2026 Latest GH-600 Learning Materials | Valid Microsoft GH-600: Developing in Agentic AI Systems 100% Pass

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Microsoft GH-600 Exam Syllabus Topics:

SectionWeightObjectives
Implement agents and multi-agent systems30%- Build agents with Azure AI tools and frameworks
  • 1. Implement agent logic and reasoning
    • 2. Integrate models and prompts
      • 3. Develop using Semantic Kernel and Azure AI Foundry
        - Orchestrate multi-agent collaboration
        • 1. Implement workflows and coordination strategies
          • 2. Manage agent handoffs and task distribution
            • 3. Define communication protocols between agents
              Integrate tools, data, and services25%- Connect data sources and knowledge bases
              • 1. Integrate vector databases and search
                • 2. Implement retrieval-augmented generation (RAG)
                  • 3. Ensure data security and access control
                    - Incorporate external tools and APIs
                    • 1. Design and register tool definitions
                      • 2. Implement function calling and service integration
                        • 3. Handle authentication and error resilience
                          Design agentic AI solutions25%- Design agent architecture
                          • 1. Plan tool integration and orchestration
                            • 2. Select agent patterns and topologies
                              • 3. Design memory and state management
                                - Define requirements for agentic systems
                                • 1. Plan for responsible AI and governance
                                  • 2. Define functional and non-functional requirements
                                    • 3. Identify use cases and scenarios
                                      Test, deploy, and monitor agentic AI systems20%- Validate agent performance and safety
                                      • 1. Evaluate quality metrics and iterate
                                        • 2. Apply guardrails and content safety
                                          • 3. Test reasoning accuracy and consistency
                                            - Deploy and monitor agents at scale
                                            • 1. Optimize cost, latency, and throughput
                                              • 2. Implement logging, telemetry, and observability
                                                • 3. Deploy to Azure AI and cloud environments

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                                                  Microsoft Developing in Agentic AI Systems Sample Questions (Q44-Q49):

                                                  NEW QUESTION # 44
                                                  You are about to start a complex refactoring task in the GitHub Copilot CLI.
                                                  Before Copilot makes any changes, you need to review and agree on the approach.
                                                  What should you do first?

                                                  Answer: D

                                                  Explanation:
                                                  The first action you should take is to switch to Agent mode or use the Plan agent to review, edit, and approve a detailed step-by-step Markdown plan before any code is modified.
                                                  Use the Plan Agent: If available in your environment, trigger the plan phase so Copilot scans your codebase in a read-only state to outline its entire approach first.
                                                  Review the Proposed Plan: Carefully inspect the resulting Markdown structure to catch any architectural issues or wrong directions before the "doing" phase begins.
                                                  Utilize edit Mode Intentionally: Alternatively, if you prefer granular control over file adjustments rather than a fully autonomous agent workflow, opt for edit mode. This allows you to specifically select the target files and describe the natural language updates manually.
                                                  Reference:
                                                  https://aidevme.com/think-before-you-build-github-copilots-plan-agent-in-visual-studio-structured-ai-assisted-development/


                                                  NEW QUESTION # 45
                                                  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.

                                                  Answer:

                                                  Explanation:


                                                  NEW QUESTION # 46
                                                  Your company uses GitHub Copilot custom agents in Microsoft Visual Studio Code.
                                                  The company also uses the Copilot coding agent on GitHub issues.
                                                  You have a file named .planner.agent.md that defines an agent named planner. planner has tools set to ['search', 'read', 'fetch']. There are explicit instructions NOT to write or modify any code. The file also defines a handoff labeled Start Implementation to an agent named implementer and sets send to false.
                                                  Developers report that after the planner agent produces a plan, implementation sometimes starts immediately in the same conversation and code changes appear without an explicit agent switch.
                                                  When Copilot-created pull requests stall, maintainers review the pull request timeline and session logs. Several stalled sessions show outbound network commands blocked by a firewall, and the repositories do NOT contain a .github/copilot-instructions.md file.
                                                  For each statement, select Yes or No.

                                                  Answer:

                                                  Explanation:


                                                  NEW QUESTION # 47
                                                  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: B

                                                  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 # 48
                                                  You have a GitHub repository that uses the GitHub Copilot coding agent. The repository uses strict branch protections on the main branch.
                                                  You maintain a long-lived branch named release/1.4 that has different dependencies and CI checks.
                                                  You need the agent to create a hotfix that is implemented and validated against the release/1.4 branch. The solution must prevent the agent from basing its work on main.
                                                  What should you do?

                                                  Answer: A

                                                  Explanation:
                                                  Selecting release/1.4 as the base branch establishes the correct repository context before the agent begins its assignment. GitHub documents that Copilot creates its working branch from the selected base branch. This ensures that the initial code, dependency declarations, and branch-specific files correspond to the release being repaired.
                                                  That distinction matters because a hotfix developed against main may depend on APIs, package versions, or build behavior that do not exist in the maintained release. Choosing the release branch at task creation removes the need for the agent to infer or subsequently correct its starting point. The task should also require validation using the release's applicable checks.
                                                  Option A controls concurrency rather than branch selection. Option B governs review requirements for changes to main; it does not determine where the agent starts. Option C supplies a natural-language instruction but is less direct than configuring the actual base branch before execution.
                                                  The selected answer configures the execution environment through the platform's supported task controls.
                                                  Relevant curriculum topics are branch-based scope, execution-context selection, and environment-specific constraints.
                                                  Reference:


                                                  NEW QUESTION # 49
                                                  ......

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