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| Section | Weight | Objectives |
|---|---|---|
| Design AI-powered business solutions | 25–30% | - Orchestrate configuration
|
| Deploy AI-powered business solutions | 40–45% | - Design ALM processes
|
| Plan AI-powered business solutions | 25–30% | - Analyze requirements for AI-powered business solutions
|
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NEW QUESTION # 13
A company has a Microsoft Foundry agent that summarizes customer feedback and recommends products to customers. The agent references data from multiple knowledge sources.
Users report that the agent response time is slow.
Telemetry data shows that the agent frequently reaches its token usage limit You need to recommend a solution to reduce token usage without degrading the quality of the generated responses.
What should you recommend?
Answer: C
Explanation:
The problem is not just that the agent is slow. The telemetry specifically says it frequently reaches its token usage limit. That means too much content is being pulled into the prompt or context window before the model generates the answer.
The best recommendation is D. Reconfigure the prompts to limit the amount of retrieved content from the knowledge sources.
Why D is correct:
It directly targets the root cause: too many tokens from retrieved context It reduces unnecessary context while still keeping the most relevant information It helps preserve response quality better than simply cutting capabilities or hard-limiting output size Why the other options are less suitable:
A). Chunk documents during indexing can improve retrieval quality in some RAG scenarios, but it does not directly guarantee lower total retrieved token volume in the final prompt B). Lower the maximum token usage limit for the responses may reduce output length, but it does not solve excessive input-context usage and can hurt response quality C). Reduce the number of knowledge sources used by the agent is too blunt and may remove useful grounding unnecessarily
NEW QUESTION # 14
A company extends Copilot in Microsoft Dynamics 365 Customer Service.
You need to recommend an automated application lifecycle management (ALM) process so that the Copilot components can be safely developed, tested, and promoted to production.
Which two actions should you include in the ALM process? Each correct answer presents part of the solution.
NOTE: Each correct selection is worth one point.
Answer: B,D
Explanation:
Comprehensive and Detailed Explanation From Agentic AI Business Solutions Topics:
The correct answers are C. Use Microsoft Power Platform pipelines and D. Include the components in a solution .
This question is about implementing a proper ALM process for Copilot components in Microsoft Dynamics
365 Customer Service so they can be:
* developed safely
* tested consistently
* promoted to production in a controlled way
That directly aligns with standard Power Platform ALM practices.
Why D. Include the components in a solution is correct
In Power Platform and Copilot-related environments, components should be packaged into a solution so they can be managed and transported across environments in a structured way.
Including the components in a solution enables:
* dependency tracking
* packaging of related assets together
* environment-to-environment movement
* better governance and change control
* cleaner release management
From a business solutions architecture perspective, this is foundational. Without solutions, Copilot components are much harder to move consistently and govern properly across dev, test, and production.
Why C. Use Microsoft Power Platform pipelines is correct
Once the components are organized into a solution, Microsoft Power Platform pipelines provide the automated mechanism to promote them across environments.
Pipelines help with:
* standardized deployments
* safe promotion from development to test to production
* reduced manual deployment errors
* traceability of releases
* repeatable and governed ALM execution
This is exactly what the question is asking for: an automated ALM process .
From an agentic AI business solutions perspective, automation in deployment is especially important because Copilot components can influence business workflows, customer interactions, and service operations. That means changes must be promoted in a disciplined and auditable way.
Why the other options are incorrect
A). Use an unmanaged solution in production
This is not recommended as a best practice for controlled enterprise production ALM. Production deployments should be governed and managed carefully, and unmanaged solutions are not the preferred pattern for that.
B). Rebuild the agents in each environment
This is inefficient, error-prone, and not an ALM best practice. It destroys consistency and traceability because each environment may end up with slight differences.
E). Store the agent transcripts in source control
Transcripts may be useful for analysis or audit in some contexts, but they are not a core ALM action for safely developing, testing, and promoting Copilot components.
Expert reasoning
For Microsoft business application ALM questions, the best-practice pattern is usually:
* package artifacts in a solution
* move them with Power Platform pipelines
That gives the cleanest answer for automated, governed promotion across environments.
NEW QUESTION # 15
A company has an AI business solution.
You need to extend the solution so that Microsoft 365 Copilot can invoke external logic hosted in Azure services.
What should you include in the solution?
Answer: C
Explanation:
To enhance an AI business solution with Microsoft 365 Copilot and integrate external logic hosted in Azure, you should use Copilot Studio to create Actions. These actions act as plugins that allow Copilot to invoke external services through Power Platform components.
Implementation Strategy
Azure Logic Hosting: Host your external logic in Azure using services like Azure Functions or Azure Logic Apps. These provide the API endpoints that Copilot will ultimately call.
*-> Power Platform Connector: Create a Custom Connector in the Power Platform to wrap your Azure service's API. This connector acts as the bridge, translating Copilot's requests into API calls your Azure logic understands.
Copilot Studio Integration: Within Microsoft Copilot Studio, add the custom connector as a Tool or Action. This makes the logic discoverable and invokable by Microsoft 365 Copilot.
Deployment: Deploy the action through the Microsoft 365 admin center under Integrated Apps to make it available to users in Teams or other Microsoft 365 apps.
Key Components
*-> Connector: Wraps the Azure API using an OpenAPI definition or Postman collection.
Plugin/Action: Defines how Copilot identifies when to use the connector based on user prompts.
Authentication: Ensure the connector is configured with appropriate security (e.g., OAuth 2.0) to safely access your Azure resources.
Reference:
https://learn.microsoft.com/en-us/copilot/security/connector-logicapp
NEW QUESTION # 16
A company uses Microsoft 365 and Dynamics 365
You need to recommend a solution lo automatically summarize email threads, generate suggested replies in Microsoft Outlook and provide meeting preparation summaries that include relevant customer relationship management (CRM) data.
Solution: You recommend a classic Microsoft Dataverse workflow.
Does this meet the goal?
Answer: A
NEW QUESTION # 17
A company has a customer order system that creates sales orders manually.
You need to design an AI solution to automate the following tasks as part of the system:
- Save the order details to a database.
- Update the order status in the database.
- Extract the order details from an order file.
- Prepare and send a confirmation email to customers.
The solution must minimize development effort and support intelligent automation and solution integration.
What should you include in the design?
Answer: D
Explanation:
To create this system, you'll need to integrate Microsoft Copilot Studio with Power Automate and AI Builder. This combination allows your agent to not only "talk" but also "act" by executing complex backend workflows.
Solution Architecture
Front-end: A Copilot Studio agent serves as the interface, receiving order requests or files from customers.
Brain (Logic): Power Automate cloud flows act as the "skills" for your agent, handling all database and email operations.
Data Extraction: AI Builder (Document Processing) extracts specific fields (like Item ID, Quantity, or Customer Name) from uploaded order files.
Storage: Microsoft Dataverse or SQL Server functions as the database to save and update order records.
Reference:
https://medium.com/@sushmita.sg/build-an-ai-powered-customer-support-system-in-2-hours-no- code-using-microsoft-copilot-2e3275dbbee5
NEW QUESTION # 18
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