AI Specialist Certi with Answers PDF

1) Which feature of the Einstein Trust Layer is designed to identify and reduce the risk of harmful or toxic outputs from generative AI? A. Dynamic Grounding with Secure Data Retrieval B. Prompt Defense C. Toxicity Scoring Prompt Defense refers to system policies that help limit hallucinations and decrease the likelihood of harmful outputs. 2) How does the Einstein Trust Layer help organizations comply with strict data privacy regulations? A. By encrypting data during transmission B. By allowing users to opt out of data sharing C. By implementing a Zero-Data Retention Policy Explanation: The Einstein Trust Layer helps organizations comply with strict data privacy regulations by implementing a Zero-Data Retention Policy, which ensures that data is not stored longer than necessary and complies with privacy laws. 3) What is the primary role of Prompt Defense in the Einstein Trust Layer? A. To monitor data for compliance with regulations B. To prevent unintended AI-generated outputs C. To dynamically update the AI model with new data Explanation: The primary role of Prompt Defense is to prevent unintended AI-generated outputs, helping to ensure that the content produced by AI models is appropriate and aligned with user expectations. 4) How does Dynamic Grounding with Secure Data Retrieval enhance the accuracy of AI-generated outputs? A. By updating AI outputs with real-time data B. By reducing computational errors C. By filtering out irrelevant data points Explanation: Dynamic Grounding with Secure Data Retrieval enhances accuracy by updating AI outputs with real-time data, ensuring that the information provided is current and relevant. 5) Which type of Prompt Templates can be used to bring generative AI-assisted workflows to custom fields within a Salesforce record? A. Flex Prompt Templates B. Field Generation Prompt Templates C. Record Summary Prompt Templates 6) An AI Specialist has been assigned a task to create a Prompt Template for Sales Team to help reduce the time that the team spends on creating invitations to customers for product events. How can AI Specialist create a Prompt Template? A. New Prompt Template button on Prompt Builder Explore page B. New Prompt Template quick Action on Home Page C. New Prompt Template global action 7) An AI Specialist has been assigned a task to create a Prompt Template for Sales Team to help reduce the time that the team spends on creating invitations to customers for product events. Which of the following resources can be used in a Prompt Template? A. Apex Class B. Omniscript C. Integration Procedure 8) Which of the following is a technique used to provide context and specificity to prompt responses? A. Toxicity Detection B. Prompt Defense C. Grounding 9) Which of the following is a building block of Einstein Copilot? A. Events B. Actions C. Prompts https://help.salesforce.com/s/articleView?id=sf.copilot_building_blocks.htm&type=5 10) Which feature in the Einstein Trust Layer helps to minimize the risks of jailbreaking and prompt injection attacks? A- Secure Data Retrieval and Grounding B- Data Masking C- Prompt Defense Explanation: Prompt Defense is a feature in the Einstein Trust Layer that helps minimize the risks of jailbreaking and prompt injection attacks. These attacks occur when malicious users try to manipulate the AI model by providing unintended inputs. Prompt Defense ensures that the prompts are processed securely, protecting the system from such vulnerabilities. 11) Universal Containers plans to enhance the customer support team's productivity using AI. Which specific use case necessitates the use of Prompt Builder? A- Creating a draft of a support bulletin post for new product patches B- Creating an Al-generated customer support agent performance score C- Estimating support ticket volume based on historical data and seasonal trends Explanation: The use case that necessitates the use of Prompt Builder is creating a draft of a support bulletin post for new product patches. Prompt Builder allows the AI Specialist to create and refine prompts that generate specific, relevant outputs, such as drafting support communication based on product information and patch details. Option B (agent performance score) would likely involve predictive modeling, not prompt generation. Option C (estimating support ticket volume) would require data analysis and predictive tools, not prompt building. For more details, refer to Salesforce's Prompt Builder documentation for generative AI content creation 12) An AI Specialist is considering using a Field Generation prompt template type. What should the AI Specialist check before creating the Field Generation prompt to ensure it is possible for the field to be enabled for generative AI? A- That the field chosen must be a rich text field with 255 characters or more. B- That the org is set to API version 59 or higher C- That the Lightning page layout where the field will reside has been upgraded to Dynamic Forms Explanation: Before creating a Field Generation prompt template, the AI Specialist must ensure that the Salesforce org is set to API version 59 or higher. This version of the API introduces support for advanced generative AI features, such as enabling fields for generative AI outputs. This is a critical technical requirement for the Field Generation prompt template to function correctly. Option A (rich text field requirement) is not necessary for generative AI functionality. Option C (Dynamic Forms) does not impact the ability of a field to be generative AI-enabled, although it might enhance the user interface. For more information, refer to Salesforce documentation on API versioning and Field Generation templates. 13) Universal Containers (UC) noticed an increase in customer contract cancellations in the last few months. UC is seeking ways to address this issue by implementing a proactive outreach program to customers before they cancel their contracts and is asking the Salesforce team to provide suggestions. Which use case functionality of Model Builder aligns with UC's request? A- Product recommendation prediction B- Customer churn prediction C- Contract Renewal Date prediction Explanation: Customer churn prediction is the best use case for Model Builder in addressing Universal Containers' concerns about increasing customer contract cancellations. By implementing a model that predicts customer churn, UC can proactively identify customers who are at risk of canceling and take action to retain them before they decide to terminate their contracts. This functionality allows the business to forecast churn probability based on historical data and initiate timely outreach programs. Option B is correct because customer churn prediction aligns with UC's need to reduce cancellations through proactive measures. Option A (product recommendation prediction) is unrelated to contract cancellations. Option C (contract renewal date prediction) addresses timing but does not focus on predicting potential cancellations. Salesforce Model Builder Use Case Overview: https://help.salesforce.com/s/articleView?id=sf.model_builder_use_cases.htm 14) Before activating a custom copilot action, an AI Specialist would like is to understand multiple real-world user utterances to ensure the action being selected appropriately. Which tool should the AI Specialist recommend? A- Model Playground B- Einstein Copilot C- Copilot Builder Explanation: To understand multiple real-world user utterances and ensure the correct action is selected before activating a custom 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 Builder provides the ability to test, refine, and improve actions based on real-world utterances. Option C is correct as Copilot Builder is 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. Salesforce Copilot Builder Overview: https://help.salesforce.com/s/articleView?id=sf.einstein_copilot_builder.htm 15) The AI Specialist of Northern Trail Outfitters reviewed the organization's data masking settings within the Configure Data Masking menu within Setup. Upon assessing all of the fields, a few additional fields were deemed sensitive and have been masked within Einstein's Trust Layer. Which steps should the AI Specialist take upon modifying the masked fields? A- Turn off the Einstein Trust Layer and turn it on again. 