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Microsoft GH-600 Exam Syllabus Topics:

SectionWeightObjectives
Orchestrate multi-agent coordination15-20%- 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. Perform post-hoc analysis of multi-agent behavior
      • 3. Document key decisions, handoffs, and outcomes across agents
        - 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
              - Manage the lifecycle of agents within multi-agent workflows
              • 1. Add agents to existing multi-agent workflows
                • 2. Update, reconfigure, or replace agents without disrupting active workflows
                  • 3. Retire agents while preserving auditability and workflow continuity
                    - 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%- Tune agent behavior based on evaluation results
                          • 1. Refine tool usage and tool access
                            • 2. Refine memory usage
                              • 3. Revise instructions, workflows, or constraints
                                - 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. Identify qualitative and quantitative evaluation signals to evaluate agents
                                        • 3. Generate evaluation signals by using automated scanning tools
                                          • 4. Align evaluation criteria with development intent
                                            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. Define inputs, outputs, and success criteria for agents
                                                • 3. Identify steps for agents to perform
                                                  - Define boundaries between planning, reasoning, and action
                                                  • 1. Configure agent planning to be distinct from agent execution
                                                    • 2. Prevent agent action until the agent checked and approved
                                                      • 3. Configure an agent to output a structured plan
                                                        • 4. Validate agent plans
                                                          - Configure observability and control for autonomous agents
                                                          • 1. Configure human intervention for autonomous agents without slowing delivery
                                                            • 2. Plan and implement the degree of agent autonomy, including guardrails
                                                              • 3. Configure agents to produce inspectable artifacts within standard development tooling
                                                                Implement tool use and environment interaction20-25%- Integrate agents within development environments
                                                                • 1. Configure an agent to handle environment-specific constraints
                                                                  • 2. Configure an agent to use branch-based scope
                                                                    • 3. Enable an agent to perform autonomous actions, including creating branches and pull requests
                                                                      • 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
                                                                            - Configure MCP servers
                                                                            • 1. Add an MCP server as a tool to an agent
                                                                              • 2. Configure a GitHub remote MCP server
                                                                                • 3. Configure MCP allow lists
                                                                                  • 4. Configure the MCP registries
                                                                                    - Operate agents with safe execution paths and robust error handling
                                                                                    • 1. Implement rollbacks
                                                                                      • 2. Implement traceability and accountability for agent actions
                                                                                        • 3. Implement retries
                                                                                          • 4. Implement escalation paths
                                                                                            • 5. Implement error handling
                                                                                              - Select and configure agent tools
                                                                                              • 1. Configure agent tool permissions
                                                                                                • 2. Configure agent tools
                                                                                                  • 3. Identify required tools
                                                                                                    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. Scope permissions and execution contexts to enforce least-privilege access
                                                                                                        • 3. Identify the subset of actions that require human judgment
                                                                                                          • 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
                                                                                                                  Manage memory, state, and execution10-15%- 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
                                                                                                                        - Ensure continuity of agent memory and state across tools and environments
                                                                                                                        • 1. Prevent stale context
                                                                                                                          • 2. Prevent conflicting context
                                                                                                                            • 3. Share agent state
                                                                                                                              - 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

                                                                                                                                    Microsoft Developing in Agentic AI Systems Sample Questions:

                                                                                                                                    An agentic coding session in the terminal has grown too long, and you want to discard all prior conversation history and start clean, without summarization. Which slash command should you run?

                                                                                                                                    • A. /clear
                                                                                                                                    • B. /compact
                                                                                                                                    • C. /usage
                                                                                                                                    • D. /reset-context
                                                                                                                                    Reveal Solution  Discussion  0

                                                                                                                                    Correct Answer: A  🗳️

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

                                                                                                                                    You need to resolve the issue of the agents generating conflicting output. The solution must meet the implementation guidelines.
                                                                                                                                    What should you do?

                                                                                                                                    • A. Configure a concurrency group on both agent workflows so that only one workflow runs at a time.
                                                                                                                                    • B. Configure each agent to work on a separate branch and add a required status check that detects file-level overlap before either pull request can be merged.
                                                                                                                                    • C. Add shared/config.yaml to a CODEOWNERS file that requires SG_Review approval before any changes can be merged.
                                                                                                                                    • D. Configure tools: ['read', 'search'] in both agent profiles to prevent either agent from writing files.
                                                                                                                                    Reveal Solution  Discussion  0

                                                                                                                                    Correct Answer: B  🗳️

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

                                                                                                                                    You have multiple GitHub Copilot coding agents that run tasks concurrently.
                                                                                                                                    You are monitoring the agents from the terminal by using the GitHub CLI.
                                                                                                                                    An agent appears stalled.
                                                                                                                                    You need to live stream the session log output.
                                                                                                                                    What should you do?

                                                                                                                                    • A. Run gh agent-task list and specify the --web parameter.
                                                                                                                                    • B. Run gh agent-task view and specify the --log and --follow parameters.
                                                                                                                                    • C. Run gh agent-task view and specify the --log and --jq parameters.
                                                                                                                                    • D. Run gh agent-task list and specify the --status and --jq parameters.
                                                                                                                                    Reveal Solution  Discussion  0

                                                                                                                                    Correct Answer: B  🗳️

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

                                                                                                                                    You want to grant the Copilot coding agent access to only a narrowly scoped set of repository permissions (e.g., read code, write pull requests) rather than full admin access. What governs this scope?

                                                                                                                                    • A. The agent's GITHUB_TOKEN permissions, configured per workflow/repo policy
                                                                                                                                    • B. The /context command
                                                                                                                                    • C. copilot-instructions.md
                                                                                                                                    • D. .copilotignore
                                                                                                                                    Reveal Solution  Discussion  0

                                                                                                                                    Correct Answer: A  🗳️

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

                                                                                                                                    You have a repository that uses the GitHub Copilot coding agent and supports hooks stored under .github/hooks.
                                                                                                                                    You need a Shell command to run automatically whenever an agent execution fails.
                                                                                                                                    Which type of hook should you use?

                                                                                                                                    • A. sessionEnd
                                                                                                                                    • B. errorOccurred
                                                                                                                                    • C. agentStop
                                                                                                                                    • D. postToolUse
                                                                                                                                    Reveal Solution  Discussion  0

                                                                                                                                    Correct Answer: B  🗳️

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

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