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| Section | Objectives |
|---|---|
| Governance and application lifecycle management | - Responsible AI and ALM
|
| Design intelligent applications with Copilot and natural language | - AI-first application design
|
| Build intelligent applications on Microsoft Power Platform | - Application development
|
| Embed agents and AI experiences | - Agent integration
|
| Implement automation and orchestration | - Process automation
|
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NEW QUESTION # 40
A company is building prompts in Microsoft Copilot Studio to support multiple customer service scenarios.
The company requires prompts to:
# Follow a consistent structure across use cases.
# Be reusable across multiple topics.
# Allow customization for different types of customer requests.
You need to build the prompts.
What should you do?
Answer: A
Explanation:
The maker should select an appropriate template from the prompt library and customize it for each scenario.
Templates provide a consistent starting structure and established prompt pattern while still allowing the instructions, inputs, grounding, and expected output to be adapted to a particular customer request. This balances standardization with scenario-level variation. Model settings influence behavior such as creativity or moderation, but they do not create a reusable prompt structure. Storing prompt text in ordinary topic variables duplicates unmanaged text and does not provide a governed prompt component with its own inputs and lifecycle. Creating unrelated prompts directly inside every topic would repeat structure and make maintenance inconsistent. Customized prompt components should be named clearly, added to solutions, tested against representative inputs, and versioned through ALM. Shared instructions can be kept consistent while scenario- specific requirements remain explicit. The AB-410 Study Guide contains the exact objective "build prompts from templates or from blank." Option D uses the template path for consistency and then applies the customization required for multiple service scenarios.
Study Guide reference/topic: "Create prompts and models in AI Hub - Build prompts from templates." AB-
410 Study Guide | Microsoft Learn technical reference
NEW QUESTION # 41
A company wants an AI system to analyze customer reviews and determine whether opinions are positive, negative, or neutral. Which Azure AI capability is most appropriate?
Answer: C
Explanation:
Sentiment analysis is a natural language processing capability used to determine emotional tone within text. It can classify opinions and provide confidence scores. Object detection analyzes images, speech synthesis generates audio, and document conversion changes formats. Review analysis is a common business scenario for sentiment analysis.
NEW QUESTION # 42
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: C,D
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 # 43
A company uses Dataverse to configure derived values for sales records.
The company requires the following functionality:
- Evaluate an expression by using numerical columns in the same row.
- Calculate the result dynamically when accessed.
- Ensure the result is NOT stored as part of the table data.
- The solution must minimize use of custom code.
You need to configure the app.
What should you do?
Answer: B
Explanation:
The best option to use is a calculated column (or its modern equivalent, a formula column).
Why?
Evaluates expressions in the same row: Calculated and formula columns natively execute calculations using other numerical columns belonging to the exact same row.
Calculates dynamically when accessed: Calculations are performed on-the-fly and evaluated in real-time when the data is read or displayed.
Not stored in table data: Because the value is dynamically generated at the database or query level whenever requested, it does not permanently occupy physical table data storage.
Minimizes custom code: These are out-of-the-box, low-code configurations inside Microsoft Dataverse utilizing simple Excel-like or Power Fx formulas.
Reference:
https://learn.microsoft.com/en-us/power-apps/maker/data-platform/types-of-fields
NEW QUESTION # 44
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: D
Explanation:
To natively consume an AI Builder model and generate predictions during user interaction using Power Fx, you must use the Predict function.
Reference:
https://learn.microsoft.com/en-us/ai-builder/use-in-powerapps-overview
NEW QUESTION # 45
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