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Microsoft GH-600 dumps - in .pdf

GH-600 pdf
  • Exam Code: GH-600
  • Exam Name: GitHub Agentic AI Developer
  • Updated: Aug 22, 2026
  • Q & A: 85 Questions and Answers
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  • Exam Code: GH-600
  • Exam Name: GitHub Agentic AI Developer
  • Updated: Aug 22, 2026
  • Q & A: 85 Questions and Answers
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Microsoft GH-600 dumps - Testing Engine

GH-600 Testing Engine
  • Exam Code: GH-600
  • Exam Name: GitHub Agentic AI Developer
  • Updated: Aug 22, 2026
  • Q & A: 85 Questions and Answers
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Microsoft GH-600 Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Manage memory, state, and execution10-15%- Manage context and memory
  • 1. Handle long-running execution
  • 2. Maintain agent state
- Control execution flow
  • 1. Monitor execution lifecycle
  • 2. Recover from interruptions and failures
Topic 2: Perform evaluation, error analysis, and tuning15-20%- Improve agent behavior
  • 1. Perform error analysis
  • 2. Tune prompts, tools, and configurations
- Evaluate agent performance
  • 1. Measure outcomes and quality
  • 2. Analyze scans, logs, and artifacts
Topic 3: Implement guardrails and accountability10-15%- Implement governance controls
  • 1. Configure approval workflows
  • 2. Apply security and compliance requirements
- Ensure accountability
  • 1. Establish human-in-the-loop processes
  • 2. Track actions and decisions
Topic 4: Orchestrate multi-agent coordination15-20%- Coordinate multiple agents
  • 1. Manage communication and task delegation
  • 2. Design multi-agent workflows
- Ensure safe collaboration
  • 1. Prevent conflicts and unsafe actions
  • 2. Coordinate execution across agents
Topic 5: Implement tool use and environment interaction20-25%- Manage execution environments
  • 1. Configure environments for agents
  • 2. Control access to resources and services
- Select and configure agent tools
  • 1. Configure tools and permissions
  • 2. Identify required tools
Topic 6: Prepare agent architecture and SDLC processes15-20%- Configure observability and control
  • 1. Implement autonomy levels and guardrails
  • 2. Enable human intervention when required
  • 3. Generate inspectable artifacts
- Integrate agents into the software development lifecycle
  • 1. Identify steps for agents to perform
  • 2. Define inputs, outputs, and success criteria
  • 3. Identify and mitigate agent anti-patterns
- Define boundaries between planning, reasoning, and action
  • 1. Separate planning from execution
  • 2. Validate and approve plans before execution
  • 3. Configure structured plans

Microsoft GitHub Agentic AI Developer Sample Questions:

1. 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) .copilotignore
B) The /context command
C) copilot-instructions.md
D) The agent's GITHUB_TOKEN permissions, configured per workflow/repo policy


2. You have a GitHub Enterprise Cloud Organization that uses a custom coding agent to run GitHub Actions workflows that create branches, open pull requests, and merge changes after required checks pass.
You need to log all agent-initiated actions and ensure that the logs are retained for two years.
What should you do?

A) Enable log forwarding.
B) Configure audit log streaming to Azure Event Hubs.
C) Configure audit log retention.
D) Enable Git events in the audit log.


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


4. A pull request created by the Copilot coding agent needs to be automatically closed if it fails to pass required checks after three retry attempts, per your organization's governance policy. What should you configure?

A) .copilotignore
B) /compact
C) A repository ruleset with agent-specific merge conditions and CI enforcement
D) agents.md


5. Drag and Drop Question
You have a GitHub repository that uses GitHub Actions for CI on pull requests.
You have a GitHub Copilot coding agent that opens pull requests for backlog items, and your company requires automated checks for agent-generated changes.
You plan to standardize success criteria so that pull requests created by agents only succeed when unit tests pass and CodeQL analysis completes.
You need to configure a GitHub Actions workflow that runs on pull requests, executes unit tests, and performs CodeQL analysis.
How should you complete the workflow? To answer, drag the appropriate values to the correct targets. Each value 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:

Question # 1
Answer: D
Question # 2
Answer: B
Question # 3
Answer: A,E
Question # 4
Answer: C
Question # 5
Answer: Only visible for members

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