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| Section | Weight | Objectives |
|---|---|---|
| Test and Manage Agents | 20-25% | - Monitor and manage agent solutions
|
| Plan and Configure Agent Solutions | 30-35% | - Plan agent solutions
|
| Integrate and Extend Agents in Copilot Studio | 40-45% | - Integrate agents with enterprise systems
|
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NEW QUESTION # 131
You need to plan how Fabrikam Inc. will reuse shared components across multiple agents while limiting who can change the shared components in Copilot Studio Lite.
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:
Prevent most builders from modifying shared assets # Share the component collection while controlling edit access; Reuse components without copying # Create a component collection and move the shared components into it; Limit use to the intended primary agent # Restrict the component collection to the primary agent.
Comprehensive and Detailed Explanation From Microsoft AB-620 Study Guide: A component collection is the correct reusable unit for the escalation topics, MCP definitions, and safety disclaimer. Moving those assets into one collection creates a maintained source that multiple agents can consume without copying and later diverging. Sharing the collection with teammates while controlling edit access separates use permission from modification permission, allowing agent authors to reference the assets while reserving changes for platform engineering. If a sensitive or tightly coupled collection must be usable only by one designated primary agent, the collection can be restricted accordingly. Exporting the primary agent and copying its components would recreate the duplication problem that Fabrikam is trying to eliminate, while restricting every collection to the primary agent would prevent the required cross-agent reuse. The collection should be versioned and tested after changes because a shared update can affect several consumers. Ownership, review, and release responsibilities should also be documented so that reuse does not become an uncontrolled dependency. This design provides consistency, centralized governance, and a smaller maintenance surface across the three agents. Study Guide alignment: Plan and configure agent solutions > Plan an agent solution > Plan reusable agent components.
NEW QUESTION # 132
Hotspot Question
You run multiple evaluation tests for an agent in Copilot Studio before expanding user access.
The tests provide the following 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 provide a conclusion based on the evaluation results.
Which conclusions should you make? 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 testing criteria in Microsoft Copilot Studio, the outcome described directly measures the Pass or fail status of your tests.
Pass or fail status: This is the primary conclusion. Microsoft Copilot Studio Agent Evaluation uses structured methods (such as Exact Match, Similarity, or Compare Meaning) to objectively check if your agent met or missed the expected responses in your test set.
Box 2: Consistent outcomes
The conclusion to make from this is Consistent outcomes.
When evaluation test cases fail repeatedly across several runs, it indicates a stable, reproducible issue with the agent's behavior rather than random variability. Because the agent produces the same failure under the same test conditions, you have consistent outcomes.
Box 3: Expected and generated response
From the multiple evaluation tests in Microsoft Copilot Studio, the primary conclusion you can make is regarding the expected and generated responses.
This specific test output allows you to directly assess the alignment between what the AI was anticipated to say (the expected response) and what it actually produced (the generated response). By contrasting these, you can analyze semantic similarity, intent, and overall quality.
Reference:
https://www.microsoft.com/en-us/microsoft-copilot/blog/copilot-studio/how-to-evaluate-ai-agents/
NEW QUESTION # 133
Case Study 1 - Blue Yonder Airlines
Background
Blue Yonder Airlines is a global carrier headquartered in Los Angeles, California, operating domestic and international flights. The company serves millions of passengers annually through its website, mobile app, and call centers. To improve customer service efficiency and reduce call center volume, Blue Yonder is deploying an AI agent in Microsoft Copilot Studio.
The agent will handle customer inquiries across multiple channels - web chat, mobile app, and Microsoft Teams (for internal support staff). It will answer questions, retrieve data from enterprise systems, and escalate to human agents when needed.
The project is led by a cross-function team:
- Product manager: Defines requirements and success metrics.
- Lead agent author: Designs topics, intents, and generative behavior.
- Flow designers: Build agent flows and integrations.
- IT/security and compliance: Oversees identity, data protection, and Responsible AI (RAI) compliance.
Current environment
Channels
Public website: Embedded web chat
Mobile app: In-app chatbot
Microsoft Teams: Internal support agent access
Identity and access
Customers: Anonymous access for general inquiries (e.g., flight status, baggage policy).
Authentication is required for personal data access (e.g., bookings, loyalty points).
Internal staff: Authenticate via Microsoft Entra ID.
Data sources
Reservation and Ticketing System (internal): REST API, no prebuilt connector with custom enterprise database.
Flight Status and Weather APIs (external): REST APIs with API keys.
Customer Support Knowledge Base: SharePoint library with PDFs and policy documents.
Loyalty Program Data: Stored in Dynamics 365 and Dataverse.
Travel Advisory Content: Uses REST API with partner services.
Integration mechanisms
Custom connectors must be used for internal APIs that lack prebuilt connectors.
HTTP request nodes may be used for lightweight external APIs.
Knowledge sources must be used for unstructured content.
Agent flows must be used to encapsulate reusable logic (e.g., rebooking).
Business requirements
Omnichannel support
Deploy the agent across web, mobile, and Teams with a consistent user experience. The Teams deployment must also support internal staff.
Self-service capabilities
The agent must handle common inquiries such as:
- Flight status
- Booking and rebooking
- Loyalty program questions
- Travel policies and baggage rules
Human escalation
If the agent cannot resolve an issue or the user requests help, it must:
- Escalate to a human agent.
- Transfer the conversation transcript and relevant context.
- Redact any sensitive personal data before escalation.
