Question # 1
Universal Containers’ current AI data masking rules do not align with organizational privacy and security policies and requirements.
What should An Agentforce recommend to resolve the issue?
| | A. Enable data masking for sandbox refreshes. | | B. Configure data masking in the Einstein Trust Layer setup. | | C. Add new data masking rules in LLM setup. |
B. Configure data masking in the Einstein Trust Layer setup.
Explanation
WhenUniversal Containers' AI data masking rulesdo not meet organizational privacy and security standards, theAgentforce Specialistshould configure thedata maskingrules within theEinstein Trust Layer. TheEinstein Trust Layerprovides a secure and compliant environment where sensitive data can be masked or anonymized to adhere to privacy policies and regulations.
Option A, enabling data masking for sandbox refreshes, is related to sandbox environments, which are separate from how AI interacts with production data.
Option C, adding masking rules in the LLM setup, is not appropriate because data masking is managed through theEinstein Trust Layer, not the LLM configuration.
The Einstein Trust Layer allows for more granular control over what data is exposed to the AI model and ensures compliance with privacy regulations.
Question # 2
| The sales team at a hotel resort would like to generate a guest summary about the guests’ interests and provide recommendations based on their activity preferences captured in each guest profile. They want the summary to be available only on the contact record page. Which AI capability should the team use? | | A. Model Builder | | B. Agent Builder | | C. Prompt Builder |
C. Prompt Builder
Explanation:
Comprehensive and Detailed In-Depth Explanation: The hotel resort team needs an AI-generated guest summary with recommendations, displayed exclusively on the contact record page. Let’s assess the options.
Option A: Model BuilderModel Builder in Salesforce creates custom predictive AI models (e.g., for scoring or classification) using Data Cloud or Einstein Platform data. It’s not designed for generating text summaries or embedding them on record pages, making it incorrect.
Option B: Agent BuilderAgent Builder in Agentforce Studio creates autonomous AI agents for tasks like lead qualification or customer service. While agents can provide summaries, they operate in conversational interfaces (e.g., chat), not as static content on a record page. This doesn’t meet the location-specific requirement, making it incorrect.
Option C: Prompt BuilderEinstein Prompt Builder allows creation of prompt templates that generate text (e.g., summaries, recommendations) using Generative AI. The template can pull data from contact records (e.g., activity preferences) and be embedded as a Lightning component on the contact record page via a Flow or Lightning App Builder. This ensures the summary is available only where specified, meeting the team’s needs perfectly and making it the correct answer.
Why Option C is Correct: Prompt Builder’s ability to generate contextual summaries and integrate them into specific record pages via Lightning components aligns with the team’s requirements, as supported by Salesforce documentation.
Question # 3
An Agentforce is setting up a new org and needs to ensure that users can create and execute prompt templates. The Agentforce Specialist is unsure which roles are necessary for these tasks.
Which permission sets should the Agentforce Specialist assign to users who need to create and execute prompt templates?
| | A. Prompt Template Manager for creating templates and Data Cloud Admin for executing templates | | B. Prompt Template Manager for creating templates and Prompt Template User for executing templates | | C. Data Cloud Admin for creating templates and Prompt Template User for executing templates |
B. Prompt Template Manager for creating templates and Prompt Template User for executing templates
Explanation
To effectively manage and use prompt templates, two distinct permission sets are required:
Prompt Template Manager: This permission set allows users to create prompt templates. It provides the necessary access to define templates, which can be shared and utilized across the organization.
Prompt Template User: This permission set is designed for users who need to execute the templates. It provides the ability to interact with pre-designed prompts and generate outcomes based on these templates.
The Data Cloud Admin permission set is not directly relevant to creating or executing prompt templates but is more focused on managing the Data Cloud.
Question # 4
| Universal Containers wants to reduce overall customer support handling time by minimizing the time spent typing routine answers for common questions in-chat, and reducing the post-chat analysis by suggesting values for case fields. Which combination of Agentforce for Service features enables this effort? | | A. Einstein Reply Recommendations and Case Classification | | B. Einstein Reply Recommendations and Case Summaries | | C. Einstein Service Replies and Work Summaries |
A. Einstein Reply Recommendations and Case Classification
Explanation:
Comprehensive and Detailed In-Depth Explanation: Universal Containers (UC) aims to streamline customer support by addressing two goals: reducing in-chat typing time for routine answers and minimizing post-chat analysis by auto-suggesting case field values. In Salesforce Agentforce for Service, Einstein Reply Recommendations and Case Classification(Option A) are the ideal combination to achieve this.
Einstein Reply Recommendations: This feature uses AI to suggest pre-formulated responses based on chat context, historical data, and Knowledge articles. By providing agents with ready-to-use replies for common questions, it significantly reduces the time spent typing routine answers, directly addressing UC’s first goal.
