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| Section | Weight | Objectives |
|---|---|---|
| Build and extend agents in Copilot Studio | 40โ45% | - Integrate with services and systems
|
| Test, deploy, and manage agents | 20โ25% | - Test and validate agent performance
|
| Plan and configure agent solutions | 30โ35% | - Plan an agent solution
|
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NEW QUESTION # 91
A team is preparing to assess an agent in Copilot Studio before expanding access to additional users.
The team requires an evaluation that provides controlled, repeatable, and consistently measured test runs.
The evaluation must:
Be triggered directly by the team to control when testing occurs.
Determine success based on clearly established acceptance criteria.
Rely on a predefined set of inputs that ensures consistency across repeated runs.
Answer:
Explanation:
Explanation:
Controlled trigger # Execute the evaluation on demand; Acceptance criteria # Compare responses against defined expectations; Consistent repeated inputs # Use a curated prompt list as the interaction source.
Comprehensive and Detailed Explanation From Microsoft AB-620 Study Guide: An on-demand evaluation gives the team explicit control over when the test is executed, which is appropriate before widening access or immediately after a meaningful change. Defined expectations convert the business acceptance criteria into measurable pass/fail or score-based judgments instead of relying on informal review.
A curated prompt list supplies the same input cases for each run, eliminating variation that would arise from live user conversations. Scheduling an evaluation is useful for continuous monitoring but would not meet the stated requirement that the team trigger it directly. Live conversations are valuable for discovering new cases, yet they are not a stable regression set because their content and distribution change over time. The curated set should cover knowledge retrieval, tool use, safety boundaries, authentication-dependent behavior, and common failure paths. Expected answers and expected resources should be specific enough to identify regressions without penalizing valid paraphrases. Once the evaluation is run, the team should inspect both aggregate scores and individual activity details before deciding whether the agent is ready for broader use.
Study Guide alignment: Test and manage agents > Evaluate agent performance > Create a test set; Choose an evaluation method.
NEW QUESTION # 92
Hotspot Question
You run multiple evaluation tests for an agent in Copilot Studio before expanding user access.
You observe the following about the evaluation results:
- Each evaluation case is reported as meeting or missing the expected
response.
- Some evaluation cases fail repeatedly across several runs.
- Each run displays the expected response and the response generated by the agent.
You need to interpret what the evaluation results reveal.
What should you conclude based on each interpretation? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
Box 1: Pass or fail status.
Based on the evaluation results, you can conclude the Pass or fail status.
Direct mapping: Measuring whether a case "meets" or "misses" an expectation is the definition of a binary pass/fail test.
Insufficient data for production: You cannot fully determine Production readiness because readiness requires broader metrics like latency, security, and user acceptance testing.
No diagnostic data: You cannot determine the Failure configuration because a simple "miss" label does not explain why the system failed or how it is misconfigured.
Box 2: Consistent outcomes
Based on the evaluation results, you can conclude that these are Consistent outcomes.
Definition of Consistency: Because the specific evaluation cases fail repeatedly across several runs, the behavior is predictable and stable, not random.
Box 3: Expected and generated responses:
The correct conclusion from these evaluation results is Expected and generated responses.
Expected and generated responses: The evaluation results explicitly show a side-by-side comparison between what the agent was supposed to say (expected response) and what it actually said (generated response). This allows you to conclude exactly how well the agent's outputs align with your test cases.
Reference:
https://learn.microsoft.com/en-us/microsoft-copilot-studio/analytics-agent-evaluation-results
NEW QUESTION # 93
A company wants to use content from a non-Microsoft enterprise knowledge base to ground agent responses.
To meet the business needs, the knowledge source must meet the following requirements:
Support grounding from indexed data.
Use existing access controls from the source system.
Support read-only operations.
You need to determine the correct behavior to meet the requirements.
