QUESTION: 53

Universal Containers (UC) wants to enable its sales team to use AI to suggest recommended products from its catalog.
Which type of prompt template should UC use?

Record summary prompt template
Email generation prompt template
Flex prompt template

Answer(s): C

Explanation:

UC needs an AI solution to suggest products from a catalog for its sales team. Let's assess the prompt template types in Prompt Builder.

Option A: Record summary prompt template

Record summary templates generate concise summaries of records (e.g., Case, Opportunity). They're not designed for product recommendations, which require dynamic logic beyond summarization, making this incorrect.

Option B: Email generation prompt template

Email generation templates craft emails (e.g., customer outreach).
While they could mention products, they're not optimized for standalone recommendations, making this incorrect.

Option C: Flex prompt template

Flex prompt templates are versatile, allowing custom inputs (e.g., catalog data from objects or Data Cloud) and instructions (e.g., "Suggest products based on customer preferences"). This flexibility suits UC's need to recommend products dynamically, making it the correct answer.

Why Option C is Correct:

Flex templates offer the customization needed to suggest products from a catalog, aligning with Salesforce's guidance for tailored AI outputs.

Reference:

Salesforce Agentforce Documentation: Prompt Builder > Flex Templates Details dynamic use cases.

Trailhead: Build Prompt Templates in Agentforce Covers Flex for custom scenarios.

Salesforce Help: Prompt Template Types Confirms Flex versatility.

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QUESTION: 54

A data scientist needs to view and manage models in Einstein Studio, and also needs to create prompt templates in Prompt Builder.
Which permission sets should an Agentforce Specialist assign to the data scientist?

Prompt Template Manager and Prompt Template User
Data Cloud Admin and Prompt Template Manager
Prompt Template User and Data Cloud Admin

Answer(s): B

Explanation:

The data scientist requires permissions for Einstein Studio (model management) and Prompt Builder (template creation).
Note: "Einstein Studio" may be a misnomer for Data Cloud's model management or a related tool, but we'll interpret based on context. Let's evaluate.

Option A: Prompt Template Manager and Prompt Template User

There's no distinct "Prompt Template Manager" or "Prompt Template User" permission set in Salesforce--Prompt Builder access is typically via "Einstein Generative AI User" or similar. This option lacks coverage for Einstein Studio/Data Cloud, making it incorrect.

Option B: Data Cloud Admin and Prompt Template Manager

The "Data Cloud Admin" permission set grants access to manage models in Data Cloud (assumed as Einstein Studio's context), including viewing and editing AI models. "Prompt Template Manager" isn't a real set, but Prompt Builder creation is covered by "Einstein Generative AI Admin" or similar admin-level access (assumed intent). This combination approximates the needs, making it the closest correct answer despite naming ambiguity.

Option C: Prompt Template User and Data Cloud Admin

"Prompt Template User" isn't a standard set, and user-level access (e.g., Einstein Generative AI User) typically allows execution, not creation. The data scientist needs to create templates, so this lacks sufficient Prompt Builder rights, making it incorrect.

Why Option B is Correct (with Caveat):

"Data Cloud Admin" covers model management in Data Cloud (likely intended as Einstein Studio), and "Prompt Template Manager" is interpreted as admin-level Prompt Builder access (e.g., Einstein Generative AI Admin). Despite naming inconsistencies, this fits the requirements per Salesforce permissions structure.

Reference:

Salesforce Data Cloud Documentation: Permissions Details Data Cloud Admin for models.

Trailhead: Set Up Einstein Generative AI Covers Prompt Builder admin access.

Salesforce Help: Agentforce Permission Sets Aligns with admin-level needs.

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QUESTION: 55

Universal Containers wants to leverage the Record Snapshots grounding feature in a prompt template.
What preparations are required?

Configure page layout of the master record type.
Create a field set for all the fields to be grounded.
Enable and configure dynamic form for the object.

Answer(s): B

Explanation:

Universal Containers (UC) aims to use Record Snapshots grounding in a prompt template to provide context from a specific record. Let's evaluate the preparation steps.

Option A: Configure page layout of the master record type.

While page layouts define field visibility for users, Record Snapshots grounding relies on field accessibility at the object level, not the layout. The AI accesses data based on permissions and configuration, not layout alone, making this insufficient and incorrect.

Option B: Create a field set for all the fields to be grounded.

Record Snapshots in Prompt Builder allow grounding with fields from a record, but you must specify which fields to include. Creating a field set is a recommended preparation step--it groups the fields (e.g., from the object) to be passed to the prompt template, ensuring the AI has the right data. This is a documented best practice for controlling snapshot scope, making it the correct answer.

Option C: Enable and configure dynamic form for the object.

Dynamic Forms enhance UI flexibility but aren't required for Record Snapshots grounding. The feature pulls data directly from the object, not the form configuration, making this irrelevant and incorrect.

Why Option B is Correct:

Creating a field set ensures the prompt template uses the intended fields for grounding, a key preparation step per Salesforce documentation.

Reference:

Salesforce Agentforce Documentation: Prompt Builder > Record Snapshots Recommends field sets for grounding.

Trailhead: Ground Your Agentforce Prompts Details field set preparation.

Salesforce Help: Set Up Record Snapshots Confirms field set usage.

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QUESTION: 56

Which scenario best demonstrates when an Agentforce Data Library is most useful for improving an

AI agent's response accuracy?

When the AI agent must provide answers based on a curated set of policy documents that are stored, regularly updated, and indexed in the data library.
When the AI agent needs to combine data from disparate sources based on mutually common data, such as Customer Id and Product Id for grounding.
When data is being retrieved from Snowflake using zero-copy for vectorization and retrieval.

Answer(s): A

Explanation:

The Agentforce Data Library enhances AI accuracy by grounding responses in curated, indexed data.
Let's assess the scenarios.

Option A: When the AI agent must provide answers based on a curated set of policy documents that are stored, regularly updated, and indexed in the data library.

The Data Library is designed to store and index structured content (e.g., Knowledge articles, policy documents) for semantic search and grounding. It excels when an agent needs accurate, up-to-date responses from a managed corpus, like policy documents, ensuring relevance and reducing hallucinations. This is a prime use case per Salesforce documentation, making it the correct answer.

Option B: When the AI agent needs to combine data from disparate sources based on mutually common data, such as Customer Id and Product Id for grounding.

Combining disparate sources is more suited to Data Cloud's ingestion and harmonization capabilities, not the Data Library, which focuses on indexed content retrieval. This scenario is less aligned, making it incorrect.

Option C: When data is being retrieved from Snowflake using zero-copy for vectorization and retrieval.

Zero-copy integration with Snowflake is a Data Cloud feature, but the Data Library isn't specifically tied to this process--it's about indexed libraries, not direct external retrieval. This is a different context, making it incorrect.

Why Option A is Correct:

The Data Library shines in curated, indexed content scenarios like policy documents, improving agent accuracy, as per Salesforce guidelines.

Reference:

Salesforce Agentforce Documentation: Data Library > Use Cases Highlights curated content grounding.

Trailhead: Ground Your Agentforce Prompts Describes Data Library accuracy benefits.

Salesforce Help: Agentforce Data Library Confirms policy document scenario.

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