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| Section | Objectives |
|---|---|
| Governance, Security, and Compliance | - Managing access control and authentication - Environment management in Power Platform - Data protection and responsible AI practices |
| Integrate External Systems and Data Sources | - Integrating Dataverse and Power Platform components - Connecting Azure services and APIs - Using Power Automate for workflow orchestration |
| 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 |
| Deploy, Monitor, and Optimize AI Agents | - Publishing and deploying copilots - Iterative improvement and lifecycle management - Monitoring performance and analytics |
| 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 |
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NEW QUESTION # 116
You create a test set in Copilot Studio to evaluate an agent that answers policy questions and retrieves data from connected knowledge sources. The evaluation threshold is set to 0.80.
You run the evaluation and review the following result for one test case:
Expected response: Digital products are non-refundable after download.
Actual response: Digital products cannot be refunded once downloaded.
Result: Pass
Score: 0.92
Reasoning: The actual response semantically matches the expected response.
Knowledge sources used: RefundPolicy_KB
Tools invoked: None
You need to determine whether additional corrective action is required based on the evaluation results.
Which two actions should you perform? Each correct answer presents a complete solution. Choose two.
NOTE: Each correct selection is worth one point.
Answer: A,B
Explanation:
Comprehensive and Detailed Explanation From Microsoft AB-620 Study Guide: The test passed because the score of 0.92 exceeds the configured threshold of 0.80 and the evaluation method recognizes semantic equivalence. The actual answer conveys the same policy meaning as the expected response even though the wording is different, so an exact textual match is unnecessary. The recorded knowledge source is RefundPolicy_KB, which is the expected grounding path; confirming that source behavior is therefore appropriate. No tool was expected or invoked, so investigating tool configuration would add noise rather than address a defect. A score below 1.00 is not itself a failure, and rewriting the expected answer to mirror every valid paraphrase would undermine a meaning-based evaluation. The result can be accepted while still being retained as regression evidence. Reviewers should confirm that the cited or retrieved policy content supports the non-refund statement and that the chosen threshold reflects the business risk. For fixed codes or legally prescribed phrases, exact match might be preferable, but this natural-language policy answer is correctly evaluated by semantic similarity. Study Guide alignment: Test and manage agents > Evaluate agent performance > Review test results.
NEW QUESTION # 117
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:
Explanation:
1. Create a new agent flow; 2. Define input values; 3. Add the database connector action and configure its connection; 4. Define output values returned to the agent; 5. Test the flow run.
Comprehensive and Detailed Explanation From Microsoft AB-620 Study Guide: The flow container must exist before its interface and implementation can be configured. Inputs are defined early so the agent has a typed contract for the values it will pass, such as an account ID or search criterion. The connector action then uses those inputs to query the database through a valid connection. Output parameters are mapped from the connector result so the calling agent receives only the relevant structured values rather than an opaque internal payload. Testing comes last because it validates the completed contract, connection, query, transformation, and returned output together. Omitting output definitions is a common reason an agent receives blank or unusable data even though the connector action itself succeeded. Input and output names should be descriptive, types must agree on both sides, and sensitive fields should be excluded unless genuinely required. After the flow passes direct tests, add or publish it as a tool and verify the end-to-end conversation path, including invalid input, empty-result, authentication, and timeout scenarios. Study Guide alignment: Plan and configure agent solutions > Create and monitor agent flows in Copilot Studio > Create an agent flow; Add input and output parameters.
NEW QUESTION # 118
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: D
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 # 119
You run the same fixed test set three times in Copilot Studio.
During evaluation, you observe the following:
The same interaction fails in all three runs.
Score values range from 0.58 to 0.61.
The reasoning states that the response partially matches the expected answer.
The knowledge source that is used is internal documentation.
No tools are invoked.
Answer:
Explanation:
NEW QUESTION # 120
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: A
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 # 121
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