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| Section | Objectives |
|---|---|
| Plan and Design Copilot Studio AI Agents | - Designing conversation flows and agent behavior - Selecting Copilot Studio capabilities and architecture approach - Requirements analysis for AI agent solutions |
| Deploy, Monitor, and Optimize AI Agents | - Iterative improvement and lifecycle management - Publishing and deploying copilots - Monitoring performance and analytics |
| Integrate External Systems and Data Sources | - Connecting Azure services and APIs - Integrating Dataverse and Power Platform components - Using Power Automate for workflow orchestration |
| Build and Configure AI Agents in Copilot Studio | - Creating and configuring copilots and topics - Configuring actions, plugins, and connectors - Using generative AI and prompt engineering in Copilot Studio |
| Governance, Security, and Compliance | - Data protection and responsible AI practices - Environment management in Power Platform - Managing access control and authentication |
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70. Frage
A company is building an agent in Copilot Studio.
The agent must meet the following requirements:
Responses must be grounded in approved internal content.
The agent must be able to retrieve information from configured data sources in a topic.
You need to configure the agent so that topic responses are grounded from custom data sources.
What should you configure?
Antwort: C
Begründung:
Comprehensive and Detailed Explanation From Microsoft AB-620 Study Guide: A generative answers node inside the topic is the correct place to retrieve from configured knowledge sources for that specific conversational path. The node can use the user ' s message as input, search designated sources, and generate a grounded response from the retrieved content. Topic-level sources can override the broader agent-level set, which is useful when the topic must restrict itself to approved data. A custom prompt that merely instructs the model to use company information does not create or enforce a retrieval connection. Increasing the response limit affects length, not grounding. Analytics measures usage after the fact and cannot supply knowledge.
Adding SharePoint only at agent level is unnecessarily narrow and would not satisfy the requirement for custom sources configured within the topic. The builder should enable Search only selected sources when strict scoping is required and turn off general knowledge if no ungrounded fallback is allowed. Testing should inspect both the answer and the resource details to confirm that the intended source supplied the evidence.
Study Guide alignment: Plan and configure agent solutions > Configure topics > Configure generative answers node; Configure advanced agent responses with custom knowledge sources.
71. Frage
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?
Antwort: B
Begründung:
To prevent your agent from generating ungrounded answers and restrict it to responding only when relevant content is found, you should configure the agent to require grounding for generative answers and use Azure AI Search as the retrieval source.
Enforces Grounding: Enabling the option to require grounding or disabling the ability for the AI to use its own general knowledge ensures that the Microsoft Foundry model will strictly use the data pulled from your indexed enterprise content.
Prevents Hallucinations: If Azure AI Search does not retrieve relevant document chunks for a specific user query, the agent will gracefully refuse to answer rather than fabricating a response based on pretrained model weights.
Reference:
https://techcommunity.microsoft.com/blog/azure-ai-foundry-blog/turn-enterprise-knowledge-into-answers-with-copilot-studio-and-azure-ai-search/4493118
72. Frage
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.
Antwort:
Begründung:
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
73. Frage
A team is preparing to evaluate an agent in Copilot Studio before expanding access to additional users.
The team must choose an evaluation method that meets the following requirements:
Use a fixed set of prepared interactions.
Determine responses against a predefined baseline.
Support consistent comparison across repeated test runs.
You need to determine the evaluation method that satisfies the evaluation requirements.
Antwort:
Begründung:
Explanation:
Fixed prepared interactions # Use a curated prompt list; Predefined baseline # Compare against predefined expected outcomes; Repeatable comparison # Use a consistent scoring evaluation matrix.
Comprehensive and Detailed Explanation From Microsoft AB-620 Study Guide: A curated prompt list creates the controlled input population required for repeatability. Predefined expected outcomes establish what a correct or acceptable response should contain, which lets the evaluator judge performance against a baseline rather than against a reviewer ' s memory. A stable scoring matrix ensures that repeated runs are interpreted under the same thresholds and dimensions. Live conversations and post-rollout feedback can enrich the test inventory, but they cannot replace a fixed regression set because the questions, users, and context change. Publishing status confirms deployment, not response quality. General impressions are similarly unsuitable for consistent comparison. The team should select the scoring method according to the response type: semantic comparison for valid paraphrases, exact match for immutable values, keyword checks for mandatory phrases, and custom criteria for compliance or domain quality. Versioning the prompt list, expected answers, rubric, agent version, and knowledge snapshot is essential; otherwise a changed test set can be mistaken for a change in agent performance. Study Guide alignment: Test and manage agents > Evaluate agent performance > Create a test set; Choose an evaluation method.
74. Frage
A company has an existing custom connector that is approved and available in the environment. A builder wants an agent in Copilot Studio to call the connector during a conversation to retrieve information from an internal system.
To meet the business needs, the solution must meet the following requirements:
The agent must make the connector available for topic steps.
The agent must run the connector call with a valid connection.
The connector call must receive the required input values at runtime.
You need to configure the agent so the custom connector can be used as a tool.
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.
Antwort:
Begründung:
75. Frage
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