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Microsoft AB-410 Exam Syllabus Topics:

SectionObjectives
Governance and application lifecycle management- Responsible AI and ALM
  • 1. Manage application lifecycle and deployment
  • 2. Apply governance and security controls
  • 3. Implement responsible AI practices
Implement automation and orchestration- Process automation
  • 1. Automate business workflows
  • 2. Coordinate apps, agents, and AI models
Design intelligent applications with Copilot and natural language- AI-first application design
  • 1. Use Copilot capabilities to design solutions
  • 2. Leverage natural language experiences in application development
Embed agents and AI experiences- Agent integration
  • 1. Build agent-first user experiences
  • 2. Embed Copilot Studio agents into applications
Build intelligent applications on Microsoft Power Platform- Application development
  • 1. Integrate AI models into applications
  • 2. Create AI-powered business applications

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Microsoft Building Intelligent Applications Sample Questions (Q109-Q114):

NEW QUESTION # 109
A company is building a prompt about product specifications. The company plans to use the prompt in Power Automate.
The prompt must use Retrieval-Augmented Generation to ground the model with additional business information.
You need to select the available knowledge source for the prompt.
What should you use?

Answer: C

Explanation:
Dataverse table columns are the appropriate knowledge source for a prompt that must use Retrieval- Augmented Generation with current business information. Grounding the prompt with selected Dataverse data allows the model to incorporate governed product specifications at runtime instead of relying only on its pretrained knowledge. The maker can identify the relevant table and columns and then pass or retrieve the business context required by the prompt. A PNG image is an input artifact, not the structured knowledge source needed for specification retrieval. Plain text can provide fixed instructions or context but does not create a maintained enterprise data source. A PDF can be useful in other grounding experiences, but under the available prompt knowledge options in this scenario, the Dataverse table provides the direct, structured, updateable source. Access remains subject to environment and table security, so only approved data should be exposed to the prompt. The AB-410 Study Guide explicitly measures the ability to "add knowledge to a prompt." Selecting Dataverse table columns implements that objective while minimizing duplication of product data.
Study Guide reference/topic: "Create prompts and models in AI Hub - Add knowledge to a prompt." AB-
410 Study Guide | Microsoft Learn technical reference


NEW QUESTION # 110
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: C

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 # 111
A company uses a model driven app that has multiple forms and system views for the same table. You must restrict specific users from accessing:
* A specific form
* A specific system view
You need to configure the access restrictions.
How should you complete the configurations? To answer, move the appropriate configurations to the correct requirements. You may use each configuration once, more than once, or not at all You may need to move the split bar between panes or scroll to view content.
NOTE: Each correct selection is worth one point.

Answer:

Explanation:

Explanation:
Specific form: Assign security roles. Specific system view: Assign security roles.

Main forms can be associated with one or more security roles so that only users holding those roles can select or receive the form. At least one fallback form must remain available to users who have no explicitly assigned form. Current model-driven app functionality also permits eligible nondefault public system views to be managed by security role. After role-based system views are enabled, the maker opens View settings, selects Specific security roles, and publishes the assignment. Web roles apply to Power Pages, not model-driven apps. Table relationships define data structure, and table-level permissions govern data access rather than the availability of one form or view. Because hiding a form or view does not protect the underlying data, sensitive records and columns still require appropriate Dataverse security privileges. Role assignments should be tested with real nonadministrative accounts before release. Microsoft separately documents security-role assignments for model-driven forms and public system views, supporting the same configuration choice for both requirements.
Reference: https://learn.microsoft.com/en-us/power-apps/maker/model-driven-apps/control-access-forms Study Guide alignment: Create intelligent applications.


