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Microsoft GH-600 Exam Syllabus Topics:

Section	Weight	Objectives
Orchestrate multi-agent coordination	15–20%	- 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. Document key decisions, handoffs, and outcomes across agents 3. Perform post-hoc analysis of multi-agent behavior - 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 - 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 - 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
Manage memory, state, and execution	10–15%	- 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. Capture task progress and decisions as durable artifacts 2. Detect and correct drift during extended agent execution 3. Resume agent work without repeating steps or diverging from prior decisions - Ensure continuity of agent memory and state across tools and environments 1. Prevent conflicting context 2. Share agent state 3. Prevent stale context
Prepare agent architecture and SDLC processes	15–20%	- Define boundaries between planning, reasoning, and action 1. Validate agent plans 2. Prevent agent action until the agent checks and approves 3. Configure agent planning to be distinct from agent execution 4. Configure an agent to output a structured plan - 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 - Configure observability and control for autonomous agents 1. Configure agents to produce inspectable artifacts within standard development tooling 2. Configure human intervention for autonomous agents without slowing delivery 3. Plan and implement the degree of agent autonomy, including guardrails
Perform evaluation, error analysis, and tuning	15–20%	- Tune agent behavior based on evaluation results 1. Refine memory usage 2. Revise instructions, workflows, or constraints 3. Refine tool usage and tool access - 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. Identify qualitative and quantitative evaluation signals to evaluate agents 4. Specify expected outcomes and operational constraints for agent tasks - 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
Implement tool use and environment interaction	20–25%	- Integrate agents within development environments 1. Configure an agent to use branch-based scope 2. Configure an agent to handle environment-specific constraints 3. Configure an agent's scope to a specific repository 4. Configure an agent to be invoked in a CI workflow 5. Evaluate the execution context for an agent 6. Enable an agent to perform autonomous actions, including creating branches and pull requests - Operate agents with safe execution paths and robust error handling 1. Implement rollbacks 2. Implement error handling 3. Implement retries 4. Implement escalation paths 5. Implement traceability and accountability for agent actions - 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 MCP registries - Select and configure agent tools 1. Configure agent tool permissions 2. Identify required tools 3. Configure agent tools
Implement guardrails and accountability	10–15%	- 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. Preserve execution velocity by minimizing approvals that do not materially reduce risk 2. Identify the subset of actions that require human judgment 3. Scope permissions and execution contexts to enforce least-privilege access 4. Block actions that violate defined security, compliance, or Responsible AI policies 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 organization that has Copilot memory enabled.
You create a new repository.
What are two ways that memories will be deleted from the repository? Each correct answer presents a complete solution.
NOTE: Each correct selection is worth one point.

A. manually by repository members
B. when pull requests are merged
C. automatically after 28 days
D. when the code that created the memory is deleted
E. when the repository is archived

Reveal Solution Discussion 0

Correct Answer: A,C 🗳️

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Question #2

You have a GitHub Actions workflow that runs GitHub Copilot-driven integration tests across multiple jobs.
You need to persist the agent memory/state so that it remains available across the jobs.
What should you do?

A. Upload the agent state as a workflow artifact and download the artifact in subsequent jobs.
B. Use the runner's memory to retain the workspace between jobs.
C. Add the agent state directory to the repository and commit the changes at the end of each job.
D. Write the agent state to environment variables.

Reveal Solution Discussion 0

Correct Answer: A 🗳️

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

Question #3

You need to make changes to repo1 to support the planned changes for the developers.
What should you modify?

A. .vscode/settings.json
B. .github/agents/*.agent.md
C. <project>/.mcp/server.json
D. .vscode/mcp.json

Reveal Solution Discussion 0

Correct Answer: B 🗳️

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Question #4

You have a GitHub repository that stores custom GitHub Copilot agents in the .github/agents/ folder.
You have an agent named lead-dev.agent.md that must invoke a specialist subagent named security-reviewer.
Evaluation results show that lead-dev attempts to invoke security-reviewer, but the subagent call fails to run.
You need to ensure that lead-dev can invoke security-reviewer.
How should you complete the YAML frontmatter of the agent profile? To answer, drag the appropriate values to the correct targets.

Reveal Solution Discussion 0

Correct Answer:

Question #5

You have a GitHub Enterprise Cloud organization that uses the GitHub Copilot coding agent.
Copilot creates a draft pull request for an assigned issue, and the pull request timeline shows Copilot started work.
After 70 minutes, the agent session log stops updating, and the pull request body status stops changing.
You need to restart the agent so that it continues the task from the issue context and produces new commits to the existing draft pull request.
What should you do?

A. Unassign the issue from Copilot, and then reassign the issue to Copilot.
B. Wait for the agent to complete.
C. Merge the draft pull request and mention @copilot on the merged pull request.
D. Select Approve and run workflows in the pull request merge box.

Reveal Solution Discussion 0

Correct Answer: A 🗳️

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