Explanation:

The standard Einstein Copilot action that would be used in response to the user utterance, “Show me all the customers in New York,” is Query Records. This action is responsible for retrieving a set of records from Salesforce based on a specified condition — in this case, filtering customers by location (New York).

Query Records is the action that fetches relevant data based on the criteria provided in the user's input.

Select Records is more about picking specific records from an already presented list.

Fetch Records is not a standard term used in this context for the action.

Explanation:

For sales reps who need to draft personalized emails based on previous communications, the AI Specialist should recommend the Einstein Copilot Action: Draft or Revise Sales Email. This action uses AI to generate or revise email content, leveraging past successful communications to create personalized and relevant outreach to prospects or clients.

Find Similar Opportunities is used for opportunity matching, not email drafting.

Summarize Record provides a summary of customer data but does not directly help with drafting emails.

Explanation:

To ensure that content generated by a large language model (LLM) is appropriately screened for toxic language, the AI Specialist should create a Trust Layer audit report with in Data Cloud. By using the toxicity detector type filter, the report can display toxic responses along with their respective toxicity scores, allowing Universal Containers to monitor and manage any toxic content generated with a high level of confidence.

Option C is correct because it enables visibility into toxic language detection with in the Trust Layer and allows for auditing responses for toxicity.

Option A suggests checking a toxicity detection log, but Salesforce provides more comprehensive options via the audit report.

Option B involves creating a flow, which is unnecessary for toxicity detection monitoring.

Explanation:

To ground a sales email on Opportunity Products, Events near the customer, and Tone and voice examples, the AI Specialist should use a prompt-initiated flow. This flow can dynamically fetch the necessary data from related records in Salesforce and ground the generative AI output with contextually accurate information.

Option B (flex template) does not provide the ability to fetch dynamic data from Salesforce records automatically.

Option C (manual insertion) would not allow for the dynamic and automated grounding of data required for custom prompts.

Explanation: WhenEinstein Copilot for Salesmatches similar opportunities, one of the primary criteria used is whether the opportunities have astatus of Closed Wonwithin the last 12 months. This is a key factor in identifying successful patterns that could help close current deals. By focusing on opportunities that have been recently successful, Einstein Copilot can provide relevant insights and suggestions to sales reps to help them close similar deals faster.
For more information, reviewSalesforce Einstein Copilot documentationrelated to opportunity matchingand sales success patterns.

Explanation: To understand multiple real-world user utterances and ensure the correct action is selected before activating acustom copilot action, the recommended tool is Copilot Builder. This tool allows AI Specialists to design and test conversational actions in response to user inputs, helping ensure the copilot can accurately handle different user queries and phrases.Copilot Builderprovides the ability to test, refine, and improve actions based on real-world utterances.
Option Cis correct asCopilot Builderis designed for configuring and testing conversational actions. Option A(Model Playground) is used for testing models, not user utterances. Option B(Einstein Copilot) refers to the conversational interface but isn't the right tool for designing and testing actions.

Explanation: WhenUniversal Containersuses theDraft with Einsteinfeature inSales Cloudto create a personalized email, the predefined adjustment toMake Less Formalis the correct option to revise the draft with a more casual tone. This option adjusts the wording of the draft to sound less formal, making the communication more approachable while still maintaining professionalism.
Enhance Friendlinesswould make the tone more positive, but not necessarily more casual.
Optimize for Clarityfocuses on making the draft clearer but doesn't adjust the tone. For more details, seeSalesforce documentation on Einstein-generated email drafts and tone adjustments.

Explanation: When buildingprompt templates in Prompt Builder, it is essential to consider how the Large Language Model (LLM) processes and generates outputs. Training the LLM with variouswriting styles, such as differentword choices, intensifiers, emojis, and punctuation, helps the model better understand diverse writing patterns and produce more contextually appropriate responses.
This approach enhances the flexibility and accuracy of the LLM when generating outputs for different use cases, as it is trained to recognize various writing conventions and styles. The prompt template should focus on providing rich context, and this stylistic variety helps improve the model’s adaptability.
Options A and B are less relevant because adding multiple-choice questions or role-playing scenarios doesn’t contribute significantly to improving the AI’s output generation quality within standard business contexts.
For more details, refer to Salesforce’sPrompt Builder documentationand LLM tuning strategies.

Explanation: WhenUniversal Containerscreates a new Sales Email prompt template using the"Save As"function, missing hyperparameters can result in different outputs. To ensure the new prompt produces comparable results to the standard Sales Email prompt, the AI Specialist shouldmanually add the necessary hyperparametersto the new template.
Hyperparameters likeTemperature,Frequency Penalty, andPresence Penaltydirectly affect how the AI generates responses. Ensuring that these are consistent with the standard template will result in similar outputs.
Option A (Model Playground)is not necessary here, as it focuses on fine-tuning models, not adjusting templates directly.
Option C (Reverting to the standard template)does not solve the issue of customizing the prompt template.
For more information, refer toPrompt Builder documentationon configuring hyperparameters in custom templates.

Explanation: When previewing aprompt templatein Salesforce, theResolutiontext provides theresponse from the LLM(Large Language Model) based on the data from a sample record. This output shows what the AI model generated in response to the prompt, giving the AI Specialist a chance to review and adjust the response before finalizing the template.
Option Bis correct becauseResolutiondisplays the actual response generated by the LLM.
Option Arefers to sending the text to theTrust Layer, but that’s not whatResolutionrepresents.
Option Crelates to data masking, which is shown elsewhere, not underResolution.