Microsoft GH-600 Valid Test : GitHub Agentic AI Developer

  • Exam Code: GH-600
  • Exam Name: GitHub Agentic AI Developer
  • Updated: Aug 22, 2026
  • Q&As: 85 Questions and Answers

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Microsoft GH-600 Exam Syllabus Topics:

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

Microsoft GitHub Agentic AI Developer Sample Questions:

1. You have a GitHub repository.
You use the GitHub Copilot CLI to run an agentic workflow from the terminal.
During execution, the conversation history approaches the context limit. The agent cannot continue the current session unless the amount of retained context is reduced.
You need to continue the current session without losing all the prior progress.
Which Copilot CLI slash command should you run?

A) /yolo
B) /clear
C) /compact
D) /context


2. You have multiple GitHub Copilot coding agents that run tasks concurrently.
You live stream the session log output and see the following.

What is a possible cause of the error?

A) a GitHub app installation policy
B) a Copilot firewall policy
C) a postToolUse hook
D) a preToolUse hook


3. Drag and Drop Question
You have a GitHub repository that uses a custom GitHub Copilot coding agent defined in the rollout-bot.agent.md file.
You need to update a workflow so that agent-profile changes can be rolled back by reverting a single commit and rerunning the workflow. The workflow must check out the exact commit being deployed and apply the agent profile from the repository at that commit.
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.


4. Hotspot Question
You have a GitHub repository that uses GitHub Actions to validate pull requests opened by the GitHub Copilot coding agent. The workflow runs unit tests and a linter on pull request triggers, and Copilot opens draft pull requests on dedicated branches while iterating by using commits.
You discover that when multiple Copilot sessions push updates to the same pull request branch in quick succession, multiple workflow runs execute concurrently.
You need to enable parallel workflow executions across different pull request branches.
How should you configure workflow-level concurrency? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.


5. You have a GitHub Enterprise repository that runs an autonomous agent by using a GitHub Actions workflow. The workflow has the following jobs:
- agent-run that generates trace.json and plan.md
- review that waits for human approval before continuing
- deploy that uses the outputs from agent-run
You need to make the files inspectable in the GitHub Actions UI and ensure that the files are available to the review and deploy jobs.
What should you do in the workflow?

A) Commit trace.json and plan.md back to the repository from agent-run.
B) Use dependency caching to store trace.json and plan.md.
C) Store trace.json and plan.md on a network share and have later jobs retrieve them from the share.
D) Upload trace.json and plan.md as workflow artifacts in agent-run, and download the files inside the jobs.


Solutions:

Question # 1
Answer: C
Question # 2
Answer: D
Question # 3
Answer: Only visible for members
Question # 4
Answer: Only visible for members
Question # 5
Answer: D

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