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| Section | Objectives |
|---|---|
| Topic 1: Implement automation and orchestration | - Process automation
|
| Topic 2: Design intelligent applications with Copilot and natural language | - AI-first application design
|
| Topic 3: Build intelligent applications on Microsoft Power Platform | - Application development
|
| Topic 4: Governance and application lifecycle management | - Responsible AI and ALM
|
| Topic 5: Embed agents and AI experiences | - Agent integration
|
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NEW QUESTION # 61
You need to implement the extensibility requirements.
Which two options should you use? Each correct answer presents part of the solution. NOTE: Each correct selection is worth one point.
Answer: B,D
Explanation:
Business rules and Power Apps component framework controls address the two extensibility requirements while minimizing unnecessary server-side code. A business rule implements supported validation or form
/table logic declaratively, making it preferable to a plug-in when the requirement can be satisfied without custom server execution. A Power Apps component framework control packages a reusable custom user- interface component that can be deployed in a solution and used across supported applications. A JavaScript web resource can customize form behavior but is not the preferred reusable control framework for a component with its own rendering and lifecycle. A sitemap controls model-driven app navigation and does not implement either reusable UI or business logic. A plug-in is valid for transactions that require server-side execution, but the case explicitly says to minimize that approach. The AB-410 Study Guide explicitly includes "recommend extensibility options." Selecting a declarative rule and a PCF control applies that objective to the distinct logic and UI requirements.
Study Guide reference/topic: "Design Power Platform solutions - Recommend extensibility options." AB-
410 Study Guide | Microsoft Learn technical reference
NEW QUESTION # 62
You need to implement a generative AI solution that meets the requirements.
Which two actions should you perform? Each correct answer presents part of the solution. NOTE: Each correct selection is worth one point.
Answer: A,C
Explanation:
The solution should use a prebuilt AI capability where it satisfies the complaint-processing requirement and create the generative prompt from blank for the organization-specific inspection report. Using a prebuilt model minimizes custom model development and training effort, which directly reflects the stated constraint.
A blank custom prompt gives the maker control over the inspection template, instructions, inputs, tone, and output format required by the business. Starting from a prompt template can accelerate common scenarios, but the case requires alignment to an existing custom inspection format; a blank prompt avoids carrying irrelevant template assumptions and permits deliberate grounding. Building a custom trained model would add data preparation, training, validation, and lifecycle overhead that the requirement seeks to minimize. The prompt should define required inputs explicitly and be tested with representative data to prevent the inconsistent output problem identified in the case. The Study Guide covers "build prompts from templates or from blank,"
"add inputs to a prompt," and consumption of AI capabilities in apps and flows. Options A and C provide the lowest-custom-development design that still supports the specific generative output.
Study Guide reference/topic: "Create prompts and models in AI Hub - Build prompts and consume AI capabilities." AB-410 Study Guide | Microsoft Learn technical reference
NEW QUESTION # 63
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 uses a model-driven app.
The company must be able to dynamically control how components of the form behave as users interact with it. The solution must modify the form in real time while the user interacts with the interface.
You need to enforce client-side behavior dynamically.
Solution: Use JavaScript to dynamically show and hide columns.
Does the solution meet the goal?
Answer: A
Explanation:
Correct:
* Use JavaScript to dynamically show and hide columns.
Using JavaScript to dynamically show, hide, or disable columns is an excellent and widely used solution for enforcing client-side behavior in a model-driven app. You achieve this in real time by adding JavaScript web resources and attaching event handlers to the form's OnLoad and OnChange events.
Incorrect:
* Use business rules to show inline error messages.
* Use Power Automate cloud flows to update column values.
Reference:
https://learn.microsoft.com/en-us/power-apps/maker/model-driven-apps/use-main-form-and-components
NEW QUESTION # 64
A company builds a canvas app that processes images submitted by users and must classify them using an existing AI Builder model.
The app must generate predictions during user interaction.
You need to consume the AI model natively.
What should you do?
Answer: A
Explanation:
The existing AI Builder classification model should be invoked from the canvas app through Power Fx. The maker adds the model as an app data source or AI capability and calls its prediction operation from the relevant user action, passing the current image. The returned classification and confidence can then be stored in variables, displayed to the user, or written to Dataverse. A static formula cannot reproduce a trained image model's inference. Refining the model with additional images is a training-lifecycle task and may improve quality later, but it does not consume the existing model during the current interaction. Exporting the containing solution transports components between environments; it does not execute a prediction. The app formula should validate that an image is present, handle service errors, and define what happens when confidence is below the accepted threshold. The Study Guide contains the exact objective "consume an AI model in apps." Option A is the native runtime integration that classifies each user-submitted image during the active canvas-app session.
Study Guide reference/topic: "Create prompts and models in AI Hub - Consume an AI model in apps." AB-
410 Study Guide | Microsoft Learn technical reference
NEW QUESTION # 65
A company creates an AI assistant that generates marketing content. Business users complain that responses vary significantly between identical requests. Which parameter should be adjusted?
Answer: D
Explanation:
Temperature controls randomness in generative AI output. Lower temperature values typically produce more consistent and predictable responses, while higher values increase creativity and variation. Storage, networking, and authentication settings do not influence model generation behavior. Adjusting temperature is a common method for controlling response consistency.
NEW QUESTION # 66
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