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Questions and Answers

How does the Einstein Trust Layer ensure the protection of sensitive data while allowing useful responses?

By offering access to all user data for AI training.

By encrypting all data during processing.

By capturing AI Audit data for monitoring and enhancement. (correct)

By limiting data retention to 24 hours.

What should an AI Specialist do first if a custom action using flow is not returning expected results?

Update all related software and tools.

Check the flow connections and settings for errors. (correct)

Reach out to other AI Specialists for assistance.

Recreate the custom action from scratch.

Which prompt template type should the AI Specialist use when tasked with generating output while enabling AI Audit data capture?

Standard text template using pre-defined variables.

Dynamic prompt template incorporating user inputs.

Predictive text template for suggestions.

Custom prompt template tailored to user needs. (correct)

What feature in the Einstein Trust Layer is best suited for enhancing data protection while using Salesforce record information?

Secure data merging capabilities. Signup and view all the answers

Why should the marketing team use Einstein Copilot for personalizing emails?

It provides predictive insights based on customer data. Signup and view all the answers

What is a key reason for implementing Einstein Copilot at Universal Containers?

To enhance operational efficiency Signup and view all the answers

How can Universal Containers enable sales reps to see opportunities similar to previously won opportunities using Einstein Copilot?

By entering the utterance in the custom search bar Signup and view all the answers

What use case is appropriate for Universal Containers to analyze sales operations efficiency using AI-powered predictions?

Forecasting monthly sales revenue. Signup and view all the answers

Which prompt template type should the AI Specialist recommend for populating a dynamic form with LLM-generated summaries?

Collaborative summary template with feedback options. Signup and view all the answers

What should an AI Specialist do to customize the existing standard email prompt template at Universal Containers?

Copy the existing template and modify its content Signup and view all the answers

Which hyperparameters can an AI Specialist change in an existing Salesforce-enabled foundational model within Model Playground?

Model architecture and training duration Signup and view all the answers

Which Einstein Copilot capability assists service agents in reviewing relevant Knowledge articles about flight cancellations?

Contextual search based on recent alerts. Signup and view all the answers

What core component should the development team review in Custom Copilot Action configuration for customer service operations?

Action workflow design Signup and view all the answers

How should an AI Specialist integrate a custom large language model into Salesforce while addressing security concerns?

Ensure compliance with data use policies Signup and view all the answers

Which predefined adjustment should UC choose to make a draft email more casual in Sales Cloud?

Use slang and informal phrases Signup and view all the answers

What should an AI Specialist consider when using related list merge fields in a prompt template associated with an Account object?

Validity of the merge fields Signup and view all the answers

Which use case functionality of Model Builder aligns with Universal Containers' request to implement a proactive outreach program?

Predictive Analytics Signup and view all the answers

Which tool should an AI Specialist recommend for understanding multiple real-world user utterances before activating a custom copilot action?

Natural Language Processing Tool Signup and view all the answers

Which Einstein Generative AI features are recommended for improving the productivity of Universal Containers' service center operation?

Automated Customer Responses Signup and view all the answers

How should an AI Specialist apply conversational AI to allow service agents to query the current fulfillment status of an order?

Developing a Chatbot Interface Signup and view all the answers

Which method is recommended for ensuring customer data privacy when integrating Einstein Generative AI into a CRM application?

Data Encryption and Masking Signup and view all the answers

What key practices should Universal Containers prioritize in refining its prompt design strategy for Generative AI to avoid mismatches in generated information?

Improving Prompt Accuracy Signup and view all the answers

What should Universal Containers do to ensure a new Sales Email prompt template produces results comparable to standard prompts?

Align Template Format with Standards Signup and view all the answers

Which type of prompt template should Universal Containers use to enable its sales team to suggest recommended products from its catalog?

Recommendation Engine Template Signup and view all the answers

What action will the planner service utilize based on the request to show all customers in New York?

List customer records Signup and view all the answers

What should an AI Specialist consider for using related lists in a custom prompt template?

Data structure and compatibility Signup and view all the answers

Which feature provides insights about competitor mentions and coaching opportunities in voice and video analysis?

Competitive intelligence tools Signup and view all the answers

What capability does enabling the 'Enrich event logs with conversation data' offer an AI Specialist?

Add context to event logs Signup and view all the answers

How should an organization utilize the Einstein Trust layer for data management?

To audit and view masked data Signup and view all the answers

In creating a custom action in Einstein Copilot, which option is available for an AI Specialist?

