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| Certification Vendor: | Microsoft / GitHub |
| Exam Name: | Developing in Agentic AI Systems (GH-600) - GitHub Agentic AI Developer |
| Exam Number: | GH-600 |
| Certificate Validity Period: | 1 year (renewable annually) |
| Exam Duration: | 120 minutes |
| Exam Format: | Multiple choice, Scenario-based questions, Drag and drop, Case studies, Interactive exam components |
| Related Certifications: | GitHub Copilot Certification GitHub Advanced Security Certifications |
| Available Languages: | English |
| Passing Score: | 700 (scaled score) |
| Recommended Training: | Microsoft Learn - GH-600 Study Guide GitHub Advanced Security learning paths |
| Exam Registration: | Official certification page (Microsoft Learn) Schedule exam (Pearson VUE via Microsoft credentials portal) |
| Sample Questions: | Microsoft GH-600 Sample Questions |
| Exam Way: | Online proctored exam via Pearson VUE; interactive and scenario-based tasks included. |
| Pre Condition: | Experience with SDLC workflows, GitHub Actions, GitHub Copilot, and basic AI agent concepts (tool use, orchestration, and prompt-driven systems). |
| Official Syllabus URL: | https://learn.microsoft.com/en-us/credentials/certifications/agentic-ai-developer/ |
| Section | Weight | Objectives |
|---|---|---|
| Manage memory, state, and execution | 10–15% | - Agent memory strategies
|
| Evaluation, error analysis, and tuning | 15–20% | - Failure analysis
|
| Implement tool use and environment interaction | 20–25% | - MCP server configuration
|
| Implement guardrails and accountability | 10–15% | - Guardrails and human-in-the-loop
|
| Prepare agent architecture and SDLC processes | 15–20% | - Observability and control
|
| Orchestrate multi-agent coordination | 15–20% | - Observability and auditability
|
1. You want the GitHub Copilot coding agent to follow project-specific conventions (coding style, testing requirements, folder structure) on every task it performs in a repository. What should you create?
A) A .copilotignore file
B) A CODEOWNERS file
C) A agents.yml workflow file
D) A copilot-instructions.md file in .github/
2. Drag and Drop Question
You have a GitHub repository that uses a custom GitHub Copilot coding agent defined in the rollout-bot.agent.md file.
You need to update a workflow so that agent-profile changes can be rolled back by reverting a single commit and rerunning the workflow. The workflow must check out the exact commit being deployed and apply the agent profile from the repository at that commit.
How should you complete the workflow? To answer, drag the appropriate values to the correct targets. Each value 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.
3. After several long agentic sessions, you notice degraded response quality and want the agent to retain a concise summary of prior progress rather than the full raw history, while continuing without interruption. Which approach addresses this?
A) --allow-all
B) /compact
C) /clear
D) .copilotignore
4. You have a GitHub repository.
You use the GitHub Copilot CLI to run an agentic workflow from the terminal.
During execution, the conversation history approaches the context limit. The agent cannot continue the current session unless the amount of retained context is reduced.
You need to continue the current session without losing all the prior progress.
Which Copilot CLI slash command should you run?
A) /context
B) /yolo
C) /compact
D) /clear
5. 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 configure agent1 to support the planned changes.
What should you do?
A) Add the mcp-servers property to the agent configuration.
B) In the agent configuration, replace line 05 with the following.05 tools: [].
C) Delete line 05 from the agent configuration.
D) Add Use all available tools to the .github/copilot-instructions.md file.
E) Add Use all available tools to the instructions in the agent configuration.
Solutions:
| Question # 1 Answer: D | Question # 2 Answer: Only visible for members | Question # 3 Answer: B | Question # 4 Answer: C | Question # 5 Answer: C |
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