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| Section | Weight | Objectives |
|---|---|---|
| Plan and configure agent solutions | 30–35% | - Configure agent foundations
|
| Test, deploy, and manage agents | 20–25% | - Deploy and manage agent lifecycle
|
| Build and extend agents in Copilot Studio | 40–45% | - Implement advanced capabilities
|
>> Latest AB-620 Test Objectives <<
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NEW QUESTION # 16
A company uses multiple Copilot Studio agents that perform specialized tasks.
You need to configure a Copilot Studio agent in your environment to connect to an external agent.
What should you do?
Answer: D
Explanation:
You should provide the A2A endpoint information for the target agent.
When configuring a Microsoft Copilot Studio agent to connect to an external agent over the Agent2Agent (A2A) protocol, providing the target agent's public communication endpoint URL is the mandatory step required to establish the connection.
Reference:
https://learn.microsoft.com/en-us/microsoft-copilot-studio/add-agent-agent-to-agent
NEW QUESTION # 17
A development team is reusing agents in Copilot Studio across development, test, and production environments.
You need to ensure the agents meet the following requirements:
Reusable components must support governed promotion across environments.
Environment-specific configuration must not be hard-coded.
Deployments must support automated, multi-stage approvals.
You need to configure the agents based on the business requirements.
Answer:
Explanation:
Explanation:
Reusable governed components # Export or package them as a component collection; Environment- specific connections and secrets # Use connection references and environment variables; Automated staged approvals # Use an ALM pipeline.
Comprehensive and Detailed Explanation From Microsoft AB-620 Study Guide: Reusable authored assets should be packaged in a governed component collection so the same topics and prompts can be promoted and consumed without uncontrolled copying. Values that differ by environment must remain outside those authored assets: connection references bind connectors in the target environment, while environment variables supply endpoints, IDs, and other configuration; secret values should use the appropriate secret mechanism. A Power Platform pipeline then moves the solution through defined stages and can impose approvals and validation before production. Hard-coding configuration would make every promotion a source edit, and copying components between agents would create divergent versions. The collection and the solution still need explicit ownership and dependency management, because a shared component update can affect multiple agents. Before each stage, validate current variable values, connections, component versions, and target permissions. After deployment, publish and run the same evaluation set in the target environment so the team verifies not only package transport but also runtime behavior under target data and identity controls. Study Guide alignment: Test and manage agents > Implement application lifecycle management for agents in Copilot Studio > Add existing agents to a solution; Create and use environment variables; Implement Power Platform Pipelines.
NEW QUESTION # 18
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.
You need to deploy the Blue Yonder Copilot agent to the public website and Microsoft Teams while ensuring compliance with the company's security and Responsible AI requirements.
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: A,B
Explanation:
[A]
You can configure prompt modifications at the system and agent level in Microsoft Copilot Studio to satisfy your organization's Responsible AI (RAI) guidelines.
[E]
Scenario:
Compliance and security
Responsible AI content moderation filters must be enabled.
Reference:
https://microsoft.github.io/agent-academy/operative/06-ai-safety/
NEW QUESTION # 19
A company is building an agent topic in Copilot Studio. The agent topic uses a generative answers node to respond to user questions based on authorized knowledge sources.
To meet the business needs, the generative answers node must meet the following requirements:
Use the user's message in the generative answers node.
Scope the topic node to query only designated data.
Restrict responses to approved enterprise data.
Answer:
Explanation:
NEW QUESTION # 20
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: A
Explanation:
Requiring grounding prevents the agent from generating an answer when relevant content isn't retrieved. Configuring Azure AI Search as the knowledge source ensures enterprise indexed content supplies the grounding context, while the response is generated through the configured Microsoft Foundry model. Microsoft also documents that disabling Allow ungrounded responses restricts answers to configured knowledge sources.
Reference:
https://learn.microsoft.com/en-us/microsoft-copilot-studio/knowledge-azure-ai-search
https://learn.microsoft.com/en-us/microsoft-copilot-studio/faqs-generative-answers
https://learn.microsoft.com/en-us/microsoft-copilot-studio/guidance/retrieval-augmented-generation
NEW QUESTION # 21
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