What is best practice when refining Agent custom action instructions?

1. A. Provide examples of user messages that are expected to trigger the action.
2. B. Use consistent introductory phrases and verbs across multiple action instructions.
3. C. Specify the persona who will request the action.

Correct Answer: A
When refining Agent custom action instructions, it is considered best practice to provide examples of user messages that are expected to trigger the action. This helps ensure that the custom action understands a variety of user inputs and can effectively respond to the intent behind the messages.
✑ Option B (consistent phrases) can improve clarity but does not directly refine the
triggering logic.
✑ Option C (specifying a persona) is not as crucial as giving examples that illustrate how users will interact with the custom action.
For more details, refer to Salesforce's Agent documentation on building and refining custom actions.

An Agentforce implements Einstein Sales Emails for a sales team. The team wants to send personalized follow-up emails to leads based on their interactions and data stored in
Salesforce. The Agentforce Specialist needs to configure the system to use the most accurate and up-to-date information for email generation.
Which grounding technique should the Agentforce Specialist use?

1. A. Ground with Apex Merge Fields
2. B. Ground with Record Merge Fields
3. C. Automatic grounding using Draft with Einstein feature

Correct Answer: C
For Einstein Sales Emails to generate personalized follow-up emails, it is crucial to ground the email content with the most up-to-date and accurate information. Grounding refers to connecting the AI model with real-time data. The most appropriate technique in this case is Ground with Record Merge Fields. This method ensures that the content in the emails pulls dynamic and accurate data directly from Salesforce records, such as lead or contact information, ensuring the follow-up is relevant and customized based on the specific record.
✑ Record Merge Fields ensure the generated emails are highly personalized using
data like lead name, company, or other Salesforce fields directly from the records.
✑ Apex Merge Fields are typically more suited for advanced, custom logic-driven scenarios but are not the most straightforward for this use case.
✑ Automatic grounding using Draft with Einstein is a different feature where Einstein automatically drafts the email, but it does not specifically ground the content with record-specific data like Record Merge Fields.
References:
✑ Salesforce Einstein Sales Emails Documentation: https://help.salesforce.com/s/articleView?id=release- notes.rn_einstein_sales_emails.htm