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 C- Turn on Einstein Feedback so that end users can report if there are any negative side effects on AI features. Explanation: 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 B is 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. Salesforce Einstein Trust Layer Overview: https://help.salesforce.com/s/articleView?id=sf.einstein_trust_layer.htm 16) Universal Containers (UC) wants to improve the efficiency of addressing customer questions and reduce agent handling time with AI-generated responses. The agents should be able to leverage their existing knowledge base and identify whether the responses are coming from the large language model (LLM) or from Salesforce Knowledge. Which step should UC take to meet this requirement? A- Turn on Service AI Grounding, Grounding with Case, and Service Replies. B- Turn on Service Replies, Service AI Grounding, and Grounding with Knowledge. C- Turn on Service AI Grounding and Grounding with Knowledge. Explanation: To meet Universal Containers' goal of improving efficiency and reducing agent handling time with AI-generated responses, the best approach is to enable Service Replies, Service AI Grounding, and Grounding with Knowledge. Service Replies generates responses automatically. Service AI Grounding ensures that the AI is using relevant case data. Grounding with Knowledge ensures that responses are backed by Salesforce Knowledge articles, allowing agents to identify whether a response is coming from the LLM or Salesforce Knowledge. Option C does not include Service Replies, which is necessary for generating AI responses. Option A lacks the Grounding with Knowledge, which is essential for identifying response sources. For more details, refer to Salesforce Service AI documentation on grounding and service replies 17) Universal Containers (UC) has recently received an increased number of support cases. As a result, UC has hired more customer support reps and has started to assign some of the ongoing cases to newer reps. Which generative AI solution should the new support reps use to understand the details of a case without reading through each case comment? A- Einstein Copilot B- Einstein Sales Summaries C- Einstein Work Summaries Explanation: New customer support reps at Universal Containers can use Einstein Work Summaries to quickly understand the details of a case without reading through each case comment. Work Summaries leverage generative AI to provide a concise overview of ongoing cases, summarizing all relevant information in an easily digestible format. Einstein Copilot can assist with a variety of tasks but is not specifically designed for summarizing case details. Einstein Sales Summaries are focused on summarizing sales-related activities, which is not applicable for support cases. For more details, refer to Salesforce documentation on Einstein Work Summaries. 18) Universal Containers (UC) plans to send one of three different emails to its customers based on the customer's lifetime value score and their market segment. Considering that UC are required to explain why an e-mail was selected, which AI model should UC use to achieve this? A- Predictive model and generative model B- Generative model C- Predictive model Explanation: Universal Containers should use a Predictive model to decide which of the three emails to send based on the customer's lifetime value score and market segment. Predictive models analyze data to forecast outcomes, and in this case, it would predict the most appropriate email to send based on customer attributes. Additionally, predictive models can provide explainability to show why a certain email was chosen, which is crucial for UC's requirement to explain the decision-making process. Generative models are typically used for content creation, not decision-making, and thus wouldn't be suitable for this requirement. Predictive models offer the ability to explain why a particular decision was made, which aligns with UC's needs. Refer to Salesforce's Predictive AI model documentation for more insights on how predictive models are used for segmentation and decision making. 19) Amid their busy schedules, sales reps at Universal Containers dedicate time to follow up with prospects and existing clients via email regarding renewals or new deals. They spend many hours throughout the week reviewing past communications and details about their customers before performing their outreach. Which standard Copilot action helps sales reps draft personalized emails to prospects by generating text based on previous successful communications? A- Einstein Copilot Action: Find Similar Opportunities B- Einstein Copilot Action: Draft or Revise Sales Email C- Einstein Copilot Action: Summarize Record 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. For more information, refer to Salesforce's Einstein Copilot documentation on standard actions for sales teams. 20) Universal Containers is evaluating Einstein Generative AI features to improve the productivity of the service center operation. Which features should the AI Specialist recommend? A- Service Replies and Case Summaries B- Service Replies and Work Summaries C- Reply Recommendations and Sales Summaries Explanation: To improve the productivity of the service center, the AI Specialist should recommend the Service Replies and Case Summaries features. Service Replies helps agents by automatically generating suggested responses to customer inquiries, reducing response time and improving efficiency. Case Summaries provide a quick overview of case details, allowing agents to get up to speed faster on customer issues. Work Summaries are not as relevant for direct customer service operations, and Sales Summaries are focused on sales processes, not service center productivity. For more information, see Salesforce's Einstein Service Cloud documentation on the use of generative AI to assist customer service teams. 21) Universal Containers is very concerned about security compliance and wants to understand: Which prompt text is sent to the large language model (LLM) * How it is masked * The masked response What should the AI Specialist recommend? A- Ingest the Einstein Shield Event logs into CRM Analytics. B- Review the debug logs of the running user. C- Enable audit trail in the Einstein Trust Layer Explanation: To address security compliance concerns and provide visibility into the prompt text sent to the LLM, how it is masked, and the masked response, the AI Specialist should recommend enabling the audit trail in the Einstein Trust Layer. This feature captures and logs the prompts sent to the large language model (LLM) along with the masking of sensitive information and the AI's response. This audit trail ensures full transparency and compliance with security requirements. Option A (Einstein Shield Event logs) is focused on system events rather than specific AI prompt data. Option B (debug logs) would not provide the necessary insight into AI prompt masking or responses. For further details, refer to Salesforce's Einstein Trust Layer documentation about auditing and security measure 22) Universal Containers wants to allow its service agents to query the current fulfilment status of an order with natural language. There is an existing autolaunched flow to query the information from Oracle ERP, which is the system of record for the order fulfilment process. How should an AI Specialist apply the power of conversational AI to this use case? A. Create a Flex prompt template in Prompt Builder B. Create a custom copilot action which calls a flow C. Configure the Integration Flow Standard Action in Einstein Copilot To enable Universal Containers service agents to query the current fulfillment status of an order using natural language and leverage an existing auto-launched flow that queries Oracle ERP, the best solution is to create a custom copilot action that calls the flow. This action will allow Einstein Copilot to interact with the flow and retrieve the required order fulfillment information seamlessly. Custom copilot actions can be tailored to call various backend systems or flows in response to user requests. * Option Bis correct because it enables integration between Einstein Copilot and the flow that connects to Oracle ERP. * Option A(Flex prompt template) is more suited for static responses and not for invoking flows. * Option C(Integration Flow Standard Action) is not directly related to creating a specific copilot action for this use case. References: * Salesforce Einstein Copilot Actions: https://help.salesforce.com/s/articleView?id=einstein_copilot_actions.htm 23) 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. Einstein Copilot B. Prompt builder C. Model builder Explanation: The sales team at a hotel resort wants to generate a guest summary about guests' interests and provide recommendations based on their activity preferences captured in each guest profile. They require the summary to be availableonly on the contact record page. Solution: UsePrompt Builderto create a prompt template that generates the desired summary and displays it on the contact record page. Prompt Builder: Purpose:Allows the creation of custom prompt templates that leverage AI to generate content based on Salesforce data. Functionality: Field Generation Templates:Can be used to populate fields on records with AI-generated summaries. Customization:Enables the AI Specialist to design prompts that utilize data from the guest profiles to produce personalized summaries and recommendations. Relevance to the Use Case: The sales team wants the summary to be available on the contact record page, which aligns with the capabilities of Prompt Builder to generate and display content on specific record pages. Implementation Steps: Create