Most Recent Salesforce-AI-Specialist Exam Dumps

In order to access and create custom prompt templates in Prompt Builder, the AI Specialist must have the Prompt Template Manager permission set assigned. Without this permission, they will not be able to access Prompt Builder in the Setup menu, even though Einstein Generative AI is enabled.

Option B is correct because the Prompt Template Manager permission set is required to use Prompt Builder.

Option A (Prompt Template User permission set) is incorrect because this permission allows users to use prompts, but not create or manage them.

Option C (LLM configuration in Data Cloud) is unrelated to the ability to access Prompt Builder.

Salesforce Prompt Builder Permissions: https://help.salesforce.com/s/articleView?id=sf.prompt_builder_permissions.htm

An AI Specialist wants to include data from the response of an external service invocation (REST API callout) into a prompt template. The goal is to incorporate dynamic data retrieved from an external API into the AI-generated content.

Solution:

Use External Service Record Merge Fields

External Service Integration:

Definition: External Services in Salesforce allow the integration of external REST APIs into Salesforce without custom code.

Registration: The external service must be registered in Salesforce, defining the API's schema and methods.

External Service Record Merge Fields:

Purpose: Enables the inclusion of data from external service responses directly into prompt templates using merge fields.

Functionality:

Dynamic Data Inclusion: Allows prompt templates to access and use data returned from REST API callouts.

Merge Fields Syntax: Use merge fields in the prompt template to reference specific data points from the API response.

Implementation Steps:

Register the External Service:

Use External Services to register the REST API in Salesforce.

Define the API's schema, including methods and data structures.

Create a Named Credential:

Configure authentication and endpoint details for the external API.

Use External Service in Flow:

Build a Flow that invokes the external service and captures the response.

Ensure the flow outputs the necessary data for use in the prompt template.

Configure the Prompt Template:

Use External Service Record merge fields in the prompt template to reference data from the flow's output.

Syntax Example: {{flowOutputVariable.fieldName}}

Why Other Options are Less Suitable:

Option A (Convert the JSON to an XML merge field):

Irrelevance: Converting JSON to XML merge fields is unnecessary and complicates the process.

Unsupported Method: Salesforce prompt templates do not support direct inclusion of XML merge fields from JSON conversion.

Option C (Use ''Add Prompt Instructions'' flow element):

Purpose of Add Prompt Instructions:

Allows adding instructions to the prompt within a flow but does not facilitate including external data.

Limitation: Does not directly help in incorporating external service responses into the prompt template.

Salesforce AI Specialist Documentation - Integrating External Services with Prompt Templates:

Explains how to use External Services and merge fields in prompt templates.

Salesforce Help - Using Merge Fields with External Data:

Provides guidance on referencing external data in templates using merge fields.

Salesforce Trailhead - External Services and Flow:

Offers a practical understanding of integrating external APIs using External Services and Flow.

Conclusion:

By using External Service Record merge fields, the AI Specialist can effectively include data from external REST API responses into prompt templates, ensuring that the AI-generated content is enriched with up-to-date and relevant external data.

To implement a solution where users enter a sales order number and the system generates a summary, the AI Specialist should create a screen flow to collect the sales order number and invoke the prompt template. The standard 'Prompt Template' flow action can then be used to trigger the custom prompt, providing a summary of the sales order header and details.

Option B, creating a template-triggered prompt flow, is not necessary for this scenario because the requirement is to directly collect input through a screen flow.

Option C, using an autolaunched flow, would be inappropriate here because the solution requires user interaction (entering a sales order number), which is best suited to a screen flow.

Salesforce AI Specialist Reference: For further guidance on creating prompt templates with flows: https://help.salesforce.com/s/articleView?id=sf.prompt_template_flow_integration.htm

In theEinstein Trust Layer, the Salesforce AI Specialist can configureprivacy data entities to be masked(Option C). This ensures sensitive or personally identifiable information (PII) is obfuscated when processed by AI models.

Data Masking Configuration:

The AI Specialist defines which fields or data types (e.g., email, phone number, Social Security Number) should be masked. For example, masking theEmailfield in a prompt response to protect user privacy.

This is done through declarative settings in Salesforce, where entities (standard or custom fields) are flagged for masking.

Why Other Options Are Incorrect:

A . Profiles exempt from masking: Exemptions are typically managed via permissions (e.g., field-level security), not directly within Einstein Trust Layer's Data Masking settings.

B . Encryption keys for masking: Encryption is separate from masking. Masking involves obfuscation (e.g., replacing 'john@example.com' with '@'), not encryption, which uses keys to secure data.

Einstein Trust Layer Documentation: States that Data Masking allows admins to 'define which fields should be masked to protect sensitive data.'

Trailhead Module: 'Einstein Trust Layer Basics' explains configuring privacy entities for masking.

Salesforce Help Article: 'Secure AI with Einstein Trust Layer' details masking configurations for privacy compliance.

TheTemperaturehyperparameter controls the randomness of model outputs:

Low Temperature (e.g., 0.2): More deterministic, consistent responses.

High Temperature (e.g., 1.0): More creative, varied responses.

Presence Penalty (Option A): Discourages repetition of tokens, unrelated to randomness.

Variability (Option B): Not a standard hyperparameter in Einstein Studio.

Einstein Studio Documentation:Model Hyperparameters

Explicitly states 'Temperature adjusts the balance between predictable and random outputs.'