Latest Salesforce-AI-Specialist Exam Questions

B.   Use BYO-LLM functionality in Einstein Studio,

Answer DescriptionExplanation: Bring Your Own Large Language Model (BYO-LLM)functionality in Einstein Studio allows organizations to integrate and use external large language models (LLMs) within the Salesforce ecosystem. Universal Containers can leverage this feature to connect and ground prompts with external LLMs, allowing for custom AI model use cases and seamless integration with Salesforce data.
Option Bis the correct choice as Einstein Studio provides a built-in feature to work with external models.
Option A suggests using Apex, but BYO-LLM functionality offers a more streamlined solution.
Option C focuses on Flow and External Services, which is more about data integration and isn't ideal for working with LLMs.

A.   Surround them with triple quotes (""").

Answer DescriptionExplanation: In Salesforce prompt templates, instructions that guide how the Large Language Model (LLM) should generate content (in this case, personalized emails) can be included by surrounding the instruction text with triple quotes ("""). This formatting ensures that the LLM adheres to the specific instructions while generating the email content.
The use of triple quotes allows the AI to understand that the enclosed text is a directive for how to approach the task, such as limiting the content to associated opportunity information or encouraging a specific action from the recipient.
Refer to Salesforce Prompt Builder documentation for detailed instructions on how to structure prompts for generative AI.

C.   Einstein Copilot analyzes the user's request and LLM technology is used to generate and display the appropriate response.

Answer DescriptionExplanation: Einstein Copilot is designed to enhance user interaction within Salesforce by leveraging Large Language Models (LLMs) to process and respond to user inquiries. When a user submits a request, Einstein Copilot analyzes the input using natural language processing techniques. It then utilizes LLM technology to generate an appropriate and contextually relevant response, which is displayed directly to the user within the Salesforce interface.
Option C accurately describes this process. Einstein Copilot does not necessarily trigger a flow (Option A) or perform an HTTP callout to an LLM provider (Option B) for each user request.
Instead, it integrates LLM capabilities to provide immediate and intelligent responses, facilitating a broad range of user requests.
References:
Salesforce AI Specialist Documentation - Einstein Copilot Overview: Details how Einstein Copilot employs LLMs to interpret user inputs and generate responses within the Salesforce ecosystem.
Salesforce Help - How Einstein Copilot Works: Explains the underlying mechanisms of how Einstein Copilot processes user requests using AI technologies.

B.   Einstein Service Replies

Answer DescriptionExplanation: When a customer chat is initiated, Einstein Service Replies provides generative AI replies or draft emails based on recommended Knowledge articles. This feature uses the information from the Salesforce Knowledge base to generate responses that are relevant to the customer's query, improving the efficiency and accuracy of customer support interactions.
Option B is correct because Einstein Service Replies is responsible for generating AI-driven responses based on knowledge articles.
Option A (Einstein Reply Recommendations) is focused on recommending replies but does not generate them.
Option C (Einstein Grounding) refers to grounding responses in data but is not directly related to drafting replies.

C.   Run Einstein Copilot Analytics.

Answer DescriptionExplanation: To monitor Einstein Copilot's usability and the assignment of actions, the AI Specialist should run Einstein Copilot Analytics. This feature provides insights into how often Copilot is used, the types of actions it is handling, and overall user engagement with the system. It’s the most effective way to track Copilot's performance and usage patterns.
Platform Debug Logs are not relevant for tracking user behavior or the assignment of Copilot actions.
Querying the Copilot log data via the Metadata API would not provide the necessary insights in a structured manner.
For more details, refer to Salesforce's Copilot Analytics documentation for tracking AI driven interactions.

B.   Field Generation

Answer DescriptionExplanation: The correct answer is Field Generation because this template type is designed to dynamically populate form fields with content generated by a large language model (LLM). In this scenario, leadership wants a dynamic form field that contains a summary or description generated by AI to aid customer interactions. Additionally, they want to keep a human in the loop, meaning the generated content will likely be reviewed or edited by a person before it's finalized, which aligns with the Field Generation prompt template.
Field Generation: This prompt type allows you to generate content for specific fields in Salesforce, leveraging large language models to create dynamic and contextual information. It ensures that AI content is available within the record where needed, but it allows human oversight or review, supporting the "human-inthe-loop" strategy.
Sales Email: This prompt type is mainly used for generating email content for outreach or responses, which doesn't align directly with populating fields in a form.
Record Summary: While this option might seem close, it is typically used to summarize entire records for high-level insights rather than filling specific fields with dynamic content based on AI generation.

B.   Test and confirm that the responses generated from prompts that utilize the data and masked data do not adversely affect the quality of the generated response

Answer DescriptionExplanation: After modifying masked fields in Einstein's Trust Layer, the next important step is to test and confirm that the responses generated by prompts utilizing the newly masked data still meet quality standards. This ensures that masking sensitive information does not negatively impact the usefulness or accuracy of the AI-generated content.
Thorough testing helps identify any issues in prompt performance that could arise due to masking, and adjustments can be made if needed.
Option Bis correct because testing the effects of masking on AI responses is a critical step in ensuring AI continues to function as expected.
Option A(turning off and on the Einstein Trust Layer) is unnecessary after changing the masked fields.
Option C(turning on Einstein Feedback) allows for user feedback but is not a direct step following field masking modifications.

B.   Use External Service Record merge fields.

Answer DescriptionExplanation: 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:
External Service Record Merge Fields:
Implementation Steps:
Register the External Service:
Create a Named Credential:
Use External Service in Flow:
Configure the Prompt Template:
Why Other Options are Less Suitable:
Option A (Convert the JSON to an XML merge field):
Option C (Use “Add Prompt Instructions” flow element):
References:
Salesforce AI Specialist Documentation -Integrating External Services with Prompt Templates:
Salesforce Help -Using Merge Fields with External Data:
Salesforce Trailhead -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.

B.   Turn on Einstein Generative AI.

Answer DescriptionExplanation: For Northern Trail Outfitters (NTO) to configure the Einstein Trust Layer, the Einstein Generative AI feature must be enabled. The Einstein Trust Layer is closely tied to generative AI capabilities, ensuring that AI-generated content complies with data privacy, security, and trust standards.
Option A(Turning on Einstein Copilot) is unrelated to the setup of the Einstein Trust Layer, which focuses more on generative AI interactions and data handling.
Option C(Turning on Prompt Builder) is used for configuring and building AI-driven prompts, but it does not enable the Einstein Trust Layer.

A.   Call Summary

Answer DescriptionExplanation: For a sales rep who may miss key details during long sales calls, the AI Specialist should recommend the Call Summary feature. Call Summary uses Einstein Generative AI to automatically generate a concise summary of important points discussed during the call, helping the rep quickly review the key information they might have missed.
Call Explorer is designed for manually searching through call data but doesn't summarize.
Sales Summary is focused more on summarizing overall sales activity, not call specific content.
For more details, refer to Salesforce's Call Summary documentation on how AI generated summaries can improve sales rep productivity.