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| Section | Weight | Objectives |
|---|---|---|
| Integrate and Extend Agents in Copilot Studio | 40-45% | - Build advanced agent solutions
|
| Test and Manage Agents | 20-25% | - Monitor and manage agent solutions
|
| Plan and Configure Agent Solutions | 30-35% | - Plan agent solutions
|
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NEW QUESTION # 66
An agent must escalate to a live human agent when it cannot resolve a customer issue, and hand off full conversation context. Which node should you add to the topic?
Answer: C
NEW QUESTION # 67
Drag and Drop Question
A company uses an agent in Copilot Studio to answer questions based on enterprise content.
The content is indexed in Azure AI Search. Responses must be generated by a Microsoft Foundry model.
To meet the business needs, the solution must meet the following requirements:
- Users are able to trace each answer back to its source.
- The agent retrieves information from a centralized data index.
- Responses are generated by an enterprise-approved foundation model.
You need to configure generative answers for the agent.
What should you configure for each requirement? To answer, move the appropriate configurations to the correct requirements. You may use each configuration 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: Instruct the agent to cite sources in knowledge settings
The specific behavior of how the agent presents that information-such as enforcing citations and tracing links back to the source documents-is controlled by the instructions and configurations within the agent's knowledge and conversation settings. You must explicitly configure the agent's prompt instructions or system settings to format the output with source citations so users can trace the answers.
Box 2: Configure Azure AI Search as the grounding data source
By adding Azure AI Search as a knowledge source Microsoft Copilot Studio enables the Retrieval-Augmented Generation (RAG) pattern. This ensures your generative AI model retrieves specific enterprise content from your centralized index and uses it to ground responses.
Box 3: Deploy a model in Foundry to an agent and connect to Copilot Studio Model Control: To strictly guarantee that an enterprise-approved foundation model (such as a specific Microsoft Foundry model) generates the response, you must manually deploy that specific model and link it to your agent.
Connection Workflow: Deploying the custom model in Azure AI Studio (formerly encompassing parts of Azure AI Foundry) and connecting it to Copilot Studio ensures the orchestration layer routes prompts directly to your certified LLM.
Reference:
https://learn.microsoft.com/en-us/azure/foundry/agents/how-to/tools/ai-search
NEW QUESTION # 68
A company uses a supported Power Platform connector to provide real-time access to enterprise records for knowledge grounding in an agent in Copilot Studio.
To meet the business needs, the knowledge source must provide the following functionality:
Avoid copying enterprise data into an index.
Keep source-system access controls enforced.
Access data by calling the system at runtime.
You need to configure the connector knowledge source.
What should you configure for each requirement? To answer, move the appropriate configurations to the correct requirements. You may use each configuration once, more than once, or not at all. You may need to move the split bar between panes or scroll to view content.
Answer:
Explanation:
Explanation:
Avoid indexing business records # Retrieve data without indexing; Preserve source-system controls # Use existing permissions; Access current data at runtime # Use a real-time Power Platform connector.
Comprehensive and Detailed Explanation From Microsoft AB-620 Study Guide: Power Platform real- time knowledge connectors query the source system when the agent needs an answer. Microsoft indexes metadata needed to understand the available tables and fields, but the business records themselves are not copied into a separate content index. Because the request is executed through the established connection, the source system ' s permissions remain part of the access decision. This is materially different from a Copilot connector, which indexes external content into Microsoft Graph, and from Azure AI Search, which relies on a maintained search index. The real-time pattern is best when current operational records and source-enforced access are more important than broad document search. The connection must be governed with the same Power Platform data policies that apply to actions, and authentication should reflect whether access is user- delegated or provided by a service identity. Testing under users with different permissions is essential to confirm that the agent cannot return records a user could not access directly and that changes in the source appear without an indexing delay. Study Guide alignment: Integrate and extend agents in Copilot Studio > Connect to enterprise knowledge sources > Connect to Microsoft Power Platform connectors.
NEW QUESTION # 69
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 # 70
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 by 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: C,D
NEW QUESTION # 71
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