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| Section | Weight | Objectives |
|---|---|---|
| Test, deploy, and monitor agentic AI systems | 20% | - Validate agent performance and safety
|
| Implement agents and multi-agent systems | 30% | - Build agents with Azure AI tools and frameworks
|
| Integrate tools, data, and services | 25% | - Incorporate external tools and APIs
|
| Design agentic AI solutions | 25% | - Define requirements for agentic systems
|
>> GH-600 Exam Objectives Pdf <<
Microsoft GH-600 certification exams play a significant role to verify skills, experience, and knowledge in a specific technology. Enrollment in the Developing in Agentic AI Systems GH-600 is open to everyone. Participants in the Developing in Agentic AI Systems GH-600 come from all over the world and receive the credentials for the Microsoft GH-600. They can quickly advance their careers in the fiercely competitive market and benefit from certification after earning the Developing in Agentic AI Systems GH-600 badge.
NEW QUESTION # 26
You have a GitHub repository that uses GitHub Copilot Chat in Microsoft Visual Studio Code. Custom agents are stored in the repository under version control.
Your team uses a multi-agent workflow where a planner agent produces an implementation plan that is then handed off to an implementation agent to make changes.
Recent prompts cause the planner agent to start editing files and running commands before the plan is approved.
You need to configure the planner agent to meet the following requirements:
Use only read-only tools.
Hand off to the implementation agent only after the plan is approved.
How should you configure the agent? To answer, select the appropriate options in the answer area.
Answer:
Explanation:
NEW QUESTION # 27
You have a GitHub repository that uses GitHub Copilot code review on pull requests.
You plan to add repository-wide code review guidance that will apply to all files.
You need Copilot code review to consistently apply the guidance during pull request reviews.
What should you do?
Answer: C
Explanation:
To apply repository-wide code review guidance that consistently impacts all pull request reviews, you must create a .github/copilot-instructions.md file in the root directory of your repository.
GitHub Copilot code review automatically ingests this file to use as a persistent checklist for every file change it analyzes.
Reference:
https://docs.github.com/en/copilot/how-tos/copilot-on-github/customize-copilot/add-custom-instructions/add-repository-instructions
NEW QUESTION # 28
Hotspot Question
You have the following agent logs.
For each of the following statements, select Yes if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
Box 1: Yes
Yes, the agent did respond with messages.
Markdown Message: The log ccreq:XXX.copilotmd | markdown message 0 returned: finish reason: [stop] indicates that a text-based markdown response was successfully generated and completed.
Language Model Output: The log ccreq:XXX.copilotmd shows the core language model (gpt-4o- mini) completed its request, delivering the main content of the message.
Box 2: Yes
Based on the log entries provided, yes, the agent can edit files in the repository.
Evidence from the LogsTargeted Component: The final three log entries explicitly target the component [panel/editAgent].
Model Selection: For these specific tasks, the system switches from standard conversational models (gpt-4o-mini) to a specialized code-generation model: gpt-5.3-codex.
Processing Time: These operations take significantly longer than standard chat generation, which is characteristic of complex code-parsing and file-modification tasks.
Box 3: Yes
Based on the log entries provided, yes, the agent analyzed files in the repository.
Action Type: The final three entries explicitly call the [panel/editAgent] capability.
Model Used: These actions utilized the gpt-5.3-codex model, which is specialized for codebases.
Operation Duration: The execution times were significantly longer.
Implied Task: Code-generation and editing agents require repository file analysis to perform edits.
Reference:
https://learn.microsoft.com/en-us/troubleshoot/power-platform/copilot-studio/authoring/error-codes
NEW QUESTION # 29
An enterprise administrator wants to audit which repositories have had Copilot coding agent- created pull requests over the last 30 days. Where should the administrator look?
Answer: D
Explanation:
GitHub's organization/enterprise audit log records agent activity, including pull requests created by the Copilot coding agent, giving administrators visibility for compliance and governance purposes.
NEW QUESTION # 30
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?
Answer: B
Explanation:
To prevent the GitHub Copilot coding agent from modifying your workflow files, you should configure GitHub branch protection rules or repository rulesets to restrict modifications to the .github/workflows/ directory.
You should create a branch ruleset.
Creating a branch ruleset with a "Restrict file paths" rule is the most effective solution. By blocking any pull request from modifying .github/workflows/*, you force the agent to find solutions within the codebase rather than altering the CI/CD pipeline.
Reference:
https://docs.github.com/en/copilot/how-tos/use-copilot-agents/cloud-agent/troubleshoot-cloud-agent
NEW QUESTION # 31
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