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| Section | Objectives |
|---|---|
| Topic 1: Integrate External Systems and Data Sources | - Using Power Automate for workflow orchestration - Connecting Azure services and APIs - Integrating Dataverse and Power Platform components |
| Topic 2: Build and Configure AI Agents in Copilot Studio | - Configuring actions, plugins, and connectors - Using generative AI and prompt engineering in Copilot Studio - Creating and configuring copilots and topics |
| Topic 3: Deploy, Monitor, and Optimize AI Agents | - Publishing and deploying copilots - Monitoring performance and analytics - Iterative improvement and lifecycle management |
| Topic 4: Governance, Security, and Compliance | - Environment management in Power Platform - Managing access control and authentication - Data protection and responsible AI practices |
| Topic 5: Plan and Design Copilot Studio AI Agents | - Selecting Copilot Studio capabilities and architecture approach - Designing conversation flows and agent behavior - Requirements analysis for AI agent solutions |
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NEW QUESTION # 120
A solution containing an agent in Copilot Studio is moved across environments. The agent relies on configuration values that differ between environments and are managed as environment variables.
You must ensure the following:
* Configuration values are managed through environment variables that support ALM.
* Runtime behavior reflects updates to environment variable values.
You need to implement environment-variable usage that supports ALM and ensures correct runtime behavior.
Which three actions should you perform? Each correct answer presents part of the solution.
NOTE: Each correct selection is worth one point.
Answer: A,C,E
Explanation:
Environment variables separate deployment-specific configuration from the agent's solution components.
Therefore, external references-such as endpoint URLs, resource identifiers, and other environment- dependent settings-should be stored as environment variables. The same agent definition can then move through development, testing, and production while administrators provide the appropriate value in each target environment. This satisfies option C and is fundamental to Power Platform application lifecycle management.
Environment variables exposed inside Copilot Studio are read-only. Agent authors can consume their values but cannot edit them directly while authoring topics. Administrators or authorized makers must modify the current values through the appropriate Power Platform administrative or solution-authoring experience, making option F correct and option E incorrect.
When a non-secret environment variable is updated, an already published agent does not automatically begin using the new value. The agent must be republished so its published runtime configuration incorporates the change, which makes option D correct. Secret environment-variable values are handled differently because they can be retrieved dynamically at runtime.
Hard-coding values would undermine solution portability, while assuming every update takes effect immediately ignores the publishing requirement. Relevant study-guide areas are Use environment variables , Move agents across environments , and Implement ALM for agents . See Use variables in Copilot Studio .
NEW QUESTION # 121
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.
Answer:
Explanation:
NEW QUESTION # 122
A company is building an agent that uses an agent flow to retrieve data from an external system and return structured output.
The company needs to create a flow that the agent can invoke to process requests and return results. To support this business need, the flow must meet the following requirements:
Accept parameters from the agent.
Execute an action to retrieve data from the database.
Ensure the agent receives the relevant output information.
Answer:
Explanation:
NEW QUESTION # 123
You need an agent to only be invoked by other trusted agents in the tenant, not directly by end users. What should you configure?
Answer: D
Explanation:
Configuring an agent as a connected agent (invoked by an orchestrating agent) without publishing a standalone end-user channel restricts its use to agent-to-agent delegation.
NEW QUESTION # 124
You need to configure generative answers so the agent meets Fabrikam Inc. ' s business requirements Which solutions should you use? To answer, move the appropriate solutions to the correct requirements. You may use each solution 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:
Trace each answer to its source # Instruct the agent to cite sources in knowledge settings; Retrieve from the centralized index # Configure Azure AI Search as the grounding data source; Use an enterprise- approved foundation model # Select a model from the Foundry model catalog.
Comprehensive and Detailed Explanation From Microsoft AB-620 Study Guide: Each requirement is controlled by a different configuration layer. Source traceability is a presentation and grounding requirement, so citations must be enabled or explicitly required for knowledge-based responses. That allows users to inspect the material used to support a policy answer; it is not achieved merely by choosing a model.
Centralized retrieval is provided by connecting the existing Azure AI Search vector index as the knowledge source. This preserves the curated index, semantic or vector retrieval behavior, and enterprise management of the policy corpus instead of copying documents into the agent. Model governance is handled in the prompt configuration by selecting the approved model from the Microsoft Foundry model catalog. Publishing does not automatically replace an unapproved model, and Azure AI Search does not enforce the foundation-model selection. Together, the three settings form a complete RAG path: Azure AI Search retrieves authoritative passages, the governed model produces the response, and citation settings expose provenance. The configuration should then be tested with representative policy questions to confirm that the response is grounded and that the cited source actually supports the answer. Study Guide alignment: Integrate and extend agents in Copilot Studio > Integrate agents with Azure > Configure generative answers by using Azure AI Search with Foundry; Configure custom prompts to use the Foundry model catalog.
Topic 2, 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. 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 summariz ed.
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.
NEW QUESTION # 125
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