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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Manage memory, state, and execution | 10–15% | - Handle execution flow, retries, and interruptions - Choose memory types: short-term, long-term, external - Implement memory cleanup and expiration rules - Scope and persist agent state correctly |
| Topic 2: Implement tool use and environment interaction | 20–25% | - Manage permissions and environment access - Connect agents to codebase, APIs, and external systems - Implement tools, custom actions, and MCP servers - Configure and extend GitHub Copilot agents |
| Topic 3: Implement guardrails and accountability | 10–15% | - Enforce least privilege and security boundaries - Log actions, decisions, and changes for audit - Ensure compliance, safety, and responsible use - Add validation, review, and approval gates |
| Topic 4: Prepare agent architecture and SDLC processes | 15–20% | - Plan agent deployment, monitoring, and maintenance - Define agent purpose, scope, and success criteria - Integrate agents into software development lifecycle - Design agent autonomy and decision boundaries |
| Topic 5: Perform evaluation, error analysis, and tuning | 15–20% | - Diagnose failures, hallucinations, and unexpected behavior - Test, validate, and compare agent results - Define metrics and quality standards for outputs - Optimize prompts, tools, and behavior through iteration |
| Topic 6: Orchestrate multi-agent coordination | 15–20% | - Monitor and troubleshoot multi-agent execution - Define communication and handoff protocols - Prevent conflicts and manage shared resources - Design workflows for multiple agents |
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NEW QUESTION # 74
You have a GitHub repository that contains an agent named Orchestrator. Orchestrator delegates work to the following specialized subagents:
Planner reviews issues and creates a plan of action.
Implementer writes code based on the plan of action.
Reviewer reviews the code.
You create a new agent named Summarizer that produces a concise summary of the work performed by the other agents.
You need to ensure that Orchestrator can invoke Summarizer as part of its workflow.
What should you do?
Answer: C
Explanation:
The configuration must be changed on the agent that performs the delegation. Orchestrator is responsible for coordinating the workflow, so its allowed subagent list must include Summarizer. Adding the new agent to that list makes it an available delegation target alongside Planner, Implementer, and Reviewer.
An agent's agents property identifies the custom agents it can invoke as subagents. The tools property serves a different purpose: it identifies available capabilities such as reading files, editing code, or invoking agents. Adding a custom agent's name to the tools list does not register that agent as a callable subagent. The agent invocation tool must also be available; the scenario already establishes that Orchestrator delegates to other subagents.
Changing Reviewer's configuration would enable a relationship originating from Reviewer, rather than the requested direct invocation by Orchestrator. A handoff also represents a different interaction pattern from having the orchestrating agent invoke a subagent and receive its result.
Availability does not force execution on every task. Orchestrator's instructions should indicate when a summary is required and what information it should contain.
Study-guide topics: delegation permissions, orchestrator responsibilities, and specialized subagents. Reference: VS Code-Subagents.
NEW QUESTION # 75
A developer uses the GitHub Copilot CLI in plan mode.
Copilot produces a plan.
What does Copilot do next?
Answer: B
Explanation:
In plan mode, after GitHub Copilot CLI analyzes your codebase and gathers requirements, it saves the plan to plan.md in your session folder.
What Happens Next?
1. Saves to plan.md: It writes the structured implementation plan with checkable tasks into a file called plan.md.
2. Waits for Approval: Copilot pauses and waits for your review. It will not begin implementation or make code modifications until you explicitly approve the strategy.
3. Execution: Once approved, you can hand the plan off to Copilot's agent/autopilot mode to begin the implementation.
Reference:
https://docs.github.com/en/copilot/how-tos/copilot-cli/cli-best-practices
NEW QUESTION # 76
Case Study 1 - Contoso, Ltd
Overview
Contoso Ltd. is a software development company located in the United States.
Existing Environment
GitHub Environment
Contoso uses GitHub Enterprise and assigns GitHub Copilot Pro+ licenses to its developers. The developers use Microsoft Visual Studio Code as their IDE.
Contoso has a customer portal. The code for the portal is stored in a GitHub repository named repo1that contains the following:
- A custom agent named agent1 that includes instructions to review specs related to best practices
- A custom instruction file named validate-instructions.md that is used to validate tone of voice and applies to all .md and .txt files
- A custom instruction file named codereview.instructions.md that is used by the Copilot coding agent but is excluded for use by the Copilot code review repo1 has the following structure:
- The front-end is stored in the /frontend folder.
