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Microsoft GH-600 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Implement guardrails and accountability | 10–15% | - Ensure compliance, safety, and responsible use - Add validation, review, and approval gates - Log actions, decisions, and changes for audit - Enforce least privilege and security boundaries |
| Topic 2: Implement tool use and environment interaction | 20–25% | - Manage permissions and environment access - Connect agents to codebase, APIs, and external systems - Implement tools, custom actions, and MCP servers - Configure and extend GitHub Copilot agents |
| Topic 3: Orchestrate multi-agent coordination | 15–20% | - Define communication and handoff protocols - Prevent conflicts and manage shared resources - Monitor and troubleshoot multi-agent execution - Design workflows for multiple agents |
| Topic 4: Manage memory, state, and execution | 10–15% | - Scope and persist agent state correctly - Handle execution flow, retries, and interruptions - Choose memory types: short-term, long-term, external - Implement memory cleanup and expiration rules |
| Topic 5: Perform evaluation, error analysis, and tuning | 15–20% | - Define metrics and quality standards for outputs - Diagnose failures, hallucinations, and unexpected behavior - Optimize prompts, tools, and behavior through iteration - Test, validate, and compare agent results |
| Topic 6: Prepare agent architecture and SDLC processes | 15–20% | - Define agent purpose, scope, and success criteria - Integrate agents into software development lifecycle - Design agent autonomy and decision boundaries - Plan agent deployment, monitoring, and maintenance |
Microsoft GitHub Agentic AI Developer Sample Questions:
1. You are using GitHub Copilot Chat's agent mode in VS Code and want it to autonomously use tools (terminal, file edits, tests) to complete a multi-step task, checking in with you between major steps. What is this interaction mode called?
A) Ask mode
B) Agent mode
C) Edit mode
D) Inline mode
2. You have a GitHub Enterprise repository.
An agent opens pull requests to the main branch.
You need to ensure that changes to .github/workflows/* and /infra/* require approval from designated reviewers before merge.
What should you configure?
A) a branch protection rule and a CODEOWNERS file
B) a branch protection rule and copilot-instructions.md
C) a ruleset and a .copilotignore file
D) a ruleset and an agents.md file
3. You assigned an issue to the Copilot coding agent, and it opened a pull request. You want to inspect exactly what code changes were made before merging. Which CLI slash command lets you view the change set directly in the terminal?
A) /compact
B) /diff
C) /plan
D) /context
4. Case Study 1 - Contoso, Ltd
Overview
Contoso Ltd. is a software development company located in the United States.
Existing Environment
GitHub Environment
Contoso uses GitHub Enterprise and assigns GitHub Copilot Pro+ licenses to its developers. The developers use Microsoft Visual Studio Code as their IDE.
Contoso has a customer portal. The code for the portal is stored in a GitHub repository named repo1that contains the following:
- A custom agent named agent1 that includes instructions to review specs related to best practices
- A custom instruction file named validate-instructions.md that is used to validate tone of voice and applies to all .md and .txt files
- A custom instruction file named codereview.instructions.md that is used by the Copilot coding agent but is excluded for use by the Copilot code review repo1 has the following structure:
- The front-end is stored in the /frontend folder.
- The API logic is stored in the /api folder.
Contoso has a second repository named repo2 that contains a legacy .NET application named App1 built by using .NET 6. repo2 has a multi-agent workflow for modernization tasks.
Contoso enables the Model Context Protocol (MCP) registry and allows the Microsoft Learn MCP Server. Every developer must configure their own connection to the Learn MCP Server.
Problem Statements
The developers working in repo1 report that the Microsoft Learn documentation is NOT being retrieved when they attempt to validate a design by using agent1.
The testing team at Contoso identifies that the customer portal uses inconsistent UI styles, which leads to customer confusion and branding issues. The UI inconsistencies stem from variations in the folder structure.
Agent Logs
You have the following logs for the multi-agent workflow used in repo2.
Requirements
Planned Changes
Contoso plans to have all agents and developers in repo1use the Microsoft Learn MCP to ensure that reviews are validated by using the appropriate documentation. This must be implemented centrally.
Contoso plans to leverage AI-powered coding agents to implement new portal features and pages.
Technical Requirements
App1 must be upgraded to .NET 10. A previous upgrade attempt was started by using the Copilot modernization agent, but the attempt was never finalized.
You plan to retry the upgrade. You must first analyze App1 by using AI, and then generate a report that contains breaking changes and deprecated patterns before retrying the upgrade.
All AI-generated code for UI styling must adhere to a predefined folder structure.
The architects at Contoso need help building implementation plans for repo1. The company wants to implement a new agent named agent2 to analyze the code base and the code requirements, and then respond with a detailed plan. The agent must NOT be able to edit files or run local commands.
The developers must be able to delegate work to the Copilot coding agent by assigning issues to the agent.
Hotspot Question
You are evaluating the logs of the multi-agent workflow in repo2.
For each of the following statements, select Yes if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.
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.
Solutions:
| Question # 1 Answer: B | Question # 2 Answer: A | Question # 3 Answer: B | Question # 4 Answer: Only visible for members | Question # 5 Answer: A |
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