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Microsoft GH-600 Exam Syllabus Topics:

SectionWeightObjectives
Implement tool use and environment interaction20–25%- Configure MCP servers
  • 1. Add an MCP server as a tool to an agent
    • 2. Configure a GitHub remote MCP server
      • 3. Configure MCP registries
        • 4. Configure MCP allow lists
          - Integrate agents within development environments
          • 1. Enable an agent to perform autonomous actions, including creating branches and pull requests
            • 2. Configure an agent to be invoked in a CI workflow
              • 3. Configure an agent's scope to a specific repository
                • 4. Configure an agent to use branch-based scope
                  • 5. Evaluate the execution context for an agent
                    • 6. Configure an agent to handle environment-specific constraints
                      - Select and configure agent tools
                      • 1. Identify required tools
                        • 2. Configure agent tool permissions
                          • 3. Configure agent tools
                            - Operate agents with safe execution paths and robust error handling
                            • 1. Implement error handling
                              • 2. Implement retries
                                • 3. Implement traceability and accountability for agent actions
                                  • 4. Implement escalation paths
                                    • 5. Implement rollbacks
                                      Implement guardrails and accountability10–15%- 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
                                          - Implement guardrails and human-in-the-loop workflows
                                          • 1. Scope permissions and execution contexts to enforce least-privilege access
                                            • 2. Block actions that violate defined security, compliance, or Responsible AI policies
                                              • 3. Identify the subset of actions that require human judgment
                                                • 4. Preserve execution velocity by minimizing approvals that do not materially reduce risk
                                                  • 5. Require explicit authorization or controlled paths for irreversible or compliance-sensitive changes
                                                    Prepare agent architecture and SDLC processes15–20%- 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. 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
                                                                - 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 checks and approves
                                                                        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
                                                                              - 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
                                                                                    - Ensure continuity of agent memory and state across tools and environments
                                                                                    • 1. Prevent conflicting context
                                                                                      • 2. Prevent stale context
                                                                                        • 3. Share agent state
                                                                                          Perform evaluation, error analysis, and tuning15–20%- 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
                                                                                              - Define success criteria and evaluation signals for agent tasks
                                                                                              • 1. Align evaluation criteria with development intent
                                                                                                • 2. Specify expected outcomes and operational constraints for agent tasks
                                                                                                  • 3. Generate evaluation signals by using automated scanning tools
                                                                                                    • 4. Identify qualitative and quantitative evaluation signals to evaluate agents
                                                                                                      - Tune agent behavior based on evaluation results
                                                                                                      • 1. Revise instructions, workflows, or constraints
                                                                                                        • 2. Refine memory usage
                                                                                                          • 3. Refine tool usage and tool access
                                                                                                            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. Add agents to existing multi-agent workflows
                                                                                                                • 3. Retire agents while preserving auditability and workflow continuity
                                                                                                                  - 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. Identify failed, partial, or stalled agent executions
                                                                                                                          • 2. Respond to degraded behavior or coordination across agents
                                                                                                                            • 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

                                                                                                                                    Microsoft Developing in Agentic AI Systems Sample Questions:

                                                                                                                                    You have a GitHub repository that uses GitHub Actions for CI.
                                                                                                                                    Your team is piloting the GitHub Copilot coding agent to autonomously create branches and open pull requests. The repository follows trunk-based development that uses main as the default branch.
                                                                                                                                    You need to ensure that the agent meets the following requirements:
                                                                                                                                    Changes to main can occur only by using pull requests that have at least one approval.
                                                                                                                                    When a pull request is opened, a validation workflow runs.
                                                                                                                                    How should you configure the repository? To answer, select the appropriate options in the answer area.

                                                                                                                                    Reveal Solution  Discussion  0

                                                                                                                                    Correct Answer:

                                                                                                                                    You have a GitHub Copilot coding agent named Orchestrator that runs a multi-phase workflow by using the following subagents:
                                                                                                                                    Explorer gathers context by using read-only tools.
                                                                                                                                    Modifier applies focused edits.
                                                                                                                                    You are adding a new agent named Summarizer that generates a concise summary after modifications are complete. Summarizer includes the following YAML frontmatter:
                                                                                                                                    ---
                                                                                                                                    name: Summarizer
                                                                                                                                    description: Produce a concise summary of recent changes
                                                                                                                                    tools: ['fetch']
                                                                                                                                    user-invocable: false
                                                                                                                                    disable-model-invocation: true
                                                                                                                                    ---
                                                                                                                                    The Orchestrator agent lists all three agents in its agents property.
                                                                                                                                    After adding the Summarizer agent, Orchestrator successfully runs Explorer and Modifier but fails to run Summarizer.
                                                                                                                                    What is a possible cause of the failure?

                                                                                                                                    • A. Orchestrator is missing a handoff entry to trigger Summarizer.
                                                                                                                                    • B. Summarizer is missing the editing tools required to complete the workflow.
                                                                                                                                    • C. Summarizer cannot be invoked as a subagent because disable-model-invocation is set to true.
                                                                                                                                    • D. Orchestrator cannot call Summarizer because user-invocable is set to false.
                                                                                                                                    Reveal Solution  Discussion  0

                                                                                                                                    Correct Answer: A  🗳️

                                                                                                                                    Explanation: Only visible for Lead2PassExam 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 personal Copilot settings of each developer
                                                                                                                                    • C. The Copilot settings of the organization
                                                                                                                                    • D. The Copilot settings of each repository
                                                                                                                                    Reveal Solution  Discussion  0

                                                                                                                                    Correct Answer: C  🗳️

                                                                                                                                    Explanation: Only visible for Lead2PassExam members. You can sign-up / login (it's free).

                                                                                                                                    A developer uses the GitHub Copilot CLI in plan mode.
                                                                                                                                    Copilot produces a plan.
                                                                                                                                    What does Copilot do next?

                                                                                                                                    • A. Begins the implementation.
                                                                                                                                    • B. Saves the plan to plan.md.
                                                                                                                                    • C. Creates a branch named /copilot/plan in the repository.
                                                                                                                                    • D. Opens a pull request that has the plan as a comment.
                                                                                                                                    Reveal Solution  Discussion  0

                                                                                                                                    Correct Answer: B  🗳️

                                                                                                                                    Explanation: Only visible for Lead2PassExam members. You can sign-up / login (it's free).

                                                                                                                                    You have a GitHub repository that uses GitHub Actions to run an autonomous coding-agent workflow.
                                                                                                                                    Your team requires that session logs be captured as workflow artifacts so that agent runs can be audited and traced back to a specific execution and code state.
                                                                                                                                    How should you complete the workflow? To answer, drag the appropriate values to the correct targets.

                                                                                                                                    Reveal Solution  Discussion  0

                                                                                                                                    Correct Answer:

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