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NEW QUESTION # 113
What should an AI Specialist consider when using related list merge fields in a prompt template associated with an Account object in Prompt Builder?
Answer: C
Explanation:
When using related list merge fields in a prompt template associated with the Account object inPrompt Builder, theActivities related listis not supported due to it being apolymorphic field. Polymorphic fields can reference multiple different types of objects, which makes them incompatible with some merge field operations in prompt generation.
* Option Bis incorrect because person accounts do not limit the availability of merge fields for the Account object.
* Option Cis irrelevant since even if no related lists are available at runtime, the prompt can still generate based on other available data fields.
For more information, refer toSalesforce documentationon supported fields and limitations inPrompt Builder.
NEW QUESTION # 114
Universal Containers (UC) recently rolled out Einstein Generative capabilities and has created a custom prompt to summarize case records. Users have reported that the case summaries generated are not returning the appropriate information.
What is a possible explanation for the poor prompt performance?
Answer: C
Explanation:
Poor prompt performance when generating case summaries is often due to the data used forgroundingbeing incorrect or incomplete. Grounding involves feeding accurate, relevant data to the AI so it can generate appropriate outputs. If the data source is incomplete or contains errors, the generated summaries will reflect that by being inaccurate or insufficient.
* Option B(prompt template incompatibility with the LLM) is unlikely because such incompatibility usually results in more technical failures, not poor content quality.
* Option C(Einstein Trust Layer misconfiguration) is focused on data security and auditing, not the quality of prompt responses.
For more information, refer toSalesforce documentation on grounding AI modelsand data quality best practices.
NEW QUESTION # 115
The sales team at a hotel resort would like to generate a guest summary about the guests' interests and provide recommendations based on their activity preferences captured in each guest profile. They want the summary to be available only on the contact record page.
Which AI capability should the team use?
Answer: C
Explanation:
The sales team at a hotel resort wants to generate a guest summary about guests' interests and provide recommendations based on their activity preferences captured in each guest profile. They require the summary to be available only on the contact record page.
Solution:
Use Prompt Builder to create a prompt template that generates the desired summary and displays it on the contact record page.
Prompt Builder:
Purpose: Allows the creation of custom prompt templates that leverage AI to generate content based on Salesforce data.
Functionality:
Field Generation Templates: Can be used to populate fields on records with AI-generated summaries.
Customization: Enables the AI Specialist to design prompts that utilize data from the guest profiles to produce personalized summaries and recommendations.
Relevance to the Use Case:
The sales team wants the summary to be available on the contact record page, which aligns with the capabilities of Prompt Builder to generate and display content on specific record pages.
Implementation Steps:
Create a Field Generation Prompt Template:
Use Prompt Builder to create a new prompt template of type Field Generation.
Design the prompt to instruct the AI to generate a summary based on the guest's interests and activity preferences.
Include Relevant Data:
Use merge fields to include data from the guest profile in the prompt.
Ensure that the prompt accesses the necessary fields to generate accurate recommendations.
Configure the Contact Page Layout:
Add the field that will display the AI-generated summary to the contact record page layout.
Ensure that the field is only visible where appropriate, adhering to the requirement of availability only on the contact record page.
Why Not Einstein Copilot or Model Builder:
Option A (Einstein Copilot):
Purpose: Einstein Copilot is a conversational AI assistant designed to interact with users through natural language.
Mismatch with Requirements:
The team wants a static summary displayed on the contact record page, not an interactive conversational experience.
Option C (Model Builder):
Purpose: Model Builder is used to create custom AI models for predictions and classifications.
Inapplicability:
Building a custom model is unnecessary for generating text summaries based on existing data.
Model Builder does not directly provide functionality to generate and display summaries on record pages.
Reference:
Salesforce AI Specialist Documentation - Prompt Builder Overview:
Provides an introduction to Prompt Builder and its capabilities.
Salesforce Help - Creating Field Generation Prompt Templates:
Guides on creating prompt templates that generate content for fields on records.
Salesforce Trailhead - Customize AI Content with Prompt Builder:
Offers hands-on experience in building and customizing prompt templates.
Conclusion:
By utilizing Prompt Builder, the sales team can create a customized prompt template that generates personalized guest summaries and recommendations based on activity preferences. This solution meets the requirement of displaying the summary only on the contact record page, enhancing the team's ability to engage with guests effectively.
NEW QUESTION # 116
An AI Specialist at Universal Containers (UC) Is tasked with creating a new custom prompt template to populate a field with generated output. UC enabled the Einstein Trust Layer to ensure AI Audit data is captured and monitored for adoption and possible enhancements.
Which prompt template type should the AI Specialist use and which consideration should they review?
Answer: A
Explanation:
When creating acustom prompt templateto populate a field with generated output, the most appropriate template type isField Generation. This template is specifically designed for generating field-specific outputs using generative AI.
Additionally, the AI Specialist must ensure thatDynamic Fieldsare enabled.Dynamic Fieldsallow the system to use real-time data inputs from related records or fields when generating content, ensuring that the AI output is contextually accurate and relevant. This is crucial when populating specific fields with AI-generated content, as it ensures the data source remains dynamic and up-to-date.
TheEinstein Trust Layerwill track and audit the interactions to ensure the organization can monitor AI adoption and make necessary enhancements based on AI usage patterns.
For further reading, refer to Salesforce's guidelines onField Generation templatesand theEinstein Trust Layer.
NEW QUESTION # 117
Universal Containers has a strict change management process that requires all possible configuration to be completed in a sandbox which will be deployed to production. The AI Specialist is tasked with setting up Work Summaries for Enhanced Messaging. Einstein Generative AI is already enabled in production, and the Einstein Work Summaries permission set is already available in production.
Which other configuration steps should the AI Specialist take in the sandbox that can be deployed to the production org?
Answer: A
Explanation:
* Context of the Question
* Universal Containers (UC) has a strict change management process that requires all possible configuration be completed in a sandbox and deployed to Production.
* Einstein Generative AI is already enabled in Production, and the "Einstein Work Summaries" permission set is already available in Production.
* The AI Specialist needs to configureWork Summaries for Enhanced Messagingin the sandbox.
* What Can Actually Be Deployed from Sandbox to Production?
* Custom Fields: Metadata that is easily created in sandbox and then deployed.
* Quick Actions: Also metadata-based and can be deployed from sandbox to production.
* Layout Components: Page layout changes (such as adding the Wrap Up component) can be added to a change set or deployment package.
* Why Option C is Correct
* No Need to Turn on Einstein in Sandbox for Deployment: Einstein Generative AI is already enabled in Production; turning it on in the sandbox is typically a manual step if you want to test, but that step itself is not "deployable" in the sense of metadata.
* Permission Set Assignments(as in Option A) are not deployable metadata. You can deploy the Permission Set itself but not the specific user assignments. Since the question specifically asks
"Which other configuration steps should be takenin the sandboxthatcanbe deployed to the production org?", user assignment is not one of them.
* Why Not Option A or B?
* Option A: Mentions creating permission set assignments for agents. This cannot be directly deployed from sandbox to Production, as permission set assignments are user-specific and considered "data," not metadata.
* Option B: Mentions "Turn on Einstein." But Einstein Generative AI is already enabled in Production. Additionally, "Turning on Einstein" is typically an org-level setting, not a deployable metadata item.
* ConclusionThe main deployable items you can reliably create and test in a sandbox, and then migrate to Production, are:
* Custom Fields(Issue, Resolution, Summary).
* A Quick Actionthat updates those fields.
* Page Layout Changeto include the Wrap Up component.
Therefore,Option Cis correct and focuses on actions that are truly deployable as metadata from a sandbox to Production.
Salesforce AI Specialist References & Documents
* Salesforce Trailhead:Work Summaries with Einstein GPTProvides an overview of how to configure Work Summaries, including the need for custom fields, quick actions, and UI components.
* Salesforce Documentation:Deploying Metadata Between OrgsExplains what can and cannot be deployed via change sets (e.g., custom fields, page layouts, quick actions vs. user permission set assignments).
* Salesforce AI Specialist Study GuideOutlines which Einstein Generative AI and Work Summaries configurations are deployable as metadata.
NEW QUESTION # 118
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