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| Section | Objectives |
|---|---|
| Governance, Security, and Compliance | - Data protection and responsible AI practices - Environment management in Power Platform - Managing access control and authentication |
| 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 - Using Power Automate for workflow orchestration - Integrating Dataverse and Power Platform components |
| 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 |
| 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 |
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NEW QUESTION # 98
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:
Comprehensive and Detailed Explanation From Microsoft AB-620 Study Guide: The required first action is to create a custom solution from the Solutions area. A solution is the ALM carrier that groups the agent with its related components and enables controlled export, import, pipeline deployment, dependency management, and versioning across environments. Exporting an agent directly is not the supported replacement for solution-based ALM. A channel configuration determines where users can interact with a published agent; it is not a container for development assets. Exporting a managed solution and importing it into production is a later release step and cannot occur until the custom solution exists and contains the agent and its dependencies. After creation, the team should add the existing agent, associated flows, connection references, environment-variable definitions, prompts, and any other required components. Development normally occurs in an unmanaged solution, while a managed build is deployed to Test and Prod. This separation supports repeatable promotion, protects downstream environments from unmanaged edits, and provides a clearer rollback and support boundary. Study Guide alignment: Test and manage agents > Implement application lifecycle management for agents in Copilot Studio > Create a solution.
NEW QUESTION # 99
An agent calls a flow to a database. The agent requires structured output values to be returned. The agent receives unexpected or empty values.
You need to configure the agent so that data is exchanged correctly between the agent and the flow. What should you do?
Answer: E
Explanation:
Comprehensive and Detailed Explanation From Microsoft AB-620 Study Guide: The first configuration check is the contract between the agent and the flow. Input and output parameter definitions must agree on name, data type, required status, and mapping. A flow can complete successfully yet return an empty value to the agent if the response field is not mapped to the declared output or if the agent expects a different type. Validating the parameter definitions therefore addresses the actual data-exchange requirement. Reviewing run history is useful for diagnosis, but it does not correct a mismatched contract by itself. Changing the trigger schema or adding Parse JSON might be necessary in a specific implementation, yet neither should be done before confirming what the caller sends and what the flow returns. Republishing cannot repair an incorrect mapping. The builder should test the flow directly with known values, inspect each action output, verify the final response action, and then test from the agent. Optional and null fields should be handled explicitly, and sensitive outputs should be minimized and protected in logs. Study Guide alignment: Plan and configure agent solutions > Create and monitor agent flows in Copilot Studio > Add input and output parameters.
NEW QUESTION # 100
You deploy an agent in Microsoft Copilot Studio that triggers a cloud flow to update customer records in Microsoft Dataverse.
You observe the following after deploying the agent:
Several runs fail due to a temporary authentication issue.
The flow continues to trigger and generate additional failed runs.
You must:
Answer:
Explanation:
NEW QUESTION # 101
A company needs an agent in Copilot Studio to complete tasks by interacting with a legacy desktop application that does not use APIs. The builder needs that UI automation can run in the supported execution context and needs a way to inspect how the automation behaves during testing conversations. to validate To meet the business needs, the solution must meet the following requirements:
* Enable the agent to perform UI automation against the legacy application.
* Inspect execution details for the automation during conversations.
You need to configure the agent based on the requirements.
Which two actions should you perform? Each correct answer presents part of the solution. Choose two.
NOTE: Each correct selection is worth one point.
Answer: A,D
Explanation:
Comprehensive and Detailed Explanation From Microsoft AB-620 Study Guide: Computer use is the Copilot Studio capability for operating a website or desktop application ' s graphical interface when an API is unavailable. Enabling it gives the agent a UI automation tool driven through the supported machine execution context. During testing, the builder can open the computer-use activity or remote session from the agent ' s activity view to observe steps, inspect logs, and understand failures in real time. Adding a desktop flow is a different deterministic automation technology and is not required by the stated computer-use design.
Publishing alone does not provision the UI automation or its machine. A custom connector cannot automate screen controls when the application exposes no API. The tool should be configured with narrowly scoped instructions, a healthy supported machine, protected credentials, and human confirmation for sensitive actions. Because computer-use behavior is probabilistic and visual interfaces change, the team should test alternate screen states, pop-ups, timing, and recovery, then monitor production sessions under strict access and retention controls. Study Guide alignment: Integrate and extend agents in Copilot Studio > Add tools to agents > Configure and monitor computer use for an agent.
NEW QUESTION # 102
Drag and Drop Question
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.
- Validate before it is used by the agent.
You need to create a usable agent flow that the agent can invoke.
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: Create a new agent flow
Initialize the flow workspace from your platform's dashboard using a template or blank canvas.
Step 2: Define input values for the flow: Configure the flow's initial trigger parameters to accept structured data passed from the AI agent.
Step 3: Add the connector action and configure the connection
Set up the database or external system connector node to perform the data retrieval query using your defined inputs.
Step 4: Define output values for the flow
Map the retrieved system results into structured output parameters back within the response node so the agent can understand the payload.
Step 5: Test the flow run
Run a simulated diagnostic execution to validate that data transfers correctly and errors are handled before deploying it to production.
NEW QUESTION # 103
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