NEW QUESTION # 112
Case Study 2 - Fabrikam Inc
Background
Fabrikam Inc. is an energy provider that operates wind and solar farms across multiple countries and regions. The company uses Microsoft Power Platform to manage asset maintenance, technician workflows, and predictive analytics.
Field technicians use canvas apps on mobile devices to capture inspection and repair data.
Operations managers use model-driven apps to monitor asset performance and maintenance history.
The company plans to enhance its platform by introducing AI-driven insights, improving reuse across applications, and establishing a formal application lifecycle management (ALM) strategy.
Current environment
Applications
Field technicians use an outdated mobile app to log maintenance activities and capture asset readings in SharePoint Online.
Operations managers use a model-driven app to review maintenance records and asset performance trends.
Development practices
Developers build and modify applications directly in the production environment.
There is NO structured ALM process.
Solutions are NOT consistently used to package or deploy application components.
Reusable components are inconsistently implemented across apps, leading to duplication.
AI integration
Fabrikam Inc. plans to actively explore generative AI usage as part of the next phase of work.
Business requirement
Application development
The outdated mobile app must be replaced with a new app that supports responsive design principles, provides full control over the UI, and allows technicians to take and upload photos directly from their mobile devices.
The new app for the field technicians requires the name of the technician to be persisted on the home screen only. In addition, work orders must be displayed within a gallery.
All new apps must connect to a scalable, cloud-based relational data store.
Apps must support efficient data entry for technicians in the field.
Reusable UI elements must be implemented to reduce duplication.
AI capabilities
The company requires a generative AI solution to manage customer complaint responses and create custom inspection reports that align to an existing template.
Customer complaint responses must be generated in applications and based on emails being sent to a mailbox.
Custom AI development must be minimized.
Generative AI reusability
Generative AI solutions must accept dynamic inputs to adapt to different scenarios.
Generative AI solutions must be reusable across different Power Platform services.
Extensibility
Custom UI form components must be reusable across applications.
Use of server-side custom code must be minimized where possible.
Technical requirements
Application lifecycle management (ALM)
Separate environments must be used for development, testing, and production.
Solutions must be used to package application components, segmented based on functional areas.
Managed solutions must be deployed to the production environment.
Validation must occur before deployment to production.
Data processing
Aggregated values across related rows must be displayed for reporting.
Calculations must update automatically as new data is entered. Calculation data must be limited to a maximum length of 10.
Issues
Duplicate logic exists across multiple canvas apps.
Developers frequently overwrite changes in production.
Generative AI solutions produce inconsistent outputs due to missing or inconsistent inputs.
Maintenance metrics are not consistently calculated across related rows.
You need to provide a solution for field technicians to create custom inspection reports natively within the new app. What should you do?

Answer: A

Explanation:
Scenario: The company requires a generative AI solution to manage customer complaint responses and create custom inspection reports that align to an existing template.
You should use a custom prompt.
Generative AI Capability: Power Platform AI Builder prompts leverage large language models (like GPT) to natively handle generative text workflows.
Complaint Handling: A custom prompt can be built specifically to analyze customer feedback and automatically generate draft email or text responses.
Template Alignment: You can embed your exact inspection report layout and instructions directly inside the custom prompt's logic. This ensures that the generated outputs perfectly match the structure of your existing template.
Reference:
https://learn.microsoft.com/en-us/ai-builder/overview


NEW QUESTION # 113
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 retrieve data from SharePoint Online lists.
Does the solution meet the goal?

Answer: A

Explanation:
Correct:
* A cloud flow must integrate with an internal web service that is used across multiple flows and requires reusable actions.
This scenario requires a custom connector. Because it is a proprietary or internal service, Microsoft does not provide a pre-built native bridge. Building a Microsoft Custom Connector wraps the web service's REST/SOAP API into a reusable tool, eliminating the need to repeatedly configure HTTP headers and endpoints across separate flows.
Incorrect:
* A cloud flow must call a REST API by using a one-time HTTP action without reuse across flows.
A custom connector is not necessary here. For single-use or non-reusable integrations, using a generic built-in HTTP action step is the most efficient and fastest choice.
* A cloud flow must retrieve data from Microsoft Dataverse.
Power Automate includes a native, out-of-the-box Microsoft Dataverse connector. There is no need to develop a custom connector for default Power Platform data storage.
* A cloud flow must retrieve data from SharePoint Online lists.
SharePoint Online is fully supported by native Microsoft 365 integrations. You should use the pre- built SharePoint connector instead of creating a custom wrapper.
Reference:
https://alphavima.com/blog/power-apps-custom-connector-rest-api/


NEW QUESTION # 114
......

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