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Microsoft GH-600 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Manage memory, state, and execution | 10–15% | - Ensure continuity of agent memory and state across tools and environments
|
| Implement tool use and environment interaction | 20–25% | - Integrate agents within development environments
|
| Prepare agent architecture and SDLC processes | 15–20% | - Integrate agents into the software development lifecycle (SDLC)
|
| Perform evaluation, error analysis, and tuning | 15–20% | - Define success criteria and evaluation signals for agent tasks
|
| Orchestrate multi-agent coordination | 15–20% | - Manage the lifecycle of agents within multi-agent workflows
|
| Implement guardrails and accountability | 10–15% | - Implement guardrails and human-in-the-loop workflows
|
Microsoft Developing in Agentic AI Systems Sample Questions:
Question #1
You have a GitHub Enterprise organization that uses GitHub Copilot.
You discover that GitHub Copilot Chat responses in Microsoft Visual Studio Code are influenced by earlier, unrelated troubleshooting prompts from the same conversation.
You need to ensure that the Copilot Chat conversation context is limited to information relevant to the current work item. The solution must minimize effort.
What should you do? To answer, select the appropriate options in the answer area.
Question #2
You need to enable Copilot memory to support the planned changes.
What should you configure?
A. The personal Copilot settings of each developer
B. The Copilot settings of each repository
C. The Copilot settings of the organization
D. The agent profile of agent1
Question #3
You have a GitHub Copilot coding agent that has completed a pull request for a security fix in your repository.
Before merging, you need to evaluate the quality of the agent's work by using both automated evaluation signals and human review.
You review the session log and the pull request.
What are two automated security scanning signals available for the pull request? Each correct answer presents a complete solution.
NOTE: Each correct selection is worth one point.
A. The median time to merge metric reported on the Copilot usage metrics dashboard
B. The detection of hardcoded secrets, such as API keys and tokens
C. Linting errors from the repository's CI pipeline configured in GitHub Actions
D. CodeQL findings that identify security vulnerabilities in the generated code
E. Dependency alerts that identify vulnerable package versions in the repository
Question #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. .copilotignore
B. Tool/server allow-list in the MCP client configuration
C. /usage
D. Repository ruleset
Question #5
You have a GitHub Enterprise Cloud organization that has Copilot agents enabled.
You discover activity in a repository.
You need to identify whether the activity was initiated by an agent.
Which two audit log fields can you use? Each correct answer presents a complete solution.
A. user
B. actor_is_agent
C. agent_session_id
D. action
Solutions:
| Question #1 Correct Answer: Only visible for members | Question #2 Correct Answer: C | Question #3 Correct Answer: B,D | Question #4 Correct Answer: B | Question #5 Correct Answer: B,C |
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