a Field Generation Prompt Template: Use Prompt Builder to create a new prompt template of typeField Generation. Design the prompt to instruct the AI to generate a summary based on the guest's interests and activity preferences. Include Relevant Data: Use merge fields to include data from the guest profile in the prompt. Ensure that the prompt accesses the necessary fields to generate accurate recommendations. Configure the Contact Page Layout: Add the field that will display the AI-generated summary to the contact record page layout. Ensure that the field is only visible where appropriate, adhering to the requirement of availability only on the contact record page. Why Not Einstein Copilot or Model Builder: Option A (Einstein Copilot): Purpose:Einstein Copilot is a conversational AI assistant designed to interact with users through natural language. Mismatch with Requirements: The team wants a static summary displayed on the contact record page, not an interactive conversational experience. Option C (Model Builder): Purpose: Model Builder is used to create custom AI models for predictions and classifications. Inapplicability: Building a custom model is unnecessary for generating text summaries based on existing data. Model Builder does not directly provide functionality to generate and display summaries on record pages. References: Salesforce AI Specialist Documentation -Prompt Builder Overview: Provides an introduction to Prompt Builder and its capabilities. Salesforce Help -Creating Field Generation Prompt Templates: Guides on creating prompt templates that generate content for fields on records. Salesforce Trailhead -Customize AI Content with Prompt Builder: Offers hands-on experience in building and customizing prompt templates. Conclusion: By utilizing Prompt Builder, the sales team can create a customized prompt template that generates personalized guest summaries and recommendations based on activity preferences. This solution meets the requirement of displaying the summary only on the contact record page, enhancing the team's ability to engage with guests effectively. 24) Universal Containers tests out a new Einstein Generative AI feature for its sales team to create personalized and contextualized emails for its customers. Sometimes, users find that the draft email contains placeholders for attributes that could have been derived from the recipient’s contact record. What is the most likely explanation for why the draft email shows these placeholders? A. The user does not have Einstein Sales Emails permission assigned B. The user does not have permission to access the fields C. The user’s locale language is not supported by Prompt Builder Explanation: When using Einstein Generative AI to create personalized emails, if placeholders appear in the draft email where data from a recipient's Contact record should be, the most likely reason is that the user lacks permission to access the necessary fields. Salesforce's field-level security may prevent users from viewing or utilizing certain data fields, resulting in placeholders being shown instead of the actual values. Option B is correct because missing field permissions will cause placeholders in email drafts. Option A (missing Einstein Sales Emails permission) is unlikely, as this would prevent email generation altogether, not just placeholders. Option C (locale language issues) would more likely affect language-specific issues, not field placeholders. References: Salesforce Email Template and Permissions Documentation: https://help.salesforce.com/s/articleView?id=sf.email_templates_field_permissions.htm 25) Universal containers wants to make a sales proposal and directly use data from multiple unrelated objects (standard and custom) in a prompt template. What should the AI Specialist recommend? A. Create a Flex template to add resources with standard and custom objects as inputs B. Create a prompt template passing in a special custom object that connects the records temporarily C. Create a prompt template-triggered flow to access the data from standard and custom objects Explanation: Universal Containers needs to generate a sales proposal using data from multiple unrelated standard and custom objects within a prompt template. The most effective way to achieve this is by using a Flex template. Flex templates in Salesforce allow AI specialists to create prompt templates that can accept inputs from multiple sources, including various standard and custom objects. This flexibility enables the direct use of data from unrelated objects without the need to create intermediary custom objects or complex flows. References: Salesforce AI Specialist Documentation - Flex Templates: Explains how Flex templates can be utilized to incorporate data from multiple sources, providing a flexible solution for complex data requirements in prompt templates. 26) An AI Specialist at Universal Containers (UC) is tasked with creating a new custom prompt template to populate a field with generated output. UC enabled the Einstein Trust Layer to ensure AI Audit data is captured and monitored for adoption and possible enhancements. Which prompt template type should the AI Specialist use and which consideration should they review? A. Flex, and that Dynamic Fields is enabled B. Filed Generation, and that Dynamic Fields is enabled (incorrect) read this C. Field generation, and that Dynamic Forms is enabled To add a field generation prompt template to a Lightning record page, you must enable Dynamic Forms, which support most, but not all, standard LWC-enabled objects. 27) In Model Playground, which hyperparameters of an existing Salesforce-enabled foundational model can an AI Specialist change? A. Temperature, Frequency Penalty, Presence Penalty B. Temperature, Top-k sampling, presence Penalty C. Temperature, Frequency Penalty, Output Tokens Explanation: In Model Playground, an AI specialist working with a Salesforce-enabled foundational model has control over specific hyperparameters that can directly affect the behavior of the generative model: Temperature: Controls the randomness of predictions. A higher temperature leads to more diverse outputs, while a lower temperature makes the model's responses more focused and deterministic. Frequency Penalty: Reduces the likelihood of the model repeating the same phrases or outputs frequently. Presence Penalty: Encourages the model to introduce new topics in its responses, rather than sticking with familiar, previously mentioned content. These hyperparameters are adjustable to fine-tune the model’s responses, ensuring that it meets the desired behavior and use case requirements. Salesforce documentation confirms that these three are the key tunable hyperparameters in the Model Playground. For more details, refer to Salesforce AI Model Playground guidance from Salesforce’s official documentation on foundational model adjustments. 28) Universal containers implements Custom Copilot Actions to enhance its customer service operations. The development team needs tounderstand the core components of a Custom Copilot Action to ensure proper configuration and functionality. What should the development team review in the Custom Copilot Action configuration to identify one of the core components of a Custom Copilot Action? A. Instructions B. Output Types C. Action triggers 29) Universal Containers (UC) is using Einstein Generative AI to generate an account summary. UC aims to ensure the content is safe and inclusive, utilizing the Einstein Trust Layer’s toxicity scoring to assess the content’s level. What does a safety category score of 1 indicate in the Einstein Generative Toxicity Score? A. Not safe B. Safe C. Moderately safe Explanation: In the Einstein Trust Layer, the toxicity scoring system is used to evaluate the safety level of content generated by AI, particularly to ensure that it is non-toxic, inclusive, and appropriate for business contexts. A toxicity score of 1 indicates that the content is deemed safe. The scoring system ranges from 0 (unsafe) to 1 (safe), with intermediate values indicating varying degrees of safety. In this case, a score of 1 means that the generated content is fully safe and meets the trust and compliance guidelines set by the Einstein Trust Layer. For further reference, check Salesforce’s official Einstein Trust Layer documentation regarding toxicity scoring for AI-generated content. 