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| Section | Objectives |
|---|---|
| Governance, Security, and Compliance | - Data protection and responsible AI practices - Managing access control and authentication - Environment management in Power Platform |
| Plan and Design Copilot Studio AI Agents | - Requirements analysis for AI agent solutions - Selecting Copilot Studio capabilities and architecture approach - Designing conversation flows and agent behavior |
| Build and Configure AI Agents in Copilot Studio | - Using generative AI and prompt engineering in Copilot Studio - Creating and configuring copilots and topics - Configuring actions, plugins, and connectors |
| Integrate External Systems and Data Sources | - Using Power Automate for workflow orchestration - Integrating Dataverse and Power Platform components - Connecting Azure services and APIs |
| Deploy, Monitor, and Optimize AI Agents | - Publishing and deploying copilots - Iterative improvement and lifecycle management - Monitoring performance and analytics |
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NEW QUESTION # 85
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 must be able to trace each answer back to its source.
The agent must retrieve information from a centralized data index.
Responses must be 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.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
NEW QUESTION # 86
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.
Answer:
Explanation:
Explanation:
* Outcome of individual evaluation cases # Pass or fail status
* Behavior observed across repeated runs # Consistent outcomes
* Details presented in evaluation output # Expected and generated responses A recurring failure across several runs indicates a consistent pattern, not an intermittent result. However, evaluation results alone do not automatically establish the root cause or grant production approval; the failed cases still require investigation.
NEW QUESTION # 87
A company is integrating an agent in Copilot Studio into a custom application by using the Microsoft 365 Agents SDK.
The company has the following requirements for the application:
The deployment workflow must follow a dependency driven sequence.
The agent must be published before configuration values are retrieved.
End-to-end validation must occur before production deployment.
You need to plan the deployment workflow to integrate the agent.
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:
NEW QUESTION # 88
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: A,E
Explanation:
Comprehensive and Detailed Explanation From [Microsoft AB-620 Study Guide] First, create a custom solution in the development environment and add the existing agent by selecting Add existing → Agent → Agent. The solution acts as the application lifecycle management package that contains the agent and its dependent components. Required objects such as agent flows, environment variables, connection references, and custom connectors should also be included when applicable.
After the agent and its dependencies are included, export the solution from the development environment. Microsoft's documented procedure starts from the list of unmanaged solutions and exports the solution containing the agent. During the export process, the maker can select the appropriate package type. Production deployments commonly use a managed export, but the source development solution remains unmanaged; it does not need to be converted before export.
Removing topics directly from the solution is specifically discouraged because changing or removing agent components outside the standard Copilot Studio authoring interface can cause export or import failures. Publishing the agent to a channel is also unrelated to creating a solution package. After the solution is imported into production, the imported agent must be configured, tested, and published in that environment.
Relevant study-guide area: Test and manage agents → Implement application lifecycle management for agents in Copilot Studio → Create a solution and add existing agents to a solution. See Export and import agents using solutions.
NEW QUESTION # 89
Users can add content to a paragraph field in a team-managed project, but they cannot @mention other users.
Identify the cause.
Answer: A
Explanation:
Comprehensive and Detailed Explanation From [Atlassian Jira Cloud Documentation] The cause is the Jira Browse users and groups global permission. Atlassian states that users with this permission can view user names when working with user-picker fields or @mentioning users. Without it, Jira cannot provide the affected users with the complete user directory required to search for and select another person through an @mention.
The fact that users can enter and save ordinary text in the paragraph field confirms that the field is present, editable, and available on the applicable work-item layout. Therefore, field settings and screen settings are not responsible. Notification settings determine how users receive updates after an event and do not control whether names appear in the mention picker.
Project permissions and issue-level security can affect whether a particular person can access the project or work item. However, a general inability to search for or mention other users indicates that the initiating users lack the site-wide user-browsing capability.
A Jira administrator should review Settings → System → Global permissions and grant Browse users and groups to an appropriate group containing the affected users, subject to the organization's privacy policies.
Relevant documentation topic: Jira Cloud administration → Global permissions → Browse users and groups. See What are global permissions, and what do they control?.
NEW QUESTION # 90
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