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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 - Plan agent deployment, monitoring, and maintenance - Define agent purpose, scope, and success criteria - Integrate agents into software development lifecycle |
| Topic 2: Manage memory, state, and execution | 10–15% | - Choose memory types: short-term, long-term, external - Handle execution flow, retries, and interruptions - Scope and persist agent state correctly - Implement memory cleanup and expiration rules |
| Topic 3: Implement guardrails and accountability | 10–15% | - Add validation, review, and approval gates - Log actions, decisions, and changes for audit - Enforce least privilege and security boundaries - Ensure compliance, safety, and responsible use |
| Topic 4: Implement tool use and environment interaction | 20–25% | - Manage permissions and environment access - Configure and extend GitHub Copilot agents - Implement tools, custom actions, and MCP servers - Connect agents to codebase, APIs, and external systems |
| Topic 5: Perform evaluation, error analysis, and tuning | 15–20% | - Diagnose failures, hallucinations, and unexpected behavior - Define metrics and quality standards for outputs - Test, validate, and compare agent results - Optimize prompts, tools, and behavior through iteration |
| Topic 6: Orchestrate multi-agent coordination | 15–20% | - Monitor and troubleshoot multi-agent execution - Design workflows for multiple agents - Prevent conflicts and manage shared resources - Define communication and handoff protocols |
Microsoft GitHub Agentic AI Developer Sample Questions:
1. You have a GitHub Enterprise repository that uses the GitHub Copilot coding agent and opens draft pull requests for assigned issues.
Evaluation results show that the agent repeatedly opens pull requests that modify .github/workflows/*.yml to bypass failing checks instead of fixing the underlying code.
You need to ensure that the agent fixes the underlying code instead of bypassing the failing checks.
What should you do?
A) Create a branch ruleset.
B) Start the GitHub Copilot CLI by using --allow-all.
C) Update .github/copilot-instructions.md.
D) Disable GitHub Actions workflows for pull requests created by the agent.
2. Hotspot Question
You have a GitHub repository that uses GitHub Actions for CI.
Your team is piloting the GitHub Copilot coding agent to autonomously create branches and open pull requests. The repository follows trunk-based development that uses main as the default branch.
You need to ensure that the agent meets the following requirements:
- Changes to main can occur only by using pull requests that have at
least one approval.
- When a pull request is opened, a validation workflow runs, and the
agent can still create branches and open pull requests autonomously.
How should you configure the repository? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
3. While using agent mode in VS Code, you want Copilot to run a specific test suite as a validation step after making changes, without manually invoking the terminal each time. What feature enables this?
A) MCP server integration
B) .copilotignore
C) Tool/terminal invocation permissions in agent mode
D) CODEOWNERS
4. Case Study 2
Existing Environment
GitHub Environment
The GitHub environment contains the following:
- Three repositories named product-api, billing-service, and infra-terraform.
- Branch protection on the main branch in all repositories that requires at least one pull request review before merging
- GitHub Actions runners used across all workflows
- A GitHub team named SG_Dev that contains developers
- A GitHub team named SG_Review that contains senior engineers and a security team
- A .github/copilot-instructions.md file that includes general coding conventions for all features Agent environment The product-api repository uses a GitHub Copilot coding agent named agent1 that has the following configurations:
- No custom agent profile is defined.
- A Model Context Protocol (MCP) server named MCP1 is deployed to
https://mcp.litwareinc.internal and provides access to internal ticketing and deployment APIs.
MCP1 requires an API key for authentication.
A second Copilot coding agent named agent2 handles changes in infra-terraform and runs in parallel with agent1 when both agents have open assigned issues.
Copilot memory is NOT enabled for the organization.
Problem Statements
Litware identifies the following issues:
- During two recent sessions, agent1 accessed files in billing-service, which is outside the agent's intended scope.
- agent1 makes code changes immediately after receiving a task.
- A developer named Ben, who is on the SG_Dev team, reports that agent1 completed a session with a successful status and opened a pull request, but the pull request contains no file changes.
Other developers report this intermittently as well.
- Both agent1 and agent2 modified shared/config.yaml in a parallel test run, generating conflicting outputs.
agent1 consistently uses raw try-catch blocks for error handling, which violates the defined implementation guidelines of SG_Dev.
Requirements
Planned Changes
Litware plans to make the following changes:
- Ensure that agent1 can access all the tools in the environment.
- Provide product-api with specific instructions to agent1 without affecting Copilot Chat or Copilot code review.
- Configure MCP1 as a tool for agent1 by modifying the product-api repository MCP configuration.
- Ensure that Copilot retains details that it has learned and uses that knowledge for future work.
This must be applied to all licensed members of the organization.
Implementation guidelines
The development team at Litware identifies the following implementation guidelines:
- Agent workflows must be able to run in parallel.
- Application error handling must use the repository ErrorHandler class.
- agent1 and agent2 must run on isolated branches during parallel execution. File-level conflicts must be detected before merges, and both agents must be able to run concurrently.
Security requirements
Litware identifies the following security requirements:
- Only the members of SG_Review must be able to approve agent1 plan outputs.
- All API keys must be stored and accessed securely.
- The developers must NOT be able to self-approve.
Agent configuration
You need to resolve the issue of the agents generating conflicting output. The solution must meet the implementation guidelines.
What should you do?
A) Configure a concurrency group on both agent workflows so that only one workflow runs at a time.
B) Configure each agent to work on a separate branch and add a required status check that detects file-level overlap before either pull request can be merged.
C) Add shared/config.yaml to a CODEOWNERS file that requires SG_Review approval before any changes can be merged.
D) Configure tools: ['read', 'search'] in both agent profiles to prevent either agent from writing files.
5. You want a reusable, shareable set of instructions that defines a specific persona/workflow (e.g.,
"security reviewer") that developers can invoke on demand in Copilot Chat, rather than instructions applied globally to every session. What should you create?
A) .copilotignore
B) A prompt file (.prompt.md)
C) agents.md
D) copilot-instructions.md
Solutions:
| Question # 1 Answer: A | Question # 2 Answer: Only visible for members | Question # 3 Answer: C | Question # 4 Answer: A | Question # 5 Answer: B |







