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| Section | Objectives |
|---|---|
| Topic 1: Integrate External Systems and Data Sources | - Integrating Dataverse and Power Platform components - Using Power Automate for workflow orchestration - Connecting Azure services and APIs |
| Topic 2: Deploy, Monitor, and Optimize AI Agents | - Publishing and deploying copilots - Iterative improvement and lifecycle management - Monitoring performance and analytics |
| Topic 3: Build and Configure AI Agents in Copilot Studio | - Creating and configuring copilots and topics - Using generative AI and prompt engineering in Copilot Studio - Configuring actions, plugins, and connectors |
| Topic 4: Governance, Security, and Compliance | - Managing access control and authentication - Data protection and responsible AI practices - Environment management in Power Platform |
| Topic 5: Plan and Design Copilot Studio AI Agents | - Requirements analysis for AI agent solutions - Designing conversation flows and agent behavior - Selecting Copilot Studio capabilities and architecture approach |
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NEW QUESTION # 44
A team is standardizing ALM for agents in Copilot Studio.
The team requires a custom solution that includes agents. The solution must support ALM scenarios, such as managing and transporting agent assets across environments and pipeline deployments.
You need to create an ALM-ready custom solution in Copilot Studio.
What should you do?
Answer: C
Explanation:
To establish an ALM-ready custom solution from the very beginning, you should Create a new custom solution from the Solutions area.
When building an agent in Microsoft Copilot Studio that requires proper Application Lifecycle Management (ALM), the end-to-end framework consists of three sequential lifecycle actions:
1. Initiate inside a Solution: Navigate to Solutions, select Create a new solution, define a custom publisher/prefix, and create or add your agent inside this container. This ensures that the agent and all its dependencies (topics, prompts, variables) are scoped to that specific package from day one instead of landing in the Default Solution.
2. Package and Move: Once your development phase passes validation, you Export the custom solution as a managed solution from your Development environment.
3. Deploy to Target: You then Import it into the Test and Production environments. Using a managed solution locks the components in downstream environments, preventing unmanaged customization drift and maintaining environment stability.
Reference:
https://learn.microsoft.com/en-us/microsoft-copilot-studio/authoring-solutions-overview
NEW QUESTION # 45
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: C
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 # 46
A team is developing an agent in Copilot Studio and wants to evaluate its behavior before expanding access.
The team needs a repeatable, consistent method to test the agent using predefined interactions.
You need to ensure that agent responses can be evaluated consistently across multiple test runs.
What should you do?
Answer: C
Explanation:
Defining test sets of prompts and expectations is the correct and recommended action to take.
Microsoft Copilot Studio includes a built-in feature specifically designed for this purpose called Agent Evaluation. This framework replaces subjective spot-checking with automated, scalable regression testing to ensure your agent behaves safely and consistently before you expand user access.
Reference:
https://techcommunity.microsoft.com/blog/copilot-studio-blog/agent-evaluation-in-microsoft-copilot-studio-is-now-generally-available/4507392
NEW QUESTION # 47
Drag and Drop Question
A company wants to extend an agent in Copilot Studio by calling an external REST API to retrieve and update data.
To meet the business needs, the REST API must be added following a correct dependency order.
You need to add a REST API to the agent so it can be invoked during conversations.
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: Add the REST API tool.
In Copilot Studio you start from Tools → Add a tool → New tool → REST API. Nothing else can be configured until the tool object exists in the agent.
Step 2: Configure the API endpoint details.
Supply the base URL, path, HTTP method (GET/POST for "retrieve and update data"), parameters, and request/response schema. This defines what is being called and must come before securing it.
Step 3: Configure authentication for the API
Choose the auth type (API key, OAuth 2.0, none) and its connection details. Auth is bound to the defined endpoint, so it logically follows endpoint definition - you can't attach credentials to a call that hasn't been described yet.
Step 4: Test the API configuration
Validation is always last. Testing requires a complete, authenticated request; only after the tool succeeds in test do you add it to a topic or let the agent invoke it generatively.
Reference:
https://learn.microsoft.com/en-us/microsoft-copilot-studio/agent-extend-action-rest-api
https://learn.microsoft.com/en-us/training/modules/take-action-external-systems-connector-rest-api-tools-copilot-studio/5-add-rest-api-tool
NEW QUESTION # 48
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: E
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 # 49
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