Which behavior meets each requirement? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
* Support grounding from indexed data # Retrieve indexed content
* Use existing access controls from the source system # Respect existing permissions
* Support read-only operations # Prevent transactional updates
Microsoft 365 Copilot connectors index non-Microsoft enterprise content into Microsoft Graph for semantic grounding. They preserve source-level access controls so users receive only content they are authorized to access. Because the connector is configured as a knowledge source, its purpose is retrieval-not executing transactional updates. Microsoft Learn: Copilot connectors as knowledge sources
NEW QUESTION # 94
A team is standardizing ALM for agents in Copilot Studio.
The team requires a custom solution that includes agents. The solution must support ALM scenarios, such as managing and transporting agent assets across environments and pipeline deployments.
You need to create an ALM-ready custom solution in Copilot Studio.
What should you do?
Answer: B
Explanation:
Comprehensive and Detailed Explanation From Microsoft AB-620 Study Guide: The required first action is to create a custom solution from the Solutions area. A solution is the ALM carrier that groups the agent with its related components and enables controlled export, import, pipeline deployment, dependency management, and versioning across environments. Exporting an agent directly is not the supported replacement for solution-based ALM. A channel configuration determines where users can interact with a published agent; it is not a container for development assets. Exporting a managed solution and importing it into production is a later release step and cannot occur until the custom solution exists and contains the agent and its dependencies. After creation, the team should add the existing agent, associated flows, connection references, environment-variable definitions, prompts, and any other required components. Development normally occurs in an unmanaged solution, while a managed build is deployed to Test and Prod. This separation supports repeatable promotion, protects downstream environments from unmanaged edits, and provides a clearer rollback and support boundary. Study Guide alignment: Test and manage agents > Implement application lifecycle management for agents in Copilot Studio > Create a solution.
NEW QUESTION # 95
Case Study 2 - Fabrikam Inc.
Background
Fabrikam Inc. is a Canada-based manufacturer with a growing service organization that supports field technicians and internal operations teams. Fabrikam Inc. plans to launch a new internal agent solution named Operations Concierge to reduce time spent searching policy content, retrieving operational metrics, and executing routine transactions.
The agent will be used by three groups:
- Service coordinators who triage incoming service requests
- Field technicians who need guided procedures and parts availability
- Operations managers who monitor KPIs and exceptions
The agent solution must work in real-world operational conditions. Users often ask questions mid- call with a customer or while coordinating parts shipments. The agents require quick, reliable outcomes. As a result, Fabrikam Inc. requires the solution to:
- Provide grounded answers with traceability when it provides guidance.
- Retrieve real-time metrics when users ask for operational status.
- Execute authenticated updates when users initiate a flow (such as creating a parts request).
Fabrikam Inc. also expects the solution to be maintained by multiple makers and developers across the year. The company has experienced duplicated logic and inconsistent behavior across different agents. This project emphasizes reuse, governance, and maintainability across teams.
Current environment
Fabrikam Inc. runs three Microsoft Power Platform environments for agent development and release: Dev, Test, and Prod.
The team plans to build the agent and validate it in Dev and Test, then promote to Prod by using a controlled release process that supports repeatable deployments.
Fabrikam Inc. already has two assets the team wants to reuse:
- A partially completed Copilot Studio agent named Service Desk Agent, used by IT to create internal tickets and route requests
- A Microsoft Foundry agent created by a central AI team that performs specialized summarization and classification for long-form text (for example, summarizing call transcripts into an incident narrative) Fabrikam Inc. also has operational and knowledge data sources:
- A curated policy library (internal SOPs, service warranty rules, escalation criteria, and standard operating procedures)
- A set of indexed documents and procedures in an Azure AI Search service that supports vector search for the policy library
- A Microsoft Fabric workspace that includes a semantic model used by operations leadership for reporting Business requirements Fabrikam Inc. requires Operations Concierge to meet the following business requirements:
- Traceability requirement: When the agent provides policy guidance or procedural recommendations, users must be able to see where the answer came from.
