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| Section | Weight | Objectives |
|---|---|---|
| Test, deploy, and manage agents | 20โ25% | - Test and validate agent performance
|
| Plan and configure agent solutions | 30โ35% | - Configure agent foundations
|
| Build and extend agents in Copilot Studio | 40โ45% | - Implement advanced capabilities
|
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NEW QUESTION # 122
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 plan how Fabrikam Inc. will reuse shared components across multiple agents while limiting who can change the shared components.
Which approach should you use for each requirement? To answer, move the appropriate components to the correct requirements. You may use each component 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: Share the component collection with teammates while controlling edit access.
Prevent shared assets from being modified by most builders.
The best action to take is to share the component collection with teammates while controlling edit access.
In Microsoft Copilot Studio, component collections are designed specifically to centralize and reuse assets (like topics, knowledge sources, and actions) across multiple separate agents.
When configuring a component collection, administrators or collection owners can utilize built-in sharing permissions to explicitly assign roles to individual makers or groups:
Box 2: Create a component collection and move shared components into it Reuse the same set of components across multiple agents without copying.
The best action to take is to create a component collection and move shared components into it.
In Microsoft Copilot Studio, Component Collections provide a central container to package and share topics, knowledge bases, actions, and entities across multiple agents without duplicating the assets. Once a collection is created, you can establish governance controls (such as managing it within a managed solution) so that makers on other agents can utilize the shared resources but cannot modify them.
Box 3: Restrict component collection to the primary agent
Limits a shared set of components so it can be used only be its intended primary agent.
The best action to take is to restrict component collection to the primary agent. In Microsoft Copilot Studio, you can restrict a shared set of components so that it can be used only by its intended agent. This feature helps teams modularize large or sensitive agents and prevents unauthorized reuse.
Reference:
https://learn.microsoft.com/en-us/microsoft-copilot-studio/authoring-export-import-copilot-components
NEW QUESTION # 123
You deploy an agent in Microsoft Copilot Studio that triggers a cloud flow to update customer records in Microsoft Dataverse.
You observe the following after deploying the agent:
Several runs fail due to a temporary authentication issue.
The flow continues to trigger and generate additional failed runs.
You must:
Answer:
Explanation:
Explanation:
Stop further failures # Turn off the flow; Reprocess the corrected execution # Resubmit the failed run; Verify recent success # Review Activity history.
Comprehensive and Detailed Explanation From Microsoft AB-620 Study Guide: Turning off the flow is the safest immediate control when a temporary authentication failure is causing repeated triggered runs. It prevents additional failures and noise while the connection is repaired without deleting the flow or altering its trigger logic. After credentials or connection references are corrected, resubmitting the failed run reprocesses the original input and is more precise than creating an unrelated new execution. The Activity history then provides run-level evidence that recent executions succeeded, including status, timestamps, action outputs, and error details. Analytics summaries are useful for trends but are less appropriate for immediate confirmation of a specific recovery. Cancelling only the latest run would not stop future triggers, and recreating or republishing the flow is unnecessary when the underlying design is sound. The flow should be re- enabled only after the connection is validated. Administrators should document the incident and consider alerting, bounded retries, and explicit error handling so a transient dependency does not generate an uncontrolled series of failures again. Study Guide alignment: Plan and configure agent solutions > Create and monitor agent flows in Copilot Studio > Monitor agent flows.
NEW QUESTION # 124
An agent in Copilot Studio already exists in a development environment.
You need to prepare the agent so it can be moved to a production environment using the supported solution-based approach.
You need to create an exportable package that contains the existing agent.
Which two actions should you perform? Each correct answer presents part of the solution.
NOTE: Each correct selection is worth one point.
Answer: A,E
Explanation:
Agents authored in Copilot Studio land in the Common Data Service Default Solution, which can't be exported. The supported ALM path is to create your own (unmanaged) solution in the dev environment and add the existing agent to it, along with its dependencies (topics, custom connectors, flows, environment variables, connection references).
Exporting produces the deployable package (.zip). Dev environments hold the unmanaged source solution, and the export step is where you generate the package - choosing managed output at export time when the target is production.
Reference:
https://learn.microsoft.com/en-us/microsoft-copilot-studio/authoring-solutions-import-export
NEW QUESTION # 125
Which two actions should you perform before making the agent available on both channels? Each correct answer presents part of the solution. NOTE: Each correct selection is worth one point.
Answer: B,D
Explanation:
* A. Configure prompt modifications at the system level. Centralized instructions enforce the required tone, disclaimers, response boundaries, and refusal behavior consistently across generative responses.
Microsoft documents that prompt modification can define an agent's personality, response format, permitted subjects, and behavior when an answer is unavailable. This avoids inconsistent manual changes across individual topics. Microsoft: Prompt modification
* D. Configure Power Platform DLP policies. DLP policies govern which connectors, knowledge sources, HTTP endpoints, and channels the agent may use. They should be configured and validated before publication because a policy violation can prevent the agent from being published. DLP also protects against unauthorized data movement between business and non-business connectors.
Microsoft: Data policies for agents
Why the others are incorrect: B creates duplicated, inconsistent disclaimers. C incorrectly treats moderation as a web-channel setting; moderation is configured for generative behavior rather than enforced only by embedding settings. E applies safeguards after publication and assumes filters must be configured separately for every channel, which would not provide the required centralized governance.
NEW QUESTION # 126
A company is configuring generative answers for an agent in Copilot Studio agent.
The agent must use Azure AI Search to retrieve enterprise content, and all responses must be generated by a Microsoft Foundry model.
The agent sometimes generates answers that are not grounded in Azure AI Search content. The company requires that the agent only generate responses when relevant indexed content is retrieved.
You need to configure the agent so that its generative answer behavior meets the organization's requirements.
What should you do?
Answer: B
Explanation:
To prevent your agent from generating ungrounded answers and restrict it to responding only when relevant content is found, you should configure the agent to require grounding for generative answers and use Azure AI Search as the retrieval source.
Enforces Grounding: Enabling the option to require grounding or disabling the ability for the AI to use its own general knowledge ensures that the Microsoft Foundry model will strictly use the data pulled from your indexed enterprise content.
Prevents Hallucinations: If Azure AI Search does not retrieve relevant document chunks for a specific user query, the agent will gracefully refuse to answer rather than fabricating a response based on pretrained model weights.
Reference:
https://techcommunity.microsoft.com/blog/azure-ai-foundry-blog/turn-enterprise-knowledge-into-answers-with-copilot-studio-and-azure-ai-search/4493118
NEW QUESTION # 127
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