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| Section | Weight | Objectives |
|---|---|---|
| Test, deploy, and monitor agentic AI systems | 20% | - Validate agent performance and safety
|
| Integrate tools, data, and services | 25% | - Incorporate external tools and APIs
|
| Design agentic AI solutions | 25% | - Design agent architecture
|
| Implement agents and multi-agent systems | 30% | - Orchestrate multi-agent collaboration
|
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NEW QUESTION # 46
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: A,E
Explanation:
The intended distinction is between delegating analytical work and allowing the agent to provide the final approval of its own work. Approving all Git commits would remove independent review of changes that include security-sensitive remediation and compatibility modifications across multiple projects.
Human validation of assessment.md is similarly important because the assessment determines the scope and direction of the upgrade. Incorrectly classified dependencies, missed projects, or an incomplete vulnerability analysis can propagate into the implementation plan. Microsoft's guidance explicitly recommends reviewing the assessment for missing projects, problematic dependencies, and application-specific concerns before proceeding.
Generating the assessment and checking whether a task file exists are appropriate automated activities. An agent can also inspect the plan's dependency relationships and flag potential ordering problems. Such assistance does not transfer final accountability for accepting the plan.
The wording should not be interpreted as prohibiting automated assessment validation. Agents can run valuable consistency checks; the unsafe delegation is treating those checks as sufficient independent approval of their own conclusions.
Study-guide topics: human oversight, independent validation, and approval boundaries. Reference: Microsoft Learn-Best practices for GitHub Copilot upgrade.
NEW QUESTION # 47
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.
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.
Answer:
Explanation:
Topic 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 repo1 that 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 repo1 use 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.
NEW QUESTION # 48
You use a GitHub Actions workflow to orchestrate a multi-agent draft-review process for pull requests. The workflow uploads a single combined review-package artifact at the end of each run.
You discover that the review-package artifact is occasionally missing from the workflow run history, and you suspect that a user deleted it.
You need to identify which user manually deleted a workflow run artifact and when the deletion occurred.
What should you use?
Answer: A
Explanation:
The artifact.destroy audit log event records manual deletion of workflow artifacts. It provides the event data needed to identify the actor responsible for the deletion and the time at which it occurred.
Pull-request comments and descriptions can describe review activity, but they are not authoritative evidence of artifact deletion. Merge commits only establish repository-history changes and do not record deletion of workflow artifacts. A checks-related log event is unrelated to artifact lifecycle management.
Audit records should be correlated with the affected repository, workflow run, artifact name, and timestamp. This produces a traceable explanation of why evidence from a particular run is no longer present. Where long-term retention is required, the organization should combine artifact policies with external audit-log retention or streaming.
Study-guide topics: artifact accountability, audit events, evidence retention, and workflow investigation.
NEW QUESTION # 49
You want the Copilot coding agent to scan a large codebase and propose a full, human- reviewable step-by-step plan before writing any code. What should you do first?
Answer: C
Explanation:
Plan mode lets the agent operate in a read-only analysis state, producing a structured Markdown plan of intended changes. This allows you to catch architectural issues before the agent starts editing files.
NEW QUESTION # 50
You have a GitHub repository that uses the GitHub Copilot coding agent to resolve issues in an ephemeral GitHub Actions environment.
Builds fail unless an environment variable named NPM_TOKEN is available, because the repository depends on a private package registry.
A workflow named .github/workflows/copilot-setup-steps.yml was added but was merged into a non-default branch and does NOT run when new agent sessions start.
You need to ensure that for every new agent session, the setup steps run, and the private registry token is available as NPM_TOKEN, without hardcoding secrets in the repository.
What should you do?
Answer: C
Explanation:
The Copilot setup workflow must be present on the repository's default branch to be used for new coding-agent sessions. Moving .github/workflows/copilot-setup-steps.yml there ensures the setup procedure is discoverable for every newly created agent environment.
The package-registry credential should be stored as an environment secret in the Copilot environment and exposed using the required variable name, NPM_TOKEN. This permits package installation without committing the token into workflow YAML, instructions, source code, or pull requests.
Disabling network controls does not resolve missing credentials and expands risk unnecessarily. Repository instructions can describe setup expectations but cannot safely substitute for an injected runtime secret. Adding the raw token to YAML permanently exposes it to repository history and anyone with repository access.
Study-guide topics: ephemeral environments, setup workflows, environment secrets, and secure dependency access.
NEW QUESTION # 51
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