30) Universal Containers (UC) wants to offer personalized service experiences and reduce agent handling time with Al-generated email responses, grounded in Knowledge base. Which AI capability should UC use? A. Einstein Email Replies B. Einstein Service Replies for Email C. Einstein Generative Service Replies for Email Explanation: For Universal Containers (UC) to offer personalized service experiences and reduce agent handling time using AI-generated responses grounded in the Knowledge base, the best solution is Einstein Service Replies for Email. This capability leverages AI to automatically generate responses to service-related emails based on historical data and the Knowledge base, ensuring accuracy and relevance while saving time for service agents. Einstein Email Replies (option A) is more suited for sales use cases. Einstein Generative Service Replies for Email (option C) could be a future offering, but as of now, Einstein Service Replies for Email is the correct choice for grounded, knowledge-based responses. References: Einstein Service Replies Overview: https://help.salesforce.com/s/articleView?id=sf.einstein_service_replies.htm 31) Northern Trail Outfitters (NTO) wants to configure Einstein Trust Layer in its production org but is unable to see the option on the Setup page. After provisioning Data Cloud, which step must an Al Specialist take to make this option available to NTO? A. Turn on Einstein Copilot. B. Turn on Einstein Generative AI. C. Turn on Prompt Builder. Explanation: 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. Salesforce AI Specialist References: For more details on the Einstein Trust Layer and setup steps: https://help.salesforce.com/s/articleView?id=sf.einstein_trust_layer_overview.htm 32) Universal Containers (UC) uses Salesforce Service Cloud to support its customers and agents handling cases. UC is considering implementing Einstein Copilot and extending Service Cloud to mobile users. When would Einstein Copilot implementation be most advantageous? A. When the goal is to streamline customer support processes and improve response times B. When the main objective is to enhance data security and compliance measures C. When the focus is on optimizing marketing campaigns and strategies Explanation: Einstein Copilot implementation would be most advantageous in Salesforce Service Cloud when the goal is to streamline customer support processes and improve response times. Einstein Copilot can assist agents by providing real-time suggestions, automating repetitive tasks, and generating contextual responses, thus enhancing service efficiency. Option B (data security) is not the primary focus of Einstein Copilot, which is more about improving operational efficiency. Option C (marketing campaigns) falls outside the scope of Service Cloud and Einstein Copilot’s primary benefits, which are aimed at improving customer service and case management. For further reading, refer to Salesforce documentation on Einstein Copilot for Service Cloud and how it improves support processes. 33) What should an AI Specialist consider when using related list merge fields in a prompt template associated with an Account object in Prompt Builder? A. The Activities related list on the Account object is not supported because it is a polymorphic field. B. If person accounts have been enabled, merge fields will not be available for the Account object. C. Prompt generation will yield no response when there is no related list associated with an Account in runtime. Explanation: When using related list merge fields in a prompt template associated with the Account object in Prompt Builder, the Activities related list is not supported due to it being a polymorphic field. Polymorphic fields can reference multiple different types of objects, which makes them incompatible with some merge field operations in prompt generation. Option B is incorrect because person accounts do not limit the availability of merge fields for the Account object. Option C is irrelevant since even if no related lists are available at runtime, the prompt can still generate based on other available data fields. For more information, refer to Salesforce documentation on supported fields and limitations in Prompt Builder. 34) A sales rep at Universal Containers is extremely busy and sometimes will have very long sales calls on voice and video calls and might miss key details. They are just starting to adopt new generative AI features. Which Einstein Generative AI feature should an AI Specialist recommend to help the rep get the details they might have missed during a conversation? A. Call Summary B. Call Explorer C. Sales Summary Explanation: 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. 35) A data scientist needs to view and manage models in Einstein Studio. The data scientist also needs to create prompt templates in Prompt Builder. Which permission sets should an AI Specialist assign to the data scientist? A. Data Cloud Admin and Prompt Template Manager B. Prompt Template Manager and Prompt Template User C. Prompt Template User and Data Cloud Admin Explanation: To allow a data scientist to view and manage models in Einstein Studio and create prompt templates in Prompt Builder, the AI Specialist should assign the Data Cloud Admin and Prompt Template Manager permission sets. Data Cloud Admin provides access to manage and oversee models within Einstein Studio. Prompt Template Manager gives the user the ability to create and manage prompt templates within Prompt Builder. Option Ais correct because it assigns the necessary permissions for both managing models and creating prompt templates. Option B and Option C are incorrect as they do not provide the correct combination of permissions for managing models and building prompts. References: Salesforce Permissions Documentation: https://help.salesforce.com/s/articleView?id=sf.perm_sets_overview.htm https://help.salesforce.com/s/articleView?id=sf.prompt_builder_enable.htm&type=5 36) Universal Containers (UC) has a legacy system that needs to integrate with Salesforce. UC wishes to create a digest of account action plans using the generative API feature. Which API service should UC use to meet this requirement? A. REST API B. Metadata API C. SOAP API Explanation: To create a digest of account action plans using the generative API feature, Universal Containers should use the REST API. The REST API is ideal for integrating Salesforce with external systems and enabling interaction with Salesforce data, including generative capabilities like creating summaries or digests. It supports modern web standards and is suitable for flexible, lightweight interactions between Salesforce and legacy systems. Metadata API is used for retrieving and deploying metadata, not for data operations like generating summaries. SOAP API is an older API used for integration but is less flexible compared to REST for this specific use case. For more details, refer to Salesforce REST API documentation regarding using REST for data integration and generating content. 37) What is an AI Specialist able to do when the “Enrich event logs with conversation data" setting in Einstein Copilot is enabled? A. View the user click path that led to each copilot action. B. View session data including user Input and copilot responses for sessions over the past 7 days. C. Generate details reports on all Copilot conversations over any time period. Explanation: When the "Enrich event logs with conversation data"setting is enabled in Einstein Copilot, it allows an AI Specialist or admin to view session data, including both the user input and copilot responses from interactions over the past 7 days. This data is crucial for monitoring how the copilot is being used, analyzing its performance, and improving future interactions based on past inputs. This setting enriches the event logs with detailed conversational data for better insights into the interaction history, helping AI specialists track AI behavior and user engagement. Option A, viewing the user click path, focuses on navigation but is not part of the conversation data enrichment functionality. Option C, generating detailed reports over any time period, is incorrect because this specific feature is limited to data for the past 7 days. Salesforce AI Specialist References: You can refer to this documentation for further insights: https://help.salesforce.com/s/articleView?id=sf.einstein_copilot_event_logging.htm 38) Universal Containers is using Einstein Copilot for Sales to find similar opportunities to help close deals faster. The team wants to understand the criteria used by the copilot to match opportunities. What is one criteria that Einstein Copilot for Sales uses to match similar opportunities? A. Matched opportunities are limited to the same account. B. Matched opportunities were created in the last 12 months. C. Matched opportunities have a status of Closed Won from last 12 months. Explanation: When Einstein Copilot for Sales matches similar opportunities, one of the primary criteria used is whether the opportunities have a status of Closed Won within 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, review Salesforce Einstein Copilot documentation related to opportunity matching and sales success patterns. 