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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Create a foundation for intelligent applications | 25-30% | - Design Microsoft Power Platform solutions using AI-enabled tools
|
| Topic 2: Create intelligent applications | 25-30% | - Create model-driven apps
|
| Topic 3: Build business application logic and automation | 40-45% | - Business logic
|
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NEW QUESTION # 19
A company wants to reduce the cost of calling a large language model while maintaining acceptable response quality for simple requests. Which strategy should be considered?
Answer: C
Explanation:
Using smaller or specialized models for simpler tasks can reduce inference costs while maintaining acceptable performance. Large models should be reserved for complex reasoning scenarios. Increasing token usage and duplicate requests increase expenses. Effective AI architecture uses workload classification and selects appropriate models based on business requirements.
NEW QUESTION # 20
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 integrate with an internal web service that is used across multiple flows and requires reusable actions .
Does the solution meet the goal?
Answer: B
Explanation:
This is an appropriate custom connector use case. The internal web service is a proprietary API and its actions must be reused across multiple flows. A custom connector centralizes the service's host, authentication, paths, parameters, request bodies, and response schemas and exposes each operation as a named Power Automate action. Makers can then use a consistent contract rather than rebuilding raw HTTP requests with different headers or payloads in every flow. The connector can be defined from an OpenAPI document or configured manually and should be packaged in a solution with connection references. If the service is reachable only on a private network, an on-premises data gateway or approved network architecture may also be required. Data loss prevention policies should classify the connector appropriately, and changes to the API should be versioned and regression-tested against dependent flows. The Study Guide explicitly measures the ability to
"evaluate and recommend connectors." The combination of a nonstandard internal service and reusable operations is precisely the situation in which the managed abstraction of a custom connector is justified. The answer is Yes.
Study Guide reference/topic: "Create cloud flows - Evaluate and recommend connectors." AB-410 Study Guide | Microsoft Learn technical reference
NEW QUESTION # 21
Hotspot Question
A company runs Power Automate cloud flows in production.
You observe many duplicate executions and 401 error codes when you review the flow runs.
You need to resolve the errors.
How should you address each error? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
Box 1: Reauthenticate connection
A 401 (Unauthorized) error in production typically means a connection's authentication token is expired, the account lacks permissions, or a password change invalidated the OAuth token. To restore the flow, fix the underlying connection.
How to Fix Authentication Failures
1. Check Run History: In the Power Automate Run History, open the failed flow run to identify exactly which action is returning the 401 error.
*-> 2. Re-authenticate the Connection
Box 2: Enable concurrency control
To fix duplicate executions in production Power Automate cloud flows, you should Enable concurrency control and set the limit to 1.
The Root Cause: Duplicate executions usually happen when an upstream system sends multiple rapid requests, or a trigger fires twice before the first run finishes.
The Solution: Enabling concurrency control with a limit of 1 forces the flow to process only one run at a time. Subsequent triggers are queued up orderly, preventing overlapping actions and race conditions.
Reference:
https://learn.microsoft.com/en-us/troubleshoot/power-platform/power-automate/flow-run-issues/triggers-troubleshoot
NEW QUESTION # 22
A developer wants a generative AI application to consistently return responses in a structured format that another application can process automatically. Which technique should be applied?
Answer: B
Explanation:
Prompt engineering can define expected response formats, including JSON structures, fields, and formatting requirements. This improves interoperability between AI-generated responses and downstream applications. Increasing randomness reduces consistency, while removing instructions weakens model behavior control. Validation logic should complement AI output processing rather than being disabled.
NEW QUESTION # 23
A company is designing an AI-enabled solution to help employees review and evaluate customer requests.
The company requires an AI summary to be generated at runtime by using instructions provided by the company, including tone, structure, and required data fields. The Prompt control will use these instructions on Power Apps forms across multiple tables.
You need to store the instructions.
Which component should you use?
Answer: A
Explanation:
To achieve a reusable, multi-table runtime AI summarization tool, you must use Custom AI Prompts configured via the AI Prompt Builder and stored in Microsoft Dataverse.
You should use AI Builder Prompt builder in the Microsoft Power Platform. It perfectly meets your requirements to create, store, and dynamically process instructions across multiple Power Apps tables and forms.
Prompt builder: Use this capability in the Power Apps Maker portal to draft, test, and save custom instructions for the AI. You can explicitly dictate the tone, structure, and required data fields within the prompt.
'Dynamic Values & Input Variables: Add dynamic input fields to your prompts so they ingest contextual data from different Dataverse tables and form controls.
Solution Lifecycle Management: The stored prompts are "solution-aware" components. They are saved directly in your environment and can be easily deployed and reused across different applications and tables.
Power Fx Integration: Trigger the AI summary at runtime by using Power Fx formulas to invoke your saved prompt. For example, on a button press, you would execute the formula:
Set(aiSummary, YourSavedPrompt.Predict(TextInput1.Text)).
Reference:
https://learn.microsoft.com/en-us/power-platform/release-plan/2025wave1/ai-builder/prompt-builder
NEW QUESTION # 24
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