• Exam Code: GH-600
  • Exam Name: Developing in Agentic AI Systems
  • Certification Provider: Microsoft
  • Corresponding Certification:GitHub Administrator
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Microsoft GH-600 Exam Syllabus Topics:

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

                                                  Microsoft Developing in Agentic AI Systems Sample Questions:

                                                  You have a GitHub Enterprise Cloud organization that uses GitHub Actions for CI/CD.
                                                  You plan to enable an agent to update and deploy workflows that access production environment secrets.
                                                  You need to select an autonomy level for a compliance-sensitive workflow.
                                                  Which autonomy level should you select?

                                                  • A. Autonomous execution limited to non-production environments
                                                  • B. Read-only analysis with no ability to trigger workflows
                                                  • C. Fully autonomous execution without approvals
                                                  • D. Human-in-the-loop with required manual approvals for production
                                                  Reveal Solution  Discussion  0

                                                  Correct Answer: D  🗳️

                                                  Explanation: Only visible for ITPassLeader 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.

                                                  Reveal Solution  Discussion  0

                                                  Correct Answer:


                                                  Explanation:
                                                  Requirement
                                                  Action
                                                  To allow cross-device tool access without local setup
                                                  Use a GitHub-hosted Model Context Protocol (MCP) server for cloud-based workflows.
                                                  To enable organization-wide agent tools across all Copilot environments Enable the MCP servers in Copilot policy.
                                                  A GitHub-hosted MCP server provides cloud-based tools that are not dependent on a developer's local Visual Studio Code installation. This enables the same service capability to be used from github.com and from supported development environments without requiring each device to run or configure a local server.
                                                  Enabling MCP servers through Copilot policy establishes organization-wide governance over which MCP capabilities are available. This is the appropriate administrative control when the organization needs consistent access across Copilot environments.
                                                  Running an MCP server in Docker can support local development, but it does not satisfy the requirement for access from any device without local setup. Changing a Copilot mode affects interaction behavior rather than tool availability. Restricting toolsets can reduce exposure, but it does not make an MCP server available across environments.
                                                  Study-guide topics: MCP hosting, cross-environment tools, organizational policy, and agent portability.
                                                  Topic 1, GitHub Environment
                                                  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 want to prevent GitHub Copilot from ever suggesting completions or making edits inside a directory containing sensitive credentials templates. What should you configure?

                                                  • A. Branch protection rules
                                                  • B. A repository ruleset
                                                  • C. A CODEOWNERS file
                                                  • D. A .copilotignore file
                                                  Reveal Solution  Discussion  0

                                                  Correct Answer: D  🗳️

                                                  Explanation: Only visible for ITPassLeader members. You can sign-up / login (it's free).

                                                  You need to implement agent2 to meet the technical requirements.
                                                  How should you complete the YAML configuration? To answer, select the appropriate options in the answer area.
                                                  NOTE: Each correct selection is worth one point.
                                                  HOTSPOT
                                                  name: implementation-planner
                                                  description: Creates detailed implementation plans and technical specifications in markdown format tools: [
                                                  < Dropdown 1 > ,
                                                  < Dropdown 2 > ,
                                                  ' microsoftdocs/mcp/docs_search ' ,
                                                  ' microsoftdocs/mcp/docs_fetch '
                                                  ]
                                                  The accompanying image includes empty dropdown controls and recreated practice alternatives.

                                                  Reveal Solution  Discussion  0

                                                  Correct Answer:


                                                  Explanation:
                                                  Target
                                                  Selection
                                                  Dropdown 1
                                                  ' search '
                                                  Dropdown 2
                                                  ' read '
                                                  The visible configuration describes an implementation planner. Providing search and read supports the information-gathering work needed to produce a technically grounded plan: locating relevant code and inspecting its contents. The listed documentation tools supplement repository context with external technical reference material.
                                                  This tool selection also establishes a practical boundary between planning and implementation. A planner can explain proposed changes and produce Markdown in its response without needing permission to modify repository files. Granting editing or command-execution capabilities would expand its authority beyond the visible planning role.
                                                  The distinction between generating Markdown and saving a Markdown file is important. The selected tools support producing a plan in conversation. If the requirements instead demanded that the planner write that plan directly into the repository, an appropriate file-writing capability or a separate persistence step would be necessary.
                                                  Tool names must also resolve to capabilities available in the configured environment. Merely listing a documentation tool does not install or authenticate its MCP server.
                                                  Study-guide topics: tool selection, least-privilege planning, and environment capabilities. Reference: VS Code-Use tools with agents .

                                                  You have a GitHub Enterprise Cloud repository that uses the GitHub Copilot coding agent.
                                                  Engineers assign issues to Copilot, and Copilot creates draft pull requests. The engineers start tasks either by assigning issues on github.com or by using GitHub Copilot Chat in an IDE. Reviewers request updates by leaving pull request comments.
                                                  You discover that sometimes, Copilot uses outdated requirements after a reviewer posts an updated instruction in a pull request comment, and, in several cases, Copilot fails to resume work from the comment.
                                                  You need to ensure that iteration requests are applied to the correct pull request session and are processed consistently.
                                                  What should you do?

                                                  • A. Start a new task from Copilot Chat in the IDE. Instruct the reviewer to mention @github in the task comments.
                                                  • B. Ensure that the reviewer has write access to the repository. Instruct the reviewer to mention @copilot in the pull request comments.
                                                  • C. Ensure that the agent has write access to the repository. Instruct the reviewer to unassign and reassign the original issue to Copilot.
                                                  • D. Ensure that the agent has write access to the repository. Instruct the reviewer to mention @github in the task comments.
                                                  Reveal Solution  Discussion  0

                                                  Correct Answer: B  🗳️

                                                  Explanation: Only visible for ITPassLeader members. You can sign-up / login (it's free).

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