- Metrics requirement: When users ask about service performance (backlog, SLA risk, parts shortages, dispatch delays), the solution must return up-to-date metrics in a structured format that operations managers can use in weekly reviews.
- Transaction requirement: The solution must support authenticated updates initiated during conversations, including creating a parts request and updating a service case status.
In addition, Fabrikam Inc. wants to avoid duplicating common assets across agents:
- The team must reuse the same set of escalation topics, MCP tool definitions, and a standard safety disclaimer across three different agents.
- Only the platform engineering group as allowed to edit shared assets. However, all agent authors must be able to use them.
Technical requirements
The Fabrikam Inc. solution architecture uses a multi-agent approach so that specialist responsibilities are isolated and can evolve independently.
The Operations Concierge (primary agent) must coordinate the following specialist capabilities:
- Policy and procedure Q&A: Use an enterprise knowledge source that supports indexed retrieval across the curated policy library and service procedures.
- Operational metrics: Delegate metric queries to a Fabric Data Agent that reads governed business data through the Fabric semantic model.
- Authenticated updates: Use tools exposed by an existing internal Model Context Protocol (MCP) server that provides transactional operations for the service organization.
- Specialized processing: Delegate summarization and classification requests to an existing Microsoft Foundry agent.
Fabrikam Inc. will onboard two MCP servers as tools:
- PartsOps MCP server: exposes tools for parts availability checks and parts request creation.
The server requires per-user authentication because actions must be traceable to the requesting user.
- WarrantyRules MCP server: exposes a read-only tool for validating warranty coverage. The server uses an API key shared by the agent team.
Fabrikam Inc. has also defined a collaboration requirement with the existing Service Desk Agent:
- The primary agent must delegate IT-specific requests to the existing Service Desk Agent rather than reimplement ticket creation logic.
Finally, Fabrikarn Inc. plans to support a partner integration:
- For shipment tracking inquiries, Fabrikam Inc. will delegate to a partner-provided agent that is only available through a standardized agent-to-agent endpoint.
Issues and constraints
During early testing, Fabrikam Inc. found three recurring problems:
- Makers are copying and modifying the same components across agents, resulting in inconsistent disclaimers and duplicated tools.
- Users can obtain a correct answer, but the response is not consistently traceable to a source when the agent uses knowledge.
- The primary agent can route some requests, but specialist capabilities are not consistently delegated (for example, some metric questions are answered generatively instead of being routed to the Fabric Data Agent).
You are part of the engineering team responsible for correcting the design and configuration to meet the preceding requirements and constraints.
Drag and Drop Question
You need to connect Operations Concierge to Fabrikam Inc.'s Azure AI Search knowledge index while complying with security requirements.
Which configuration should you use for each requirement? To answer, move the appropriate configurations to the correct requirements. You may use each configuration once, more than once, or not at all. You may need to move the split bar between panes or scroll to view content.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
Box 1: Select the service principal as the authentication type
Ensure the Azure AI Search connection complies with the governance requirement for authenticated access.
Scenario:
A set of indexed documents and procedures in an Azure AI Search service that supports vector search for the policy library Box 2: Provide the Azure Search Endpoint URL in the connection details.
Ensure policy and procedure Q&A uses the required curated, indexed enterprise knowledge source.
Box 3: Provide the Azure Search Endpoint URL in the connection details.
Ensure the connection targets the Azure AI Search service instance that stores the indexed policy documents.
The best action to take is to Provide the Azure Search Endpoint URL in the connection details.
When connecting a Copilot agent to an external knowledge source like Azure AI Search, establishing the connection requires identifying the specific service host. Providing the Azure AI Search Endpoint URL ensures that the underlying connection infrastructure explicitly targets and authenticates against your specific Azure AI Search service instance. Once this service-level connection is validated, you are prompted in the next step to select or enter the specific index containing your documents.
Reference:
https://learn.microsoft.com/en-us/microsoft-copilot-studio/knowledge-azure-ai-search
NEW QUESTION # 96
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