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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Build and extend agents in Copilot Studio | 40–45% | - Develop agent flows and logic
|
| Topic 2: Test, deploy, and manage agents | 20–25% | - Deploy and manage agent lifecycle
|
| Topic 3: Plan and configure agent solutions | 30–35% | - Plan an agent solution
|
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問題 #90
A company uses an agent in Copilot Studio to coordinate user interactions.
The company wants the agent to delegate requests to a Microsoft Fabric Data Agent that accesses governed business data.
The agent must retrieve structured analytical data while enforcing data security and scope controls.
You need to select the integration approach that meets the requirements.
What should you use?
答案：A
解題說明：
To coordinate interactions while accessing governed data, you should create a Microsoft Fabric Data Agent and integrate it into Microsoft Copilot Studio using the Add Agent / Generative Orchestration feature.
Agent-to-Agent Collaboration: Instead of writing custom APIs, you can publish a specialized Fabric Data Agent in Microsoft Fabric, and then simply bind it as an external agent within Copilot Studio.
Built-in Security & Scope: Fabric enforces existing data constraints. Data access runs under the authenticated user's identity, automatically respecting Power BI model-level read permissions, Row-Level Security (RLS), and Object-Level Security (OLS).
Seamless Context: This enables multi-step agent orchestration where Copilot Studio routes queries to the Fabric agent for complex analytical insights (translating natural language to SQL/DAX/KQL) without exposing raw data.
Reference:
https://learn.microsoft.com/en-us/fabric/data-science/data-agent-microsoft-copilot-studio
問題 #91
A team is preparing to manage agents in Copilot Studio by using ALM from Power Platform.
A solution must be created before agents and configuration of assets can be managed through ALM.
You need to create a solution that can contain agents and related assets.
Which three actions should you perform in order? To answer, move the appropriate actions from the list of actions to the answer area and arrange them in the correct order.
答案：
解題說明：
Explanation:
1. Open the Solutions area in Copilot Studio; 2. Define the solution name and publisher; 3. Save the solution container.
Comprehensive and Detailed Explanation From Microsoft AB-620 Study Guide: Solution creation begins in the Solutions area because that is the Copilot Studio entry point to the Power Platform solution explorer. The maker then supplies the solution name and publisher. The publisher is not cosmetic: it determines the customization prefix and forms part of the ownership and naming strategy for components that will move through ALM. Saving creates the solution container, after which agents, flows, connection references, environment-variable definitions, prompts, and other dependent assets can be added. Reviewing the solution details page can follow creation but is not one of the required creation steps in this three-action sequence. A custom solution is preferable to relying on the default solution for controlled export, source management, and pipeline deployment. Before export, the team should use dependency checks to ensure all assets required by the agent are included and should avoid including unrelated components. Downstream releases normally import a managed build of the solution, while development remains unmanaged so authorized makers can continue editing. Study Guide alignment: Test and manage agents > Implement application lifecycle management for agents in Copilot Studio > Create a solution.
問題 #92
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: ≥20%
Response time: 90% of queries answered within 30 seconds
Accuracy: ≥95% for known FAQs
CSAT: ≥85% 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 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.
答案：
解題說明：
Explanation:
Scenario: Problem statement: The agent must adhere to strict data protection and Responsible AI standards while improving customer service efficiency and satisfaction.
Step 1: Define Data Loss Prevention (DLP) policies
Security and compliance must be established at the foundation level. Admins use the Power Platform admin center to configure DLP policies. This establishes environmental guardrails by restricting unauthorized data connectors or preventing the agent from leaking sensitive data.
Step 2: Add custom prompt modifications
Once the environment is secure, the maker configures the specific behavior of the agent. Custom prompt modifications and agent instructions shape the tone, define conversational topics, and establish explicit boundaries for the generative model (e.g., instructing the model to strictly stay within its knowledge base).
Step 3: Conduct adversarial testing
This is the final evaluation phase before deployment. After the guardrails and custom prompts are in place, you simulate real-world attacks (such as jailbreaks, prompt injections, or malicious user inputs) to verify that the agent reliably adheres to your corporate guidelines and Microsoft's Responsible AI standards.
Reference:
https://learn.microsoft.com/en-us/troubleshoot/power-platform/copilot-studio/generative-answers/agent-response-filtered-by-responsible-ai
問題 #93
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.
答案：
解題說明：
問題 #94
A company is configuring an agent in Copilot Studio that uses a generative answers node inside multiple topics.
The company requires responses to meet the following requirements.
* Must use an executive summary format
* Must apply only within a specific topic.
* Must continue using configured knowledge sources.
* Must comply with connector security controls.
You need to configure a custom prompt to meet the formatting requirements Solution: Create a custom prompt tool in the specific topic that instructs the model to respond using an executive-summary structure.
Does the solution meet the goal?
答案：B
解題說明：
Comprehensive and Detailed Explanation From Microsoft AB-620 Study Guide: A separate custom prompt tool that merely requests an executive-summary structure does not, by itself, guarantee that the existing generative answers node and its configured knowledge sources remain in the response path. Prompt tools have their own inputs, knowledge configuration, model settings, and completion behavior. If the tool is invoked independently, it can generate correctly formatted text without using the sources selected for the topic's generative answer, which violates a stated requirement. The safer design is to keep the generative answers node and apply topic-specific custom instructions or prompt modification to that node, or explicitly pass its grounded output into a downstream formatting prompt with a controlled contract. Connector security remains enforced by the underlying connections and data policies; wording in a prompt cannot override those controls. Therefore, the proposed solution is incomplete and does not meet the goal as written. Testing should confirm not only the output format but also the sources used and the identity under which any connector retrieval occurred. Study Guide alignment: Plan and configure agent solutions > Configure topics > Configure advanced agent responses with custom prompts and custom knowledge sources.
問題 #95
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