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Microsoft GH-600 Exam Syllabus Topics:

Microsoft GitHub Agentic AI Developer Sample Questions:

1. You have a GitHub Enterprise Cloud Organization that uses GitHub Actions for CI/CD.
You plan to enable an agent to update and deploy workflows that access production environment secrets.
You need to select an autonomy level for a compliance-sensitive workflow.
Which autonomy level should you select?

A) read-only analysis with no ability to trigger workflows
B) human-in-the-loop with required manual approvals for production
C) fully autonomous execution without approvals
D) autonomous execution limited to non-production environments

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. Your organization wants to ensure the Copilot coding agent cannot push directly to main, and all its changes must go through a pull request review process like any other contributor. What enforces this?

A) /context
B) .copilotignore
C) Standard branch protection rules on the main branch
D) copilot-instructions.md

4. You have a GitHub Copilot coding agent that has completed a pull request for a security fix in your repository.
Before merging, you need to evaluate the quality of the agent's work by using both automated evaluation signals and human review.
You review the session log and the pull request.
What are two automated evaluation signals generated by the coding agent's built-in scanning tools? Each correct answer presents a complete solution.
NOTE: Each correct selection is worth one point.

A) comments from Copilot code review that suggest improvements to code patterns
B) the detection of hardcoded secrets, such as API keys and tokens
C) the median time to merge metric reported on the Copilot usage metrics dashboard
D) linting errors from the repository's CI pipeline configured in GitHub Actions
E) CodeQL findings that identify security vulnerabilities in the generated code

5. Drag and Drop Question
You have a GitHub repository that uses the GitHub Copilot coding agent to resolve issues and create draft pull requests. The repository uses GitHub Actions for CI, and reviewers rely on pull request timelines and workflow artifacts to understand what the agent did.
During long-running agent tasks, the reviewers lose track of decisions and validation steps, which causes repeated questions and reworks when context drifts between iterations.
You need to persist task progress and decisions as durable artifacts and ensure that the reviewers can verify what the agent did during and after execution by using GitHub as the system of record.
What should you do for each requirement? To answer, drag the appropriate actions to the correct requirements. Each action may be used once, more than once, or not at all. You may need to drag the split bar between panes or scroll to view content.
NOTE: Each correct selection is worth one point.

Solutions: