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Microsoft GH-600 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Prepare agent architecture and SDLC processes | 15–20% | - Design agent autonomy and decision boundaries - Integrate agents into software development lifecycle - Define agent purpose, scope, and success criteria - Plan agent deployment, monitoring, and maintenance |
| Topic 2: 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 3: Orchestrate multi-agent coordination | 15–20% | - Define communication and handoff protocols - Prevent conflicts and manage shared resources - Design workflows for multiple agents - Monitor and troubleshoot multi-agent execution |
| Topic 4: Perform evaluation, error analysis, and tuning | 15–20% | - Optimize prompts, tools, and behavior through iteration - Test, validate, and compare agent results - Define metrics and quality standards for outputs - Diagnose failures, hallucinations, and unexpected behavior |
| Topic 5: Manage memory, state, and execution | 10–15% | - Handle execution flow, retries, and interruptions - Scope and persist agent state correctly - Implement memory cleanup and expiration rules - Choose memory types: short-term, long-term, external |
| Topic 6: Implement tool use and environment interaction | 20–25% | - Connect agents to codebase, APIs, and external systems - Implement tools, custom actions, and MCP servers - Manage permissions and environment access - Configure and extend GitHub Copilot agents |
Microsoft GitHub Agentic AI Developer Sample Questions:
1. Hotspot Question
Your company uses Microsoft Visual Studio Code and GitHub Copilot Chat.
You have a GitHub repository that uses main as the default branch. The repository contains a workspace custom agent stored at .github/agents/release-notes.agent.md.
A developer switches to a branch named branch1 where the agent file does NOT exist. In the same session, the developer switches to a user profile named profile1.profile1 contains a custom agent file named release-notes.agent.md that has user-invokable set to false.
For each of the following statements, select Yes if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.
2. 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.
Before App1 is upgraded, you need to verify each individual upgrade step and whether all tests have passed.
Which file should you use?
A) tasks.md
B) assessment.md
C) agent.md
D) plan.md
3. 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) Wait for the agent to complete.
B) Select Approve and run workflows in the pull request merge box.
C) Merge the draft pull request and mention @copilot on the merged pull request.
D) Unassign the issue from Copilot, and then reassign the issue to Copilot.
4. 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) Edit mode
C) Inline mode
D) Agent mode
5. Drag and Drop Question
Your team uses a remote GitHub Model Context Protocol (MCP) server for workflows in the software development life cycle (SDLC).
You need to commit a workspace-scoped MCP configuration to ensure that GitHub Copilot can connect to the GitHub-hosted MCP endpoint and authenticate by using a GitHub personal access token (PAT).
How should you complete the mcp.json configuration file? 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: Only visible for members | Question # 2 Answer: B | Question # 3 Answer: D | Question # 4 Answer: D | Question # 5 Answer: Only visible for members |