- The API logic is stored in the /api folder.
Contoso has a second repository named repo2 that contains a legacy .NET application named App1 built by using .NET 6. repo2 has a multi-agent workflow for modernization tasks.
Contoso enables the Model Context Protocol (MCP) registry and allows the Microsoft Learn MCP Server. Every developer must configure their own connection to the Learn MCP Server.
Problem Statements
The developers working in repo1 report that the Microsoft Learn documentation is NOT being retrieved when they attempt to validate a design by using agent1.
The testing team at Contoso identifies that the customer portal uses inconsistent UI styles, which leads to customer confusion and branding issues. The UI inconsistencies stem from variations in the folder structure.
Agent Logs
You have the following logs for the multi-agent workflow used in repo2.
Requirements
Planned Changes
Contoso plans to have all agents and developers in repo1use the Microsoft Learn MCP to ensure that reviews are validated by using the appropriate documentation. This must be implemented centrally.
Contoso plans to leverage AI-powered coding agents to implement new portal features and pages.
Technical Requirements
App1 must be upgraded to .NET 10. A previous upgrade attempt was started by using the Copilot modernization agent, but the attempt was never finalized.
You plan to retry the upgrade. You must first analyze App1 by using AI, and then generate a report that contains breaking changes and deprecated patterns before retrying the upgrade.
All AI-generated code for UI styling must adhere to a predefined folder structure.
The architects at Contoso need help building implementation plans for repo1. The company wants to implement a new agent named agent2 to analyze the code base and the code requirements, and then respond with a detailed plan. The agent must NOT be able to edit files or run local commands.
The developers must be able to delegate work to the Copilot coding agent by assigning issues to the agent.
While upgrading App1, the agent identifies 47 issues, including a security vulnerability, and 46 API incompatibilities across different projects.
Which two actions are unsafe to delegate to the agent and require human involvement? Each correct answer presents a complete solution.
NOTE: Each correct selection is worth one point.
Answer: D,E
Explanation:
The two actions that are unsafe to delegate to the agent and require human involvement are Approve all Git commits and Validate the assessment.md file for accuracy.
Validate the assessment.md file for accuracy: The agent generated this file based on its own scan. A human expert must cross-check its findings to catch false positives, false negatives, and misclassified security vulnerabilities.
Approve all Git commits: Automated agents can introduce unintended code changes, logic flaws, or broken builds. A human must review and approve commits to maintain code quality and prevent security regressions.
Scenario:
Contoso has a second repository named repo2 that contains a legacy .NET application named App1 built by using .NET 6. repo2 has a multi-agent workflow for modernization tasks.
Technical Requirements
App1 must be upgraded to .NET 10. A previous upgrade attempt was started by using the Copilot modernization agent, but the attempt was never finalized.
You plan to retry the upgrade. You must first analyze App1 by using AI, and then generate a report that contains breaking changes and deprecated patterns before retrying the upgrade.
Reference:
https://learn.microsoft.com/en-us/dotnet/core/porting/github-copilot-app-modernization/overview
NEW QUESTION # 77
You need to resolve the scoping issue associated to agent1.
What should you do?
Answer: D
Explanation:
A fine-grained PAT restricted to product-api provides an enforceable repository-level authorization boundary for agent1. GitHub fine-grained personal access tokens can be limited to selected repositories and assigned only the repository permissions required by the workload. Consequently, even if agent1 attempts to access billing-service or infra-terraform, the credential does not authorize access to those repositories. GitHub specifically recommends fine-grained PATs when repository access must be restricted to particular repositories.
This directly aligns with the GH-600 objective to configure an agent's scope to a specific repository and define execution boundaries through repository context and permissions. Microsoft Learn defines execution context as including the repository an agent can access and emphasizes that repository scope is the first boundary limiting agent behavior.
Option A provides behavioral guidance but is not a security authorization boundary. Option B controls the permissions available to the workflow token but does not, by itself, establish the required cross-repository credential restriction. Option D only prevents certain push operations; it does not stop agent1 from reading or otherwise accessing the other repositories.
Study Guide Reference Topics: Implement Tool Use and Environment Interaction → execution context and boundaries; repository-specific agent scope; tool permissions; least-privilege authentication.
NEW QUESTION # 78
After App1 is upgraded to meet the technical requirements, you need to validate the output.
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:
NEW QUESTION # 79
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