Knowledge integration
The agent must use scalable methods for knowledge integration and must not rely on manually authored Q&A topics for each document.
Performance metrics
First-contact resolution: +25%
Tier-1 call deflection: โฅ20%
Response time: 90% of queries answered within 30 seconds
Accuracy: โฅ95% for known FAQs
CSAT: โฅ85% for AI-handled interactions
Technical requirements
Platform constraints
No custom code is permitted; only Copilot Studio's built-in tools may be used.
All backend logic must be implemented using agent flows.
Markdown must be used for formatting (e.g., bold, bullet points); HTML is not supported.
Authentication
Sign-in is required for personal data access.
Anonymous access is allowed for general inquiries.
User identity must be used for data access; shared or builder credentials must not be used.
Compliance and security
Power Platform DLP policies must be enforced to block unauthorized data flows.
Responsible AI content moderation filters must be enabled.
Prompt modifications must be added to enforce tone, disclaimers, and refusal behavior.
Disclaimers must be applied consistently across all generative responses. Manual edits to individual topics must be avoided.
Monitoring and maintenance
All conversations and actions must be logged for auditing.
Weekly reviews of transcripts and metrics must be conducted.
Topics, flows, and knowledge sources must be updated as policies or systems evolve.
Issues and constraints
API rate limits: External APIs (e.g., flight status) have usage limits. Agent flows must handle retries and caching to avoid exceeding quotas.
Knowledge base limits: Copilot Studio has limits on the number and size of indexed documents.
Large files must be split or summarized.
Generative answer risks: Generative responses must be constrained to avoid policy violations.
Prompt modifications and filters must be used to enforce tone, safety, and compliance.
User input variability: Users phrase questions in diverse ways. Topics must include varied trigger phrases and fallback handling.
Authentication UX: The agent must clearly explain when sign-in is required and handle transitions smoothly across channels.
Problem statement
Blue Yonder Airlines must deploy a secure, scalable, and policy-compliant AI agent using Microsoft Copilot Studio. The agent must deliver accurate, helpful, and safe responses across multiple channels, integrate with enterprise systems, and support both anonymous and authenticated users. It must adhere to strict data protection and Responsible AI standards while improving customer service efficiency and satisfaction.
Drag and Drop Question
You need to implement tool usage in topics that meet the Blue Yonder design and governance requirements.
Which implementation method should you use for each requirement? To answer, move the appropriate implementation methods to the correct requirements. You may use each implementation method 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: Add a Question node for the user to choose the tool.
Let the agent decide when to run a tool based on user input.
Box 2: Add an Adaptive card
Run a specific agent flow at a defined step in a topic.
You can run a specific agent flow at a defined step in your topic by using an Ask with Adaptive card node to collect user input, and then triggering the flow using the submitted data.
Box 3: Add a tool node
Use a connector action to retrieve data during a conversation.
Reference:
https://learn.microsoft.com/en-us/microsoft-copilot-studio/authoring-ask-with-adaptive-card
NEW QUESTION # 134
A tenant administrator configures a Copilot connector that indexes content from an external knowledge system into Microsoft Graph.
A builder is building an agent that must:
- Use the indexed enterprise knowledge during answer generation.
- Avoid duplicating or manually uploading the same content.
- Avoid invoking the system as a transactional tool.
You need to configure the agent so that responses are grounded in the authorized knowledge sources.
What should you do?
Answer: B
Explanation:
You should add the Copilot connector as a knowledge source for the agent.
Grounding via Microsoft Graph: Since the external knowledge system is already being indexed into Microsoft Graph via a Copilot connector, it is already optimized as a read-only semantic knowledge base. In Copilot Studio or the Agent Builder, you simply enable or select this existing Copilot connector from your available knowledge sources.
Avoids Duplication: Adding it as an existing knowledge source directly references the data already indexed in the Graph, preventing you from manually uploading files or duplicating content.
Avoids Transactional Invocation: Creating a new custom connector inside the agent configuration utilizes Power Platform connectors. Power Platform connectors are designed for tool invocation (real-time API calls, writing data, and performing transactional operations), which violates your requirement to avoid a transactional tool setup.
Reference:
https://learn.microsoft.com/en-us/microsoft-copilot-studio/knowledge-copilot-connectors
NEW QUESTION # 135
Drag and Drop Question
A team has deployed an agent in Copilot Studio and needs to evaluate whether the agent is meeting its intended goals before expanding usage to a broader audience.
The team must evaluate agent performance using a structured and repeatable approach that produces actionable insights.
You need to select and apply an appropriate evaluation method by performing the required actions in the correct order.
In which order should you perform the actions? To answer, move all actions from the list of actions to the answer area and arrange them in the correct order.
Answer:
Explanation:
Explanation:
Step 1: Define the success criteria and evaluation objectives
You must always start by establishing what "success" looks like and what you are trying to measure. Without clear goals, you cannot choose the right metrics.
Step 2: Select the evaluation method and metrics aligned to the criteria Once goals are set, you determine how to measure them (e.g., using automated tests, human reviewers, or user satisfaction scores) and define specific key performance indicators (KPIs).
Step 3: Collect agent interaction data and evaluation signals
After setting up your metrics, you run the evaluation by gathering conversational logs, user feedback, and system performance telemetry during agent interactions.
Step 4: Review evaluation results and identify improvement opportunities Finally, you analyze the gathered data against your original criteria to pinpoint bottlenecks, conversational failures, or gaps, allowing you to iterate and improve the agent.
NEW QUESTION # 136
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