Select pre-defined action types Signup and view all the answers

What grounding technique should the AI Specialist use to ensure personalized follow-up emails are based on the most accurate information for leads?

Real-Time Data Syncing Signup and view all the answers

What recommendation should an AI Specialist give to ensure that sales reps can only execute prompt templates?

Implement role-based access control Signup and view all the answers

Which feature should the AI Specialist utilize to provide automatic post-call insights on competitors and products?

Competitor Mention Detection Signup and view all the answers

What is the main purpose of Prompt Builder in an AI context?

To create user prompts efficiently Signup and view all the answers

What is the primary function of the planner service in the Einstein Copilot system?

Task Scheduling Signup and view all the answers

What type of information does the Resolution text in a prompt template output provide?

Final Outcome Summary Signup and view all the answers

Which action should an AI Specialist take to manage toxic language within the Trust Layer?

Enable Toxicity Detection Algorithms Signup and view all the answers

What should the AI Specialist do to customize the standard case summary response from Einstein Copilot?

Use Custom Prompt Templates Signup and view all the answers

What is considered best practice when refining custom action instructions in Einstein Copilot?

Collect User Feedback Regularly Signup and view all the answers

Which feature in the Einstein Trust Layer helps to reduce the risk of prompt injection attacks?

Input Validation Mechanism Signup and view all the answers

Study Notes

Einstein Copilot Implementation

Key reason for implementing Einstein Copilot: Increased efficiency and improved processes in Salesforce.

Enabling Similar Opportunity Exploration

User utterance: ('Show me other opportunities like this one.')
AI Functionality: Einstein Copilot can be configured to recognize this utterance and recommend opportunities similar to the current one.

Customizing Standard Prompt Template

Objective: To use an existing standard email prompt template and customize it to meet specific business requirements.
Steps: An AI Specialist should:
- Review the content of the existing template.
- Identify gaps between current functionality and required functionality.
- Modify the prompt template to include the required enhancements.

Model Playground Hyperparameters

Hyperparameter adjustments: AI Specialists can modify hyperparameters influencing the behavior of Salesforce-enabled foundation models within Model Playground.

Understanding Custom Copilot Actions

Development team objective: Understand the core components of a Custom Copilot Action for proper configuration and functionality.
Key component: The development team should review the custom action's configuration to understand its action type (e.g. flow, Apex, etc.).

Integrating Custom LLM into Salesforce

Objective: An AI Specialist needs to integrate a custom LLM into Salesforce while maintaining security and data privacy.
Process:
- The AI Specialist should use data anonymization techniques to protect sensitive customer data.
- Integrate the custom LLM as an external service to Salesforce, strictly limiting data access.
- Implement robust authentication and authorization controls for communication between the service and Salesforce.

Adjusting Email Tone with 'Draft with Einstein'

Objective: Create a personalized introduction email using 'Draft with Einstein' and revise its tone.
Adjustment option: 'Casual' is a predefined option for revising the email's tone to a less formal style within 'Draft with Einstein'.

AI Specialist Objective: Ground a prompt template with the User related list.
Considerations:
- Ensure the related list's data is accurate and relevant.
- Develop prompts that effectively utilize the data from the related list.

AI Specialist Objective: Use related list merge fields in a prompt template associated with an Account object in Prompt Builder.
Considerations:
- Review the available merge fields for the related list and select the appropriate ones.
- Use clear and concise prompts that effectively use the chosen merge fields.

Bringing Unified Data Cloud Objects to Prompt Templates

Objective: Use Flow to bring data from unified Data Cloud objects to prompt templates.
Method: AI Specialists should use a combination of Flow to integrate data from Data Cloud objects into prompt templates.

Einstein Trust Layer for Sensitive Data Protection

Objective: Protect sensitive data while generating meaningful responses.
Mechanism:
- Einstein Trust Layer obfuscates sensitive data prior to feeding it to AI models.
- De-identification techniques are used to ensure privacy.
- The layer generates responses that are useful but do not compromise sensitive data.

Troubleshooting Custom Copilot Action Issues

Objective: Troubleshoot a Custom Copilot action that is not delivering the expected results.
Action: The AI Specialist should:
- Review the flow logic contained within the Custom Copilot Action.
- Check for any errors or misconfigured steps in the flow.
- Ensure that the flow accesses the correct data sources.

AI Audit Tracking and Monitoring

Objective: Enable AI Audit data capture and monitoring for adoption and enhancements.
Considerations:
- AI Specialists should prioritize the use of a 'Field Generation' prompt template type when creating custom prompt templates.
- Ensure that the target data is captured and monitored for improvement and to understand user interaction with the system.

