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| Section | Objectives |
|---|---|
| Topic 1: Deploy, Monitor, and Optimize AI Agents | - Iterative improvement and lifecycle management - Publishing and deploying copilots - Monitoring performance and analytics |
| Topic 2: Integrate External Systems and Data Sources | - Connecting Azure services and APIs - Using Power Automate for workflow orchestration - Integrating Dataverse and Power Platform components |
| Topic 3: Build and Configure AI Agents in Copilot Studio | - Creating and configuring copilots and topics - Configuring actions, plugins, and connectors - Using generative AI and prompt engineering in Copilot Studio |
| Topic 4: Plan and Design Copilot Studio AI Agents | - Requirements analysis for AI agent solutions - Selecting Copilot Studio capabilities and architecture approach - Designing conversation flows and agent behavior |
| Topic 5: Governance, Security, and Compliance | - Data protection and responsible AI practices - Environment management in Power Platform - Managing access control and authentication |
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.
You need to enable collaboration requirements for Operations Concierge.
Which two actions should you perform? Each correct answer presents part of the solution.
NOTE: Each correct selection is worth one point.
Correct Answer: D,E 🗳️
Explanation: Only visible for itPass4sure members. You can sign-up / login (it's free).
A company requires an agent in Copilot Studio to answer questions using content stored in a third-party knowledge base system and reuse that content for knowledge grounding.
The agent must ground answers using indexed enterprise knowledge from a non-Microsoft system.
You need to choose the correct integration approach.
What should you use?
Correct Answer: D 🗳️
Explanation: Only visible for itPass4sure members. You can sign-up / login (it's free).
A company uses multiple Copilot Studio agents that perform specialized tasks.
The company needs to enable one agent to directly delegate and invoke another agent within Copilot Studio by using a standard Copilot Studio interface.
You need to configure collaboration among agents by using Copilot Studio.
What should you do?
Correct Answer: C 🗳️
Explanation: Only visible for itPass4sure members. You can sign-up / login (it's free).
Drag and Drop Question
A company is preparing an agent flow so that it can be invoked by an agent during conversations.
The agent flow must meet the following requirements:
- The agent must be able to trigger the flow.
- The agent flow must be verified.
You need to prepare an agent flow so that it can be used by the agent.
In which order should you perform the actions to prepare the agent flow? To answer, move all actions from the list of actions to the answer area and arrange them in the correct order.
Correct Answer:

Explanation:
Step 1: Create a new agent flow artifact in the environment
You must first initialize the flow container within your Copilot Studio workspace before adding any logic.
Step 2: Configure the invocation trigger that allows the agent to call the agent flow You must set up the specialized trigger first (i.e., "When an agent calls the flow"), because this defines the required input variables that the downstream behavioral actions will rely on.
Step 3: Configure the actions that implement the required behavior
With the trigger and input variables established, you build the functional core of the flow (e.g., pulling data, sending approvals) and finalize it with the "Respond to the agent" action.
Step 4: Validate the agent flow behavior with representative test runs
The workflow needs to be tested and verified directly within the flow authoring interface using test data to check for errors before exposing it to the orchestrator.
Step 5: Make the agent flow available for agent usage
Once verified, you publish the flow and add it to your agent as an active tool so the conversational orchestrator can dynamically call it during live interactions.
Reference:
https://learn.microsoft.com/en-us/microsoft-copilot-studio/flow-agent
Drag and Drop Question
A company plans to use Copilot connectors to ground answers from a third-party system for an agent in Copilot Studio.
To meet the business needs, responsibilities for configuring and using Copilot connectors must be separated, based on the following requirements:
- For tenant administration, the connector must be available at the
tenant level.
- For agent runtime behavior, answers must be grounded from authorized
sources.
- For builder configuration, you must add the connector to the agent.
You need to determine how Copilot connector set-up responsibilities are handled across tenant, runtime, and builder stages.
What should you configure for each requirement? To answer, move the appropriate configuration 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.
Correct Answer:

Explanation:
Box 1: Configure the Copilot connector in Microsoft 365 Admin Center
Microsoft 365 Copilot connectors (Graph connectors) must be enabled, authenticated, and configured centrally at the tenant level via the Microsoft 365 Admin Center (Copilot > Connectors). This establishes organizational data availability, schema mapping, and access permissions across the whole tenant.
Box 2: Call the connector knowledge source.
When an end user interacts with the agent at runtime, the execution engine dynamically queries and calls the connector knowledge source to retrieve authorized context and ground the generated response.
Box 3: Add the Copilot connector as a knowledge source.
Maker/builder actions in Copilot Studio involve authoring the agent by choosing to add the Copilot connector as a knowledge source so the agent knows where to retrieve enterprise information from.
Reference:
https://learn.microsoft.com/en-us/microsoft-365/copilot/connectors/overview
https://learn.microsoft.com/en-us/microsoft-365/copilot/connectors/manage-connector
https://learn.microsoft.com/en-us/microsoft-365/copilot/extensibility/agent-builder-add-knowledge
https://learn.microsoft.com/en-us/microsoft-copilot-studio/copilot-connectors-in-copilot-studio
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