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Microsoft GH-600 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Implement guardrails and accountability | 10-15% | - Implement guardrails and human-in-the-loop workflows
|
| Topic 2: Perform evaluation, error analysis, and tuning | 15-20% | - Tune agent behavior based on evaluation results
|
| Topic 3: Manage memory, state, and execution | 10-15% | - Persist agent state and manage context drift
|
| Topic 4: Implement tool use and environment interaction | 20-25% | - Integrate agents within development environments
|
| Topic 5: Orchestrate multi-agent coordination | 15-20% | - Configure observability for multi-agent behavior by using logs, artifacts, and operational signals
|
| Topic 6: Prepare agent architecture and SDLC processes | 15-20% | - Configure observability and control for autonomous agents
|
Microsoft Developing in Agentic AI Systems Sample Questions:
You need to enable Copilot memory to support the planned changes.
What should you configure?
- A. The agent profile of agent1
- B. The Copilot settings of the organization
- C. The personal Copilot settings of each developer
- D. The Copilot settings of each repository
Correct Answer: B 🗳️
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. Dependency alerts that identify vulnerable package versions in the repository
- B. CodeQL findings that identify security vulnerabilities in the generated code
- C. Linting errors from the repository's CI pipeline configured in GitHub Actions
- D. The detection of hardcoded secrets, such as API keys and tokens
- E. The median time to merge metric reported on the Copilot usage metrics dashboard
Correct Answer: B,D 🗳️
Explanation: Only visible for Prep4cram members. You can sign-up / login (it's free).
You have a GitHub repository that uses the GitHub Copilot coding agent.
The agent is assigned to a long-running issue and has already opened a draft pull request linked to the issue. The pull request timeline shows Copilot started work and the pull request description shows periodic status updates.
After 70 minutes, the pull request stops receiving new commits, and the agent session log indicates that the session has timed out. In a pull request comment thread, the agent then proposes changes that no longer match the latest repository guidance.
You need to resume execution in a way that reestablishes the correct context and produces new commits in the existing draft pull request.
What should you do?
- A. Create a new issue and assign the issue to Copilot.
- B. Close and reopen the issue.
- C. Post a pull request comment that mentions @copilot.
- D. Select Approve and run workflows in the pull request merge box.
Correct Answer: C 🗳️
Explanation: Only visible for Prep4cram members. You can sign-up / login (it's free).
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.
Correct Answer:
You have a GitHub repository that runs an agentic software development lifecycle workflow by using GitHub Actions. The workflow uses the following three executors implemented as scripts: spec_analyzer, risk_reviewer, and plan_merger.
You need to coordinate multiple specialized agents so that analysis and risk review run in parallel and then a final executor merges the outputs into a single plan. The orchestration pattern must fan out one request to multiple executors and then fan in the results to a final executor.
How should you complete the workflow definition? To answer, drag the appropriate values to the correct targets.
Correct Answer:
