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Microsoft GH-600 Exam Syllabus Topics:

Section	Weight	Objectives
Implement guardrails and accountability	10–15%	- Guardrails and human-in-the-loop 1. Require approvals for sensitive actions 2. Enforce least-privilege execution - Autonomy and risk levels 1. Assign autonomy levels with compliance constraints 2. Classify agent actions by risk
Prepare agent architecture and SDLC processes	15–20%	- Integrate agents into SDLC workflows 1. Define agent steps in SDLC 2. Define inputs, outputs, and success criteria 3. Identify and mitigate agent anti-patterns - Planning vs execution boundaries 1. Validate structured agent plans 2. Prevent execution before approval 3. Separate planning and execution phases - Observability and control 1. Produce inspectable artifacts in GitHub 2. Define autonomy levels and guardrails 3. Enable human-in-the-loop controls
Evaluation, error analysis, and tuning	15–20%	- Failure analysis 1. Classify reasoning, tool, and context errors 2. Analyze logs, traces, and artifacts - Define evaluation criteria 1. Generate automated evaluation signals 2. Define success metrics and constraints - Tuning agent behavior 1. Optimize memory usage and constraints 2. Refine prompts, tools, and workflows
Orchestrate multi-agent coordination	15–20%	- Multi-agent workflows 1. Resolve conflicts and overlaps 2. Coordinate parallel agent execution - Failure handling and recovery 1. Detect stalled or degraded agents 2. Implement rollback and recovery patterns - Observability and auditability 1. Generate logs and artifacts for review 2. Document agent handoffs and decisions - Lifecycle management 1. Add/replace/retire agents safely
Manage memory, state, and execution	10–15%	- Agent memory strategies 1. Short-term vs long-term memory selection 2. Memory scoping and expiration rules - State persistence and drift control 1. Persist task progress as artifacts 2. Detect and correct context drift - Cross-tool continuity 1. Share state across tools and environments 2. Prevent stale or conflicting context
Implement tool use and environment interaction	20–25%	- Agent tool configuration 1. Configure tool permissions and scope 2. Select and configure tools - Development environment integration 1. Enable CI-based agent execution 2. Enable autonomous actions (PRs, branches) 3. Scope agents to repositories or branches - Safe execution and error handling 1. Escalation paths and traceability 2. Retries and rollback strategies - MCP server configuration 1. Configure registries and allow lists 2. Add MCP servers to agents

Microsoft GitHub Agentic AI Developer Sample Questions:

1. You are debugging an agentic workflow that intermittently fails specific tool calls with rate-limit errors when connecting to an internal MCP server. What is the most direct remediation?

A) Add a CODEOWNERS entry
B) Switch to --allow-all
C) Increase the MCP server's configured rate limits/quota
D) Run /clear

2. Hotspot Question
You have a GitHub repository that uses GitHub Copilot Chat in Microsoft Visual Studio Code.
Custom agents are stored in the repository under version control.
Your team uses a multi-agent workflow where a planner agent produces an implementation plan that is then handed off to an implementation agent to make changes.
Recent prompts cause the planner agent to start editing files and running commands before the plan is approved.
You need to configure the planner agent to meet the following requirements:
- Use only read-only tools.
- Hand off to the implementation agent only after the plan is approved.
How should you configure the agent? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

3. You use a GitHub Actions workflow to orchestrate a multi-agent draft-review process for pull requests. The workflow uploads a single combined review-package artifact at the end of each run.
You discover that the review-package artifact is occasionally missing from the workflow run history, and you suspect that a user deleted it.
You need to identify which user manually deleted a workflow run artifact and when the deletion occurred.
What should you use?

A) the artifact.destroy audit log event
B) the pull request description and comment history
C) the checks.delete_logs audit log event
D) the merge commit history

4. You have a GitHub repository that uses GitHub Copilot code review on pull requests.
You plan to add repository-wide code review guidance that will apply to all files.
You need Copilot code review to consistently apply the guidance during pull request reviews.
What should you do?

A) Create a .github/instructions/copilot.instructions.md file.
B) Create a .github/copilot-instructions.md file.
C) Update the instructions in the .github/agents/*.agent.md files.
D) Modify the .github/pull_request_template.md file.

5. 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.

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

Solutions:

Question # 1
Answer: C

Question # 2
Answer: Only visible for members

Question # 3
Answer: A

Question # 4
Answer: A

Question # 5
Answer: A