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Microsoft GH-600 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Manage memory, state, and execution | 10–15% | - Implement memory cleanup and expiration rules - Choose memory types: short-term, long-term, external - Handle execution flow, retries, and interruptions - Scope and persist agent state correctly |
| Topic 2: Prepare agent architecture and SDLC processes | 15–20% | - Integrate agents into software development lifecycle - Plan agent deployment, monitoring, and maintenance - Design agent autonomy and decision boundaries - Define agent purpose, scope, and success criteria |
| 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: Perform evaluation, error analysis, and tuning | 15–20% | - Diagnose failures, hallucinations, and unexpected behavior - Test, validate, and compare agent results - Optimize prompts, tools, and behavior through iteration - Define metrics and quality standards for outputs |
| Topic 5: Implement tool use and environment interaction | 20–25% | - Implement tools, custom actions, and MCP servers - Configure and extend GitHub Copilot agents - Connect agents to codebase, APIs, and external systems - Manage permissions and environment access |
| Topic 6: Implement guardrails and accountability | 10–15% | - Add validation, review, and approval gates - Ensure compliance, safety, and responsible use - Log actions, decisions, and changes for audit - Enforce least privilege and security boundaries |
Microsoft GitHub Agentic AI Developer Sample Questions:
1. Drag and Drop Question
Your company uses GitHub Copilot Enterprise.
Developers use GitHub Copilot agent mode in Microsoft Visual Studio Code on their laptops and Copilot Chat on github.com when they are away from their laptops.
When switching between environments, the developers notice that agent workflows lose continuity because the tools available in Visual Studio Code are unavailable on github.com.
You need to ensure that the agent tools and state are available consistently across environments and can be used from any device without local setup.
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.
2. An agent working through the Copilot coding agent in GitHub Actions needs additional build dependencies installed before it can run tests. Where should you define this setup?
A) copilot-instructions.md
B) copilot-setup-steps.yml
C) agents.md
D) .copilotignore
3. 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.
4. You are architecting an agentic AI system and need the agent's tool-calling behavior to be constrained so it can only call a specific allow-listed set of MCP tools, never arbitrary ones. What should you configure?
A) /usage
B) Tool/server allow-list in the MCP client configuration
C) .copilotignore
D) Repository ruleset
5. You have a GitHub Copilot coding agent named CodeAgent. The .agent.md file of CodeAgent contains the following YAML frontmatter.
---
name: CodeAgent
description: Performs repository analysis and code review tasks.
tools: ['edit', 'execute', 'read', 'search']
---
You need to issue a GitHub Copilot CLI command that preserves execution velocity for read-only tasks by eliminating approval prompts for low-risk tools. The solution must ensure that high-risk tools that can make changes remain available but still require explicit user approval before running.
Which command should you run?
A) copilot agent run CodeAgent --allow-all-tools
B) copilot agent run CodeAgent --deny-tool 'edit,execute'
C) copilot agent run CodeAgent --allow-tool 'read,search'
D) copilot agent run CodeAgent --allow-tool 'read,search' --deny-tool 'edit,execute'
E) copilot agent run CodeAgent
Solutions:
| Question # 1 Answer: Only visible for members | Question # 2 Answer: B | Question # 3 Answer: Only visible for members | Question # 4 Answer: B | Question # 5 Answer: D |