39) An AI Specialist built a Field Generation prompt template that worked for many records, but users are reporting random failures with token limit errors. What is the cause of the random nature of this error? A. The number of tokens generated by the dynamic nature of the prompt template will vary by record. B. The template type needs to be switched to Flex to accommodate the variable amount of tokens generated by the prompt grounding. C. The number of tokens that can be processed by the LLM varies with total user demand. Explanation: The reason behind the token limit errors lies in the dynamic nature of the prompt template used in Field Generation. In Salesforce's AI generative models, each prompt and its corresponding output are subject to a token limit, which encompasses both the input and output of the large language model (LLM). Since the prompt template dynamically adjusts based on the specific data of each record, the number of tokens varies per record. Some records may generate longer outputs based on their data attributes, pushing the token count beyond the allowable limit for the LLM, resulting in token limit errors. This behavior explains why users experience random failures—it is dependent on the specific data used in each case. For certain records, the combined input and output may fall within the token limit, while for others, it may exceed it. This variation is intrinsic to how dynamic templates interact with large language models. Salesforce provides guidance in their documentation, stating that prompt template design should take into account token limits and suggests testing with varied records to avoid such random errors. It does not mention switching to Flex template type as a solution, nor does it suggest that token limits fluctuate with user demand. Token limits are a constant defined by the model itself, independent of external user load. References: Salesforce Developer Documentation on Token Limits for Generative AI Models Salesforce AI Best Practices on Prompt Design (Trailhead or Salesforce blog resources) 40) Universal Containers Is Interested In Improving the sales operation efficiency by analyzing their data using Al-powered predictions in Einstein Studio. Which use case works for this scenario? A. Predict customer sentiment toward a promotion message. B. Predict customer lifetime value of an account. C. Predict most popular products from new product catalog. Explanation: For improving sales operations efficiency, Einstein Studio is ideal for creating AI-powered models that can predict outcomes based on data. One of the most valuable use cases is predicting customer lifetime value, which helps sales teams focus on high-value accounts and make more informed decisions.Customer lifetime value (CLV) predictions can optimize strategies around customer retention, cross-selling, and long-term engagement. Option B is the correct choice as predicting customer lifetime value is a well-established use case for AI in sales. Option A (customer sentiment) is typically handled through NLP models, while Option C (product popularity) is more of a marketing analysis use case. References: Salesforce Einstein Studio Use Case Overview: https://help.salesforce.com/s/articleView?id=sf.einstein_studio_overview 41) An AI Specialist wants to ground a new prompt template with the User related list. What should the AI Specialist consider? A. The User related list should have View All access. B. The User related list needs to be included on the record page. C. The User related list is not supported in prompt templates. Explanation: An AI Specialist wants to ground a new prompt template with the User related list. Grounding in prompt templates involves using data from related lists to provide context or additional information to the Large Language Model (LLM) when generating responses. Key Consideration: Unsupported Related Lists in Prompt Templates: Limitation: TheUser related list is not supported in prompt templates for grounding purposes. Reason: Salesforce restricts certain objects and related lists from being used in prompt templates to maintain data security and integrity. The User object often contains sensitive information and is subject to strict access controls. Impact: Attempting to use the User related list in a prompt template will not work as expected because the system does not support it. Why Options A and B are Incorrect: Option A (The User related list should have View All access): Incorrect: Even with View All access, the User related list is still not supported in prompt templates. Security Concerns: Granting View All access to the User object is a significant security risk and not a recommended practice. Option B (The User related list needs to be included on the record page): Incorrect: Including the User related list on the record page does not affect its availability in prompt templates. Irrelevance: The placement of the related list on the record page does not change the system's ability to access it in a prompt template. References: Salesforce AI Specialist Documentation - Prompt Templates Limitations: Details the objects and related lists that are not supported in prompt templates. Salesforce Help - Data Access in Prompt Templates: Explains how data access and security considerations affect the use of objects in prompt templates. Salesforce Trailhead - Understanding Prompt Template Grounding: Provides insights into grounding prompt templates and the limitations involved. Conclusion: Since the User related list is not supported in prompt templates, the AI Specialist must consider alternative approaches. They might need to redesign the prompt template to use supported objects or related lists, or explore other methods to incorporate necessary user information while adhering to Salesforce's data access policies. 42) When a customer chat is initiated, which functionality in Salesforce provides generative AI replies or draft emails based on recommended Knowledge articles? A. Einstein Reply Recommendations B. Einstein Service Replies C. Einstein Grounding Explanation: 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. References: Einstein Service Replies Overview: https://help.salesforce.com/s/articleView?id=sf.einstein_service_replies.htm 43) An AI Specialist wants to include data from the response of external service invocation (REST API callout) into the prompt template. How should the AI Specialist meet this requirement? A. Convert the JSON to an XML merge field. B. Use External Service Record merge fields. C. Use “Add Prompt Instructions” flow element. Explanation: 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: Definition: External Services in Salesforce allow the integration of external REST APIs into Salesforce without custom code. Registration: The external service must be registered in Salesforce, defining the API's schema and methods. External Service Record Merge Fields: Purpose: Enables the inclusion of data from external service responses directly into prompt templates using merge fields. Functionality: Dynamic Data Inclusion:Allows prompt templates to access and use data returned from REST API callouts. Merge Fields Syntax: Use merge fields in the prompt template to reference specific data points from the API response. Implementation Steps: Register the External Service: UseExternal Servicesto register the REST API in Salesforce. Define the API's schema, including methods and data structures. Create a Named Credential: Configure authentication and endpoint details for the external API. Use External Service in Flow: Build a Flow that invokes the external service and captures the response. Ensure the flow outputs the necessary data for use in the prompt template. Configure the Prompt Template: Use External Service Record merge fields in the prompt template to reference data from the flow's output. Syntax Example: {{flowOutputVariable.fieldName}} Why Other Options are Less Suitable: Option A (Convert the JSON to an XML merge field): Irrelevance: Converting JSON to XML merge fields is unnecessary and complicates the process. Unsupported Method: Salesforce prompt templates do not support direct inclusion of XML merge fields from JSON conversion. Option C (Use “Add Prompt Instructions” flow element): Purpose of Add Prompt Instructions: Allows adding instructions to the prompt within a flow but does not facilitate including external data. Limitation: Does not directly help in incorporating external service responses into the prompt template. References: Salesforce AI Specialist Documentation -Integrating External Services with Prompt Templates: Explains how to use External Services and merge fields in prompt templates. Salesforce Help -Using Merge Fields with External Data: Provides guidance on referencing external data in templates using merge fields. Salesforce Trailhead -External Services and Flow: Offers a practical understanding of integrating external APIs using 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. 44) What is best practice when refining Einstein Copilot custom action instructions? A. Provide examples of user messages that are expected to trigger the action. B. Use consistent introductory phrases and verbs across multiple action instructions. C. Specify the persona who will request the action. Explanation: When refining Einstein Copilot 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 Einstein Copilot documentation on building and refining custom actions. 