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| Section | Objectives |
|---|---|
| Governance, Security, and Compliance | - Data protection and responsible AI practices - Environment management in Power Platform - Managing access control and authentication |
| Integrate External Systems and Data Sources | - Integrating Dataverse and Power Platform components - Connecting Azure services and APIs - Using Power Automate for workflow orchestration |
| Deploy, Monitor, and Optimize AI Agents | - Iterative improvement and lifecycle management - Monitoring performance and analytics - Publishing and deploying copilots |
| Plan and Design Copilot Studio AI Agents | - Selecting Copilot Studio capabilities and architecture approach - Requirements analysis for AI agent solutions - Designing conversation flows and agent behavior |
| Build and Configure AI Agents in Copilot Studio | - Using generative AI and prompt engineering in Copilot Studio - Creating and configuring copilots and topics - Configuring actions, plugins, and connectors |
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NEW QUESTION # 82
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 # 83
A team is developing an agent in Copilot Studio and wants to evaluate its behavior before expanding access.
The team needs a repeatable, consistent method to test the agent by using predefined interactions.
You need to ensure that agent responses can be evaluated consistently across multiple test runs.
What should you do?
Answer: D
Explanation:
A test set provides the controlled evaluation method required in this scenario. It consists of prepared prompts or questions together with defined expectations, such as an expected response or evaluation criterion. Copilot Studio can run the same test cases repeatedly, capture the agent's generated responses, and compare the results against the established baseline. Because the inputs and expectations remain fixed, changes between runs can be attributed more reliably to modifications in the agent's instructions, topics, tools, or knowledge configuration.
A qualitative review may be useful during exploratory testing, but it depends heavily on individual judgment and does not provide the same repeatability. Previous production sessions also contain uncontrolled user inputs and changing conversational context, so they are unsuitable as a standardized baseline. Publishing the agent to additional channels expands exposure rather than validating response quality.
Telemetry and analytics are valuable after deployment for monitoring fallback frequency, topic usage, engagement, containment, and other operational behavior. However, analytics alone do not execute a fixed collection of interactions or compare each response with a predefined expectation. They therefore complement formal evaluation rather than replace it.
The appropriate action is to define and repeatedly execute a test set containing prompts and expected outcomes. Relevant study-guide areas are Evaluate agent responses , Create and run test sets , and Analyze evaluation results . See Agent evaluation overview .
NEW QUESTION # 84
You need to configure the agent in Copilot Studio to meet Blue Vender ' s Responsible AI and data protection requirements.
Which three actions should you perform in sequence? To answer, move the appropriate actions from the list of actions to the answer area and arrange them in the correct order.
Answer:
Explanation:
Explanation:
NEW QUESTION # 85
A company uses an agent in Copilot Studio that produces structured responses using a reusable instruction template. The responses follow the required tone and format. During a compliance review, the team discovers that the responses were generated using a model that is not on the approved list.
The company requires that the reusable instruction template continues to be used and the model used for prompt-driven responses meets governance requirements.
The solution must ensure that prompt-driven responses are generated using an approved model.
You need to configure the solution that meets the requirements.
Which two actions should you perform? Each correct answer presents part of the solution.
NOTE: Each correct selection is worth one point.
Answer: E,F
Explanation:
To fix the compliance issue in Microsoft Copilot Studio, you must select an approved model from the catalog for generation and ensure the correct template is applied. The two necessary configuration steps are:
[F] Select an approved model from the model catalog in the configuration used for prompt-driven response generation.
[C] Ensure the reusable instruction template is the one applied to the agent that generates the structured response.
Configuration Steps
Model Selection: Open your agent settings in Microsoft Copilot Studio and choose a compliant, approved foundation model from the catalog for your prompt responses.
Template Assignment: Verify and re-apply the correct reusable instruction template directly to the specific agent responsible for generating the structured output.
Reference:
https://techcommunity.microsoft.com/blog/microsoft365insiderblog/choosing-the-right-ai-model-in-microsoft-365-flexibility-control-and-confidence/4530762
NEW QUESTION # 86
A company must enable an agent in Copilot Studio to execute operations exposed by an external MCP server.
The MCP server publishes callable tools and requires authentication.
The agent must be able to invoke MCP tools during conversations.
You need to configure MCP tools so the agent can execute MCP tool calls.
What should you do?
Answer: B
Explanation:
To best configure the Model Context Protocol (MCP) tools so the agent can successfully invoke operations, you should configure OAuth 2.0 authentication.
Reference:
https://learn.microsoft.com/en-us/microsoft-copilot-studio/mcp-add-existing-server-to-agent
NEW QUESTION # 87
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