Data Protection and Information Merging with Einstein Trust Layer

Objective: Secure and reliable CRM data with enhanced data protection and AI capabilities.
Solution: 'Contextual Data' feature within Einstein Trust Layer. This feature allows administrators to include relevant information from Salesforce records to be merged with the prompt.

Personalized Emails with Einstein Copilot

Objective: Personalize emails based on customer behavior, preferences, and purchase history.
Reason: Einstein Copilot provides deep customer insights and generates personalized content, enhancing engagement and conversions.

AI-Powered Predictions in Einstein Studio

Objective: Improve sales operations efficiency by analyzing data using AI-powered predictions.
Use Cases: Einstein Studio can be used for:
- Sales forecasting,
- Opportunity scoring,
- Lead prioritization,
- Predictive lead scoring.

Dynamic Form Field Population with AI

Objective: Populate a dynamic form field with a summary description created by an LLM.
Prompt Template Type: 'Field Generation' with human-in-the-loop AI strategy is recommended.

Einstein Copilot for Service Agent Knowledge Retrieval

Objective: Help a service agent retrieve specific knowledge articles for canceling and rebooking customer flights.
Capability: Einstein Copilot's 'Knowledge Search' feature allows agents to find relevant Knowledge articles using natural language queries.

Standard Einstein Copilot Action for Customer Queries

User utterance: ('Show me all the customers in New York.')
Standard Action: The planner service should be able to identify this utterance and execute the 'List records' action to display customer records from the location.

AI Specialist Objective: Use related lists from an Account object in a custom prompt template.
Considerations:
- Determine which fields from the related list should be included in the template.
- Write prompts that make the most effective use of the included fields.

Voice and Video Insights with Generative AI

Objective: Identify competitor mentions, coaching opportunities, and other key information from voice and video records.
Feature: 'Generative AI for Voice and Video'. This feature analyzes voice and video records to provide insights into competitor mentions, coaching opportunities, and other key indicators.

Enabling Conversation Data Enrichment

Objective: Enable the 'Enrich event logs with conversation data' setting in Einstein Copilot.
Action: This setting allows the AI Specialist to:
- Capture interactions and outputs from conversations involving Einstein Copilot.
- Analyze the collected data to identify trends and improve the AI's performance.

Auditing Masked Data with the Einstein Trust Layer

Objective: Audit, track, and view masked data.
Method: The Einstein Trust Layer contains features for tracking and viewing data that was masked for privacy.

Custom Copilot Action Configuration

AI Specialist Options:
- Flow: Use predefined flows as a custom action.
- Apex: Use Apex code to implement custom logic for the action.
- External Service: Integrate an external service with the Einstein Copilot to implement custom actions.

AI-Powered Marketing Emails

Objective: Generate a personalized marketing email based on customer interests.
Recommendation: Use Einstein Email Insights feature to recommend the most relevant products and create personalized marketing email content.

Generative AI Field Icon Visibility Issue

Problem: A user is unable to see the generative AI-enabled field icon next to a summary field.
Likely Cause: The user's profile does not have the necessary permissions to access generative AI features.

Efficiency Enhancement with Einstein for Service

Objective: Reduce agent handling time and post-chat analysis time.
Features:
- Einstein Bots: Automates replies to common queries.
- Einstein Case Suggestions: Suggests values for case fields, minimizing manual typing.

Limiting Users to Prompt Template Execution

Objective: Users should only be able to execute prompt templates.
Recommendation: Use 'Prompt Only' user access in Einstein Copilot. This setting restricts users to executing prompt templates without access to any other functionality, ensuring prompt template usage only.

Purpose of Prompt Builder

Core Function: To create, edit, and manage prompt templates for various use cases.
Prompt Template Creation: This includes adding prompts for different object types and customizing the prompts to meet specific requirements.

Configuring Service AI Grounding

Objective: Include all supported objects in AI Grounding to ensure responses are grounded in relevant data.
Configuration: The AI Specialist should select the following objects to configure Service AI Grounding:
- Cases
- Contacts
- Accounts
- Knowledge Articles
- Other custom objects as needed.

Choosing the Right Grounding Technique

Objective: Use the most accurate and up-to-date information for email generation.
Recommended Technique: 'Contextual Grounding'. This technique ensures that email content reflects the most recent information available in Salesforce.

Post-Call Insights for Sales Teams

Objective: Automatically provide post-call insights into competitor mentions, products, and custom phrases.
Feature: 'Conversation Insights' in Einstein Copilot analyzes voice and video calls and provides key insights to sales teams.