45) Universal Containers wants to implement a solution in Salesforce with a custom UX that allows users to enter a sales order number. Subsequently, the system will invoke a custom prompt template to create and display a summary of the sales order header and sales order details. Which solution should an AI Specialist implement to meet this requirement? A. Create a screen flow to collect sales order number and invoke the prompt template using the standard "Prompt Template" flow action. B. Create a template-triggered prompt flow and invoke the prompt template using the standard “Prompt Template” flow action. C. Create an autolaunched flow and invoke the prompt template using the standard “Prompt Template" flow action. Explanation: To implement a solution where users enter a sales order number and the system generates a summary, the AI Specialist should create a screen flow to collect the sales order number and invoke the prompt template. The standard "Prompt Template" flow action can then be used to trigger the custom prompt, providing a summary of the sales order header and details. Option B, creating a template-triggered prompt flow, is not necessary for this scenario because the requirement is to directly collect input through a screen flow. Option C, using an autolaunched flow, would be inappropriate here because the solution requires user interaction (entering a sales order number), which is best suited to a screen flow. Salesforce AI Specialist References: For further guidance on creating prompt templates with flows: https://help.salesforce.com/s/articleView?id=sf.prompt_template_flow_integration.htm 46) Which use case is best supported by Salesforce Einstein Copilot’s capabilities? A. Bring together a conversational interface for interacting with AI for all Salesforce users, such as developers and ecommerce retailers B. Enable salesforce admin users to create and train custom large language models (LLMs) using CRM data C. Enable data scientists to train predictive AI models with historical CRM data using built-in machine learning capabilities Salesforce Einstein Copilot is designed to provide a conversational AI interface that can be utilized by different types of Salesforce users, such as developers, sales agents, and retailers. It acts as an AI-powered assistant that facilitates natural interactions with the system, enabling users to perform tasks and access data easily. This includes tasks like pulling reports, updating records, and generating personalized responses in real time. * Option Ais correct because Einstein Copilot brings a conversational interface that caters to a wide range of users. * Option B and Option C are more focused on developing and training AI models, which are not the primary functions of Einstein Copilot. References: * Salesforce Einstein Copilot Overview: https://help.salesforce.com/s/articleView?id=einstein_copilot_overview.htm 47) Universal Containers has an active standard email prompt template that does not fully deliver on the business requirements. Which steps should an AI Specialist take to use the content of the standard prompt email template in question and customize it to fully meet the business requirements? A. Clone the existing template and modify as needed B. Save as new version and edit as needed C. Save as new template and edit as needed You can use the Save As button to create a custom template based on a standard template. 48) Universal containers implemented Einstein Copilot for its users. One user complains that Einstein Copilot is not deleting activities from the past 7 days. What is the reason for this issue? A. Einstein copilot does not support the delete record action B. Einstein copilot does not have the permission to delete the user’s records C. Einstein copilot delete record action permission is not associated to the user 49) Universal containers has seen a high adoption rate of a new feature that uses generative AI to populate a summary field of a custom object, competitor analysis. All sales users have the same profile but one user cannot see the generative AI-enabled field icon next to the summary field. What is the most likely cause of the issue? A. The prompt template associated with summary field is not activated for that user B. The user does not have the field Generative AI user permission set assigned C. The user does not have the Prompt Template User permission set assigned 50) Universal containers wants to utilize Einstein for Sales to help sales reps reach their quotas by providing AI-generated plans containing guidance and steps for closing deals. Which feature should the AI Specialist recommend to the sales team? A. Create Account Plan B. Create Close Plan C. Find Similar Deals The "Create Close Plan" feature is designed to help sales reps by providing AI-generated strategies and steps specifically focused on closing deals. This feature leverages AI to analyze the current state of opportunities and generate a plan that outlines the actions, timelines, and key steps required to move deals toward closure. It aligns directly with the sales team's need to meet quotas by offering actionable insights and structured plans. * Find Similar Deals(Option A) helps sales reps discover opportunities similar to their current deals but doesn't offer a plan for closing. * Create Account Plan(Option B) focuses on long-term strategies for managing accounts, which might include customer engagement and retention, but doesn't focus on deal closure. Salesforce AI Specialist References: For more information on using AI for sales, visit: https://help.salesforce.com/s/articleView?id=sf.einstein_for_sales_overview.htm 51) Universal Containers’ current AI data masking rules do not align with organizational privacy and security policies and requirements. What should an AI Specialist 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. Explanation: When Universal Containers' AI data masking rules do not meet organizational privacy and security standards, the AI Specialist should configure the data masking rules within the Einstein Trust Layer. The Einstein Trust Layer provides 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 the Einstein 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. Salesforce AI Specialist Reference: For more information, refer to: https://help.salesforce.com/s/articleView?id=sf.einstein_trust_layer_data_masking.htm 52) Where should the AI Specialist go to add/update actions assigned to a copilot? A. Copilot Actions page, the record page for the copilot action, or the Copilot Action Library tab B. Copilot Actions page or Global Actions C. Copilot Detail page, Global Actions, or the record page for the copilot action https://help.salesforce.com/s/articleView?id=sf.copilot_actions.htm&type=5 53) An AI Specialist 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 AI Specialist needs to configure the system to use the most accurate and up-to-date information for email generation. Which grounding technique should the AI Specialist use? A. Ground with Apex Merge Fields B. Ground with Record Merge Fields C. Automatic grounding using Draft with Einstein feature 54) Universal Containers wants to use an external large language model (LLM) in Prompt Builder. What should an AI Specialist recommend? A. Use Apex to connect to an external LLM and ground the prompt. B. Use BYO-LLM functionality in Einstein Studio C. Use Flow and External Services to bring data from an external LLM. 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. References: * Salesforce Einstein Studio BYO-LLM Documentation: https://help.salesforce.com/s/articleView?id=sf.einstein_studio_llm.htm 55) An AI Specialist is creating a custom action in Einstein Copilot. Which option is available for the AI Specialist to choose for the custom copilot action? A Apex trigger B SOQL C Flows Explanation: When creating a custom action in Einstein Copilot, one of the available options is to use Flows. Flows are a powerful automation tool in Salesforce, allowing the AI Specialist to define custom logic and actions within the Copilot system. This makes it easy to extend Copilot's functionality without needing custom code. While Apex triggers and SOQL are important Salesforce tools, Flows are the recommended method for creating custom actions within Einstein Copilot because they are declarative and highly adaptable. For further guidance, refer to Salesforce Flow documentation and Einstein Copilot customization resources. 