GPT-5.2 (copilot).
                                                                                                                                    Add a second handoff that has label: Run Review, agent: code-review, and prompt: Review the code changes made in the previous step.

                                                                                                                                    Reveal Solution  Discussion  0

                                                                                                                                    Correct Answer:

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