Planner Service Functionality

Primary Function: The planner service in Einstein Copilot manages how users interact with the system.
User Interactions: It processes user utterances, identifies the intent, and determines the appropriate action to take.

Understanding Resolution Text in Prompt Template Preview

Resolution Text: Provides information about the reasoning behind the prompt template's output during a preview.
Explanation: It shows the logic used by the AI model to generate the output, explaining the reasoning for the generated response.

Managing Toxicity with the Trust Layer

Objective: Detect and mitigate potentially toxic language generated by LLM.
Action: The AI Specialist should configure the 'Toxicity Detection' setting in the Einstein Trust Layer. This setting enables the Trust Layer to detect and flag content that is considered toxic.

Customizing Standard Case Summary Response

Objective: Customize the standard case summary response generated by Einstein Copilot.
Action: The AI Specialist should:
- Create a custom prompt template that includes the desired modifications.
- Use the new custom template to replace the standard case summary prompt.

Refining Custom Action Instructions

Best Practice: Ensure that:
- Instructions are clear and concise, minimizing ambiguity.
- They provide detailed information about the desired input and output.
- Examples are included to illustrate the expected behavior.

Minimizing Jailbreaking Attacks with Einstein Trust Layer

Feature: 'Prompt Filtering' in the Einstein Trust Layer.
Action: Filter and sanitize user inputs to prevent malicious code injection and safeguard the system.

Using Prompt Builder for Customer Support Productivity

Objective: Enhance the customer support team's productivity using AI.
Use Case: Create prompt templates for:
- Case summarization
- Case analysis
- Pre-populated customer outreach emails
- Knowledge article recommendations.

Validating Field Generation for Generative AI

Objective: Validate if a field is eligible for generative AI.
Checkpoints: The AI Specialist should confirm that the field:
- Is of a text-based data type (e.g., text area, rich text area).
- Does not have any unique validation rules that would hinder generative AI functionality.

Proactive Customer Outreach with Model Builder

Objective: Implement a proactive outreach program to prevent customer contract cancellations.
Model Builder Functionality: Use the 'Predictive Model' functionality to:
- Identify customers at risk of cancellation.
- Target these customers with early intervention strategies.

Testing Custom Copilot Actions

Objective: Understand how custom copilot actions will perform with real-world user utterances.
Recommendation: Use the 'Conversation Preview' tool in Einstein Copilot to test the action with various user utterances.

Einstein Generative AI Features for Service Operations

Recommendations: The AI Specialist should recommend the following features:
- Einstein Bots: Automatic replies to common questions, improving agent availability.
- Case Summarization: Summarize case details, reducing agent reading time.
- Case Suggestions: Suggest appropriate case fields, minimizing manual input.

Conversational AI for Order Fulfillment Queries

Objective: Enable service agents to query order fulfillment status using natural language.
Method: Use the power of conversational AI by creating:
- A custom prompt template that allows agents to query the order status naturally.
- Integrate the existing auto-launched flow with this prompt template to receive order fulfillment data.

Protecting Customer Privacy with Generative AI

Recommended Method: Differential Privacy.
Advantages:
- Adds random noise to data before it is used by generative models.
- Preserves the overall data distribution while safeguarding customer privacy.

Refining Prompt Design for Generative AI

Key Practices: Universal Containers should:
- Provide clear and specific instructions: Define the desired output format and style clearly.
- Include relevant context: Ensure the AI model has access to relevant information from the Guest object.
- Iterate and test: Continuously test and refine prompts based on the quality of the generated output.

Ensuring Consistent Prompt Template Results

Problem: A new prompt template is producing different results compared to the standard template.
Action: The AI Specialist should:
- Compare the hyperparameter settings: Ensure that all necessary hyperparameters are included in the new template.
- Utilize the "Save As" function: Use this function to create a copy of the standard template to preserve hyperparameter settings.

Understanding Security Compliance with Einstein AI

Recommendation: The AI Specialist should:
- Review data masking and de-identification methods.
- Understand the Trust Layer's data encryption and access control mechanisms.
- Familiarize themselves with compliance certifications and reporting capabilities.

Managing Einstein Copilot Actions

Location: The AI Specialist should go to 'Setup' > 'Einstein AI' > 'Einstein Copilot' to add or update custom actions.

Recommended Prompt Template for Product Suggestions

Prompt Template Type: 'Product Recommendation'. This template type is designed to generate recommendations for products based on various factors like customer profiles, purchase history, and browsing behavior.

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