56) Universal Containers (UC) wants to assess Salesforce's generative features but has concerns over its company data being exposed to third- party large language models (LLMs). Specifically, UC wants the following capabilities to be part of Einstein's generative AI service. No data is used for LLM training or product improvements by third- party LLMs. No data is retained outside of UC's Salesforce org. The data sent cannot be accessed by the LLM provider. Which property of the Einstein Trust Layer should the AI Specialist highlight to UC that addresses these requirements? A Prompt Defense B Zero-Data Retention Policy C Data Masking Explanation: Universal Containers (UC) has concerns about data privacy when using Salesforce's generative AI features, particularly around preventing third-party LLMs from accessing or retaining their data. The Zero-Data Retention Policy in the Einstein Trust Layer is designed to address these concerns by ensuring that: No data is used for training or product improvements by third-party LLMs. No data is retained outside of the customer's Salesforce organization. The LLM provider cannot access any customer data. This policy aligns perfectly with UC's requirements for keeping their data safe while leveraging generative AI capabilities. Prompt Defense and Data Masking are also security features, but they do not directly address the concerns related to third-party data access and retention. 57) What is the correct process to leverage Prompt Builder in a Salesforce org? A Select the appropriate prompt template type to use, select one of Salesforce's standard prompts, determine the object to associate the prompt, select a record to validate against, and associate the prompt to an action. B Select the appropriate prompt template type to use, develop the prompt within the prompt workspace, select resources to dynamically insert CRM-derived grounding data, pick the model to use, and test and validate the generated responses. C Enable the target object for generative prompting, develop the prompt within the prompt workspace, select records to fine-tune and ground the response, enable the Trust Layer, and associate the prompt to an action. Explanation: When using Prompt Builder in a Salesforce org, the correct process involves several important steps: Select the appropriate prompt template type based on the use case. Develop the prompt within the prompt workspace, where the template is created and customized. Select CRM-derived grounding data to be dynamically inserted into the prompt, ensuring that the AI-generated responses are based on accurate and relevant data. Pick the model to use for generating responses, either using Salesforce's built-in models or custom ones. Test and validate the generated responses to ensure accuracy and effectiveness. Option B is correct as it follows the proper steps for using Prompt Builder. Option A and Option C do not capture the full process correctly. Salesforce Prompt Builder Documentation: https://help.salesforce.com/s/articleView?id=sf.prompt_builder_overview.htm 58) Universal Containers (UC) wants to enable its sales reps to explore opportunities that are similar to previously won opportunities by entering the utterance, "Show me other opportunities like this one." How should UC achieve this in Einstein Copilot? A. Use the standard Copilot action. B. Create a custom Copilot action calling a flow. C. Create a custom Copilot action calling an Apex class. 59) Leadership needs to populate a dynamic form field with a summary or description created by a large language model (LLM) to facilitate more productive conversations with customers. Leadership also wants to keep a human in the loop to be considered in their AI strategy. Which prompt template type should the AI Specialist recommend? A. Sales Email B. Field Generation C. Record Summary Explanation: 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-in-the-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. Salesforce AI Specialist Reference: You can explore more about these prompt templates and AI capabilities through Salesforce documentation and official resources on Prompt Builder: https://help.salesforce.com/s/articleView?id=sf.prompt_builder_templates_overview.htm 60) Universal Containers plans to implement prompt templates that utilize the standard foundation models. What should the AI Specialist consider when building prompt templates in Prompt Builder? A. Include multiple-choice questions within the prompt to test the LLM's understanding of the context. B. Ask it to role-play as a character in the prompt template to provide more context to the LLM. C. Train LLM with data using different writing styles including word choice, intensifiers, emojis, and punctuation. https://admin.salesforce.com/blog/2024/the-ultimate-guide-to-prompt-builder-spring-24 61) Universal Containers is considering leveraging the Einstein Trust Layer in conjunction with Einstein Generative AI Audit Data. Which audit data is available using the Einstein Trust Layer? A. Response accuracy and offensiveness score B. Hallucination score and bias score C. Masked data and toxicity score Explanation: Universal Containers is considering the use of the Einstein Trust Layer along with Einstein Generative AI Audit Data. The Einstein Trust Layer provides a secure and compliant way to use AI by offering features like data masking and toxicity assessment. The audit data available through the Einstein Trust Layer includes information about masked data— which ensures sensitive information is not exposed—and the toxicity score, which evaluates the generated content for inappropriate or harmful language. Reference: Salesforce AI Specialist Documentation - Einstein Trust Layer: Details the auditing capabilities, including logging of masked data and evaluation of generated responses for toxicity to maintain compliance and trust. 62) What is the main purpose of Prompt Builder? A. A tool within Salesforce offering real-time Al-powered suggestions and guidance to users, Improving productivity and decision-making. B. A tool for developers to use in Visual Studio Code that creates prompts for Apex programming, assisting developers in writing code more efficiently. C. A tool that enables companies to create reusable prompts for large language models (LLMs), bringing generative AI responses to their flow of work 63) Universal Containers (UC) is experimenting with using public Generative AI models and is familiar with the language required to get the information it needs. However, it can be time consuming for both UC's sales and service reps to type in the prompt to get the information they need, and ensure prompt consistency. Which Salesforce feature should a Salesforce AI Specialist recommend to address these concerns? A. Einstein Prompt Builder and Prompt Templates B. Einstein Copilot Action: Query Records C. Einstein Recommendation Builder 64) How does the Einstein Trust Layer ensure that sensitive data is protected while generating useful and meaningful responses? A. Masked data will be de-masked during request journey. B. Responses that do not meet the relevance threshold will be automatically rejected. C. Masked data will be de-masked during response journey. https://help.salesforce.com/s/articleView?id=sf.generative_ai_mask_data.htm&type=5 65) An AI Specialist needs to create a Sales Email with a custom prompt template. They need to ground on the following data. Opportunity Products Events near the customer Tone and voice examples How should the AI Specialist obtain related items? A. Call prompt initiated flow to fetch and ground the required data. B. Utilize a standard email template and manually insert the required data fields. C. Create a flex template that takes the records in question as inputs. 66) Universal Containers (UC) wants to enable its sales team with automatic post-call visibility into mention of competitors, products, and other custom phrases. Which feature should the AI Specialist set up to enable UC's sales team? A. Call Summaries B. CallExplorer C. Call Insights To enable Universal Containers' sales team with automatic post-call visibility into mentions of competitors, products, and custom phrases, the AI Specialist should set up Call Insights. Call Insights analyzes voice and video calls for key phrases, topics, and mentions, providing insights into critical aspects of the conversation. This feature automatically surfaces key details such as competitor mentions, product discussions, and custom phrases specified by the sales team. * Call Summaries provide a general overview of the call but do not specifically highlight keywords or topics. * Call Explorer is a tool for navigating through call data but does not focus on automatic insights. For more information, refer toSalesforce's Call Insights documentation regarding the analysis of call content and extracting actionable information. 