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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Build business application logic and automation | 40-45% | - Business logic
|
| Topic 2: Create a foundation for intelligent applications | 25-30% | - Build data models in Dataverse
|
| Topic 3: Create intelligent applications | 25-30% | - Create canvas apps
|
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NEW QUESTION # 16
Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might have more than one correct solution, while others might not have a correct solution.
After you answer a question in this section, you will NOT be able to return to it. As a result these questions will not appear on the review screen.
A company integrates external systems into Power Automate by using cloud flows.
The company must connect to external services with different characteristics and determine whether a custom connector is required.
You need to evaluate if a custom connector is necessary to meet the requirements.
Solution: A cloud flow must call a REST API by using a one-time HTTP action without reuse across flows.
Does the solution meet the goal?
Answer: B
Explanation:
The requirement does not make a custom connector necessary. A one-time, non-reusable REST request can be implemented with an appropriate HTTP action by supplying the endpoint, method, authentication, headers, query parameters, and request body. The response can then be parsed or referenced in that same flow. A custom connector is most valuable when an API must be exposed as reusable, named operations across several flows or apps, when makers need a shared schema and authentication definition, or when governance requires a managed API abstraction. The scenario explicitly states that reuse is not required, so building and maintaining that abstraction would be unnecessary. The designer must still confirm that the HTTP action supports the service's authentication method, that licensing is available, and that environment data policies allow the endpoint. Those implementation constraints do not change the connector decision given. The Study Guide objective is "evaluate and recommend connectors," which requires distinguishing a direct HTTP call from a reusable custom connector. Since the proposed one-off call can be made natively, the answer is No.
Study Guide reference/topic: "Create cloud flows - Evaluate and recommend connectors." AB-410 Study Guide | Microsoft Learn technical reference
NEW QUESTION # 17
A company builds a canvas app for support agents to enter customer notes and generate a summarized response by using a custom prompt.
The company requires the following functionality built into the prompt:
# Generate the summary immediately when the agent selects a button in the app.
# Supply current user-entered data to the prompt.
You need to execute the prompt.
Which two actions should you perform? Each correct answer presents part of the solution. NOTE: Each correct selection is worth one point.
Answer: C,D
Explanation:
The app should pass the current user-entered values as prompt parameters and invoke the prompt directly from the button's Power Fx logic. Parameters ensure that the generated summary is grounded in the text currently displayed in the app rather than stale or hard-coded data. Direct invocation from the button provides the immediate interactive behavior required by the scenario. A cloud flow can also consume a prompt, but it adds an orchestration layer that is unnecessary when the requirement is limited to a synchronous canvas-app interaction. Publishing the prompt is part of making a completed component available, but it does not execute the prompt or provide the current input. Updating general app settings is unrelated. The button formula should validate blank content, handle errors, and place the returned summary in a variable or control only after a successful response. The prompt's inputs and output should be typed and tested for expected maximum lengths. The Study Guide explicitly includes "add inputs to a prompt" and "consume a prompt in apps." Options B and C meet those two runtime responsibilities.
Study Guide reference/topic: "Create prompts and models in AI Hub - Consume a prompt in apps." AB-410 Study Guide | Microsoft Learn technical reference
NEW QUESTION # 18
A company is designing a Power Platform solution that includes a model-driven app used by customer service representatives to manage support cases.
The company is evaluating which solution component to include in the app .
The solution must meet the following requirements:
# Users must interact with system-generated responses while working within forms and views.
# Responses must reflect the current data and context in the app.
# Users must remain within the app while interacting with the solution.
You need to recommend solution components for the app.
Which two components should you recommend? Each correct answer presents a complete solution. NOTE:
Each correct selection is worth one point.
Answer: A,C
Explanation:
A Copilot Studio agent and an app assistant agent are the two components designed for contextual, in-app conversational interaction. A Copilot Studio agent can be embedded or made available within the business solution and can use configured knowledge, actions, and conversation topics to answer users while they remain in the application. An app assistant agent is intended to assist users in the context of the model-driven app and its current business data. Business rules execute deterministic form or table logic; they cannot provide a conversational response experience. Smart assist surfaces suggested knowledge articles or similar recommendations in supported customer-service scenarios, but it is not the general conversational component described by the requirements. The implementation must also govern grounding sources and security so an agent cannot reveal records the user is not authorized to access. The AB-410 Study Guide asks candidates to
"evaluate built-in agents to include in the business solution" and to integrate Copilot capabilities into model- driven experiences. Those objectives support selecting the two agent-based components rather than validation or recommendation-only features.
Study Guide reference/topic: "Design Power Platform solutions - Evaluate built-in agents." AB-410 Study Guide | Microsoft Learn technical reference
NEW QUESTION # 19
You need to configure a Power Automate flow to send the email with the results to the client. What should you use? To answer, select the appropriate options in the answer area. NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
Trigger: Set Table name to Qualification and select/filter on the Status Reason column. Completion logic: List the related Qualification rows and complete the Service Request only if all are in Complete status.
The flow should start when a Qualification row is modified because completion of an individual qualification is the event that can make its parent Service Request eligible for completion. Configure the Dataverse trigger for the Qualification table and include the Status Reason column in Select columns so unrelated updates do not start the flow. Where appropriate, add an OData filter condition for the Complete status value. Triggering on Service Request would be too late because that row must be completed by the automation. The flow must then retrieve all Qualification rows related to the same Service Request and verify that every row has reached Complete. It must not decide from the current Qualification alone: one completed child does not prove that the other related qualifications are finished. If no incomplete child rows remain, the flow updates the parent status and sends the templated client email. Microsoft documents that Select columns limits Dataverse update triggers to requests containing designated scalar columns and that List rows supports OData filtering of related records.
Reference: https://learn.microsoft.com/en-us/power-automate/dataverse/create-update-delete-trigger Study Guide alignment: Build business application logic and automation.
NEW QUESTION # 20
A company wants to monitor an AI application's performance after deployment. The team needs information about response quality, latency, failures, and user interactions. Which practice should be implemented?
Answer: D
Explanation:
Monitoring and telemetry provide visibility into AI application behavior after deployment. Important metrics include latency, errors, user feedback, and response quality. Production AI systems require continuous evaluation because data patterns and user expectations change over time.
Model weights alone cannot reveal operational issues or application performance problems.
NEW QUESTION # 21
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