Case Classification: This capability leverages AI to analyze case details (e.g., chat transcripts) and suggest values for case fields (e.g., Subject, Priority, Resolution) during or after the interaction. By automating field population, it reduces post-chat analysis time, fulfilling UC’s second goal.
Option B: While "Einstein Reply Recommendations" is correct for the first part, "Case Summaries" generates a summary of the case rather than suggesting specific field values. Summaries are useful for documentation but don’t directly reduce post-chat field entry time.
Option C: "Einstein Service Replies" is not a distinct, documented feature in Agentforce (possibly a distractor for Reply Recommendations), and "Work Summaries" applies more to summarizing work orders or broader tasks, not case field suggestions in a chat context.
Option A: This combination precisely targets both in-chat efficiency (Reply Recommendations) and post- chat automation (Case Classification).
Question # 5
Universal Containers (UC) has implemented Generative AI within Salesforce to enable summarization of a custom object called Guest. Users have reported mismatches in the generated information.
In refining its prompt design strategy, which key practices should UC prioritize?
| | A. Enable prompt test mode, allocate different prompt variations to a subset of users for evaluation, and standardize the most effective model based on performance feedback. | | B. Create concise, clear, and consistent prompt templates with effective grounding, contextual role- playing, clear instructions, and iterative feedback. | | C. Submit a prompt review case to Salesforce and conduct thorough testing In the playground to refine outputs until they meet user expectations. |
B. Create concise, clear, and consistent prompt templates with effective grounding, contextual role- playing, clear instructions, and iterative feedback.
Explanation
ForUniversal Containers (UC)to refine itsGenerative AIprompt design strategy and improve the accuracy of the generated summaries for the custom objectGuest, the best practice is to focus on craftingconcise, clear, and consistent prompt templates.This includes:
Effective grounding: Ensuring the prompt pulls data from the correct sources.
Contextual role-playing: Providing the AI with a clear understanding of its role in generating the summary.
Clear instructions: Giving unambiguous directions on what to include in the response.
Iterative feedback: Regularly testing and adjusting prompts based on user feedback. Option Bis correct because it follows industry best practices for refining prompt design. Option A(prompt test mode) is useful but less relevant for refining prompt design itself.
Option C(prompt review case with Salesforce) would be more appropriate for technical issues or complex prompt errors, not general design refinement.
Question # 6
Universal Containers' sales team engages in numerous video sales calls with prospects across the nation. Sales management wants an easy way to understand key information such as deal terms or customer sentiments.
Which Einstein Generative AI feature should An Agentforce recommend for this request?
| | A. Einstein Call Summaries | | B. Einstein Conversation Insights | | C. Einstein Video KPI |
A. Einstein Call Summaries
Explanation
Einstein Call Summaries is the best option for this scenario because it leverages Salesforce's AI capabilities to automatically summarize key details of video or voice calls. It includes details like deal terms, customer sentiments, follow-up tasks, and other crucial information. This feature is designed to help sales teams focus on their strategies rather than taking extensive manual notes during conversations.
Einstein Call Summaries: Automatically generates summaries for calls, identifying critical points such as next steps and follow-ups, enhancing efficiency and understanding of deal progression.
Einstein Conversation Insights: While it provides insights into customer sentiment and engagement, it is more suited for analyzing patterns across conversations rather than summarizing specific call details.
Einstein Video KPI: Focuses on analyzing key performance indicators within video calls but does not offer summarization features needed for deal terms or sentiment tracking.
This feature ensures actionable insights are delivered directly into the Salesforce CRM, allowing sales managers to gain a concise overview without manually reviewing long recordings.
Question # 7
An Agentforce is tasked with analyzing Agent interactions looking into user inputs, requests, and queries to identify patterns and trends.
What functionality allows the AX Specialist to achieve this?
| | A. User Utterances dashboard | | B. Agent Event Logs dashboard | | C. AI Audit & Feedback Data dashboard |
A. User Utterances dashboard
Explanation
The User Utterances dashboard (Option A) is the correct functionality for analyzing user inputs, requests, and queries to identify patterns and trends. This dashboard aggregates and categorizes the natural language inputs (utterances) from users, enabling theAgentforce Specialistto:
Identify Common Queries: Surface frequently asked questions or recurring issues.
Detect Intent Patterns: Understand how users phrase requests, which helps refine intent detection models.
Improve Bot Training: Highlight gaps in training data or misclassified utterances that require adjustment.
Why Other Options Are Incorrect:
B. Agent Event Logs dashboard: Focuses on agent activity (e.g., response times, resolved cases) rather than user input analysis.
C. AI Audit & Feedback Data dashboard: Tracks AI model performance, audit trails, and user feedback scores but does not directly analyze raw user utterances or queries.
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