67) An AI Specialist needs to create a prompt template to fill a custom field named Latest Opportunities Summary on the Account object with information from the three most recently opened opportunities. How should the AI Specialist gather the necessary data for the prompt template? A. Create a flow to retrieve the opportunity information. B. Select the Account Opportunity object as a resource when creating the prompt template. C. Select the latest Opportunities related list as a merge field. To gather the necessary data for populating the Latest Opportunities Summarycustom field on the Account object with information from the three most recently opened opportunities, the AI Specialist should create a flow. A flow can be configured to query and retrieve the required opportunity records based on criteria such as their open date. Once the flow has gathered the necessary data, it can be used in a prompt template or other automation processes to populate the custom field on the Account record. * Option Ais correct because creating a flow allows for dynamic data retrieval and control over the logic for selecting the most recent opportunities. * Option B and Option C do not provide sufficient control or data retrieval capabilities needed for this scenario. References: * Salesforce Flow Documentation:https://help.salesforce.com/s/articleView?id=sf.flow.htm 68) Universal Containers needs a tool that can analyze voice and video call records to provide insights on competitor mentions, coaching opportunities, and other key information. The goal is to enhance the team's performance by identifying areas for improvement and competitive intelligence. Which feature provides insights about competitor mentions and coaching opportunities? A. Call Summaries B. Einstein Sales Insights C. Call Explorer For analyzing voice and video call records to gain insights into competitor mentions, coaching opportunities, and other key information, Call Explorer is the most suitable feature. Call Explorer, a part of Einstein Conversation Insights, enables sales teams to analyze calls, detect patterns, and identify areas where improvements can be made. It uses natural language processing (NLP) to extract insights, including competitor mentions and moments for coaching. These insights are vital for improving sales performance by providing a clear understanding of the interactions during calls. * Call Summaries offer a quick overview of a call but do not delve deep into competitor mentions or coaching insights. * Einstein Sales Insightsfocuses more on pipeline and forecasting insights rather than call-based analysis. References: * Salesforce Einstein Conversation Insights Documentation:https://help.salesforce.com/s/articleView? id=einstein_conversation_insights.htm 69) An AI Specialist turned on Einstein Generative AI in Setup. Now, the AI Specialist would like to create custom prompt templates in Prompt Builder. However, they cannot access Prompt Builder in the Setup menu. What is causing the problem? A. The Prompt Template User permission set was not assigned correctly. B. The Prompt Template Manager permission set was not assigned correctly. C. The large language model (LLM) was not configured correctly in Data Cloud. In order to access and create custom prompt templates in Prompt Builder, the AI Specialist must have the Prompt Template Manager permission set assigned. Without this permission, they will not be able to access Prompt Builder in the Setup menu, even though Einstein Generative AI is enabled. * Option Bis correct because the Prompt Template Manager permission set is required to use Prompt Builder. * Option A(Prompt Template User permission set) is incorrect because this permission allows users to use prompts, but not create or manage them. * Option C(LLM configuration in Data Cloud) is unrelated to the ability to access Prompt Builder. References: * Salesforce Prompt Builder Permissions: https://help.salesforce.com/s/articleView?id=sf.prompt_builder_permissions.htm 70) Universal Containers wants to reduce overall agent handling time 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 Einstein for Service features enables this effort? A. Einstein Service Replies and Work Summaries B. Einstein Reply Recommendations and Case Summaries C. Einstein Reply Recommendations and Case Classification Universal Containers aims to reduce overall agent handling time by minimizing the time agents spend typing routine answers for common questions during chats and by reducing post-chat analysis through suggesting values for case fields. To achieve these objectives, the combination ofEinstein Reply RecommendationsandCase Classificationis the most appropriate solution. 1. Einstein Reply Recommendations: * Purpose:Helps agents respond faster during live chats by suggesting the best responses based on historical chat data and common customer inquiries. * Functionality: * Real-Time Suggestions:Provides agents with a list of recommended replies during a chat session, allowing them to quickly select the most appropriate response without typing it out manually. * Customization:Administrators can configure and train the model to ensure the recommendations are relevant and accurate. * Benefit:Significantly reduces the time agents spend typing routine answers, thus improving efficiency and reducing handling time. 2. Case Classification: * Purpose:Automatically suggests or populates values for case fields based on historical data and patterns identified by AI. * Functionality: * Field Predictions:Predicts values for picklist fields, checkbox fields, and more when a new case is created. * Automation:Can be set to auto-populate fields or provide suggestions for agents to approve. * Benefit:Reduces the time agents spend on post-chat analysis and data entry by automating the classification and field population process. Why Options A and B are Less Suitable: * Option A (Einstein Service Replies and Work Summaries): * Einstein Service Replies:Similar to Reply Recommendations but typically used for email and not live chat. * Work Summaries:Provides summaries of customer interactions but does not assist in field value suggestions. * Option B (Einstein Reply Recommendations and Case Summaries): * Case Summaries:Generates a summary of the case details but does not help in suggesting field values. References: * Salesforce AI Specialist Documentation -Einstein Reply Recommendations: * Details how Reply Recommendations assist agents in providing quick responses during live chats. * Salesforce AI Specialist Documentation -Einstein Case Classification: * Explains how Case Classification predicts and suggests field values to streamline case management. * Salesforce Trailhead -Optimize Service with AI: * Provides an overview of AI features that enhance service efficiency. 71) Universal Containers (UC) wants to use Flow to bring data from unified Data Cloud objects to prompt templates. Which type of flow should UC use? A. Data Cloud-triggered flow B. Template-triggered prompt flow C. Unified-object linking flow In this scenario, Universal Containers wants to bring data from unified Data Cloud objects into prompt templates, and the best way to do that is through a Data Cloud-triggered flow. This type of flow is specifically designed to trigger actions based on data changes within Salesforce Data Cloud objects. Data Cloud-triggered flows can listen for changes in the unified data model and automatically bring relevant data into the system, making it available for prompt templates. This ensures that the data is both real-time and up-to-date when used in generative AI contexts. For more detailed guidance, refer to Salesforce documentation on Data Cloud-triggered flows and Data Cloud integrations with generative AI solutions. 72) An AI Specialist configured Data Masking within the Einstein Trust Layer. How should the AI Specialist begin validating that the correct fields are being masked? A. Use a Flow-based resource in Prompt Builder to debug the fields' merge values using Flow Debugger. B. Request the Einstein Generative AI Audit Data from the Security section of the Setup menu. C. Enable the collection and storage of Einstein Generative AI Audit Data on the Einstein Feedback setup page. To begin validating that the correct fields are being masked in Einstein Trust Layer, the AI Specialist should request the Einstein Generative AI Audit Data from the Security section of the Salesforce Setup menu. This audit data allows the AI Specialist to see how data is being processed, including which fields are being masked, providing transparency and validation that the configuration is working as expected. * Option B is correct because it allows for the retrieval of audit data that can be used to validate data masking. * Option A(Flow Debugger) and Option C(Einstein Feedback) do not relate to validating field masking in the context of the Einstein Trust Layer. References: * Salesforce Einstein Trust Layer Documentation: https://help.salesforce.com/s/articleView?id=sf.einstein_trust_layer_audit.htm 73) Universal Containers recently launched a pilot program to integrate conversational AI into its CRM business operations with Einstein Copilot. How should the AI Specialist monitor Copilot's usability and the assignment of actions? A. Run a report on the Platform Debug Logs. B. Query the Copilot log data using the metadata API. C. Run Einstein Copilot Analytics. 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. 74) Universal Containers' data science team is hosting a generative large language model (LLM) on Amazon Web Services (AWS). What should the team use to access externally-hosted models in the Salesforce Platform? A. Model Builder B. App Builder C. Copilot Builder To access externally-hosted models, such as a large language model (LLM) hosted on AWS, the Model Builder in Salesforce is the appropriate tool. Model Builder allows teams to integrate and