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NEW QUESTION # 142
Universal Containers wants to incorporate CRM data as well-formatted JSON in a prompt to a large language model (LLM).
What is an important consideration for this requirement?
Answer: A
Explanation:
* Context of the Question
* Universal Containers (UC) wants to send well-formatted JSON data in a prompt to a large language model (LLM).
* The question is about an important technical or design consideration for including CRM data as JSON in that prompt.
* Why Apex Code for JSON Formatting?
* Apex to Generate JSON: Salesforce does not have a simple "checkbox" or single setting to
"convert CRM data to JSON." Typically, to structure data as JSON in a template, you either:
* Use an Apex class that queries or processes the data, then returns a JSON string.
* Use a Flow or formula approach (though complex data structures often require Apex).
* No Built-In "Enable JSON Format in Prompt Builder": Prompt Builder doesn't have a toggle that automatically transforms data into JSON.
* ConclusionThe practical solution to pass CRM data in JSON format to an LLM is touse Apex code(or a specialized Flow approach) to produce a JSON string, which the prompt can then merge and pass along. Hence,Option Bis correct.
Salesforce AI Specialist References & Documents
* Salesforce Documentation:Working with JSON in ApexDescribes how to serialize and deserialize data using Apex for integration or AI prompts.
* Salesforce AI Specialist Study GuideEmphasizes the need for custom logic (often in Apex) when complex data transformations (like JSON formatting) are required.
NEW QUESTION # 143
Universal Containers (UC) is implementing Einstein Generative AI to improve customer insights and interactions. UC needs audit and feedback data to be accessible for reporting purposes.
What is a consideration for this requirement?
Answer: A
Explanation:
When implementing Einstein Generative AI for improved customer insights and interactions, the Data Cloud is a key consideration for storing and managing large-scale audit and feedback data. The Salesforce Data Cloud (formerly known as Customer 360 Audiences) is designed to handle and unify massive datasets from various sources, making it ideal for storing data required for AI-powered insights and reporting. By provisioning Data Cloud, organizations like Universal Containers (UC) can gain real-time access to customer data, making it a central repository for unified reporting across various systems.
Audit and feedback data generated by Einstein Generative AI needs to be stored in a scalable and accessible environment, and the Data Cloud provides this capability, ensuring that data can be easily accessed for reporting, analytics, and further model improvement.
Custom objects or Salesforce Big Objects are not designed for the scale or the specific type of real-time, unified data processing required in such AI-driven interactions. Big Objects are more suited for archival data, whereas Data Cloud ensures more robust processing, segmentation, and analysis capabilities.
Reference:
Salesforce Data Cloud Documentation: https://www.salesforce.com/products/data-cloud/overview/ Salesforce Einstein AI Overview: https://www.salesforce.com/products/einstein/overview/
NEW QUESTION # 144
What is the role of the large language model (LLM) in understanding intent and executing an Agent Action?
Answer: B
NEW QUESTION # 145
Universal Containers has seen a high adoption rate of a new feature that uses generative AI to populate a summary field of a custom object, Competitor Analysis. All sales users have the same profile but one user cannot see the generative AlI-enabled field icon next to the summary field.
What is the most likely cause of the issue?
Answer: C
Explanation:
In Salesforce, Generative AI capabilities are controlled by specific permission sets. To use features such as generating summaries with AI, users need to have the correct permission sets that allow access to these functionalities.
* Generative AI User Permission Set: This is a key permission set required to enable the generative AI capabilities for a user. In this case, the missingGenerative AI Userpermission setprevents the user from seeing the generative AI-enabled field icon. Without this permission, the generative AI feature in the Competitor Analysis custom object won't be accessible.
* Why not A?ThePrompt Template Userpermission set relates specifically to users who need access to prompt templates for interacting with Einstein GPT, but it's not directly related to the visibility of AI- enabled field icons.
* Why not B?While a prompt template might need to be activated, this is not the primary issue here. The question states that other users with the same profile can see the icon, so the problem is more likely to be permissions-based for this particular user.
For more detailed information, you can review Salesforce documentation onpermission setsrelated to AI capabilities atSalesforce AI DocumentationandEinstein GPTpermissioning guidelines.
NEW QUESTION # 146
Universal Containers (UC) noticed an increase in customer contract cancellations in the last few months. UC is seeking ways to address this issue by implementing a proactive outreach program to customers before they cancel their contracts and is asking the Salesforce team to provide suggestions.
Which use case functionality of Model Builder aligns with UC's request?
Answer: B
Explanation:
Customer churn prediction is the best use case for Model Builder in addressing Universal Containers' concerns about increasing customer contract cancellations. By implementing a model that predicts customer churn, UC can proactively identify customers who are at risk of canceling and take action to retain them before they decide to terminate their contracts. This functionality allows the business to forecast churn probability based on historical data and initiate timely outreach programs.
Option B is correct because customer churn prediction aligns with UC's need to reduce cancellations through proactive measures.
Option A (product recommendation prediction) is unrelated to contract cancellations.
Option C (contract renewal date prediction) addresses timing but does not focus on predicting potential cancellations.
Reference:
Salesforce Model Builder Use Case Overview: https://help.salesforce.com/s/articleView?id=sf.model_builder_use_cases.htm
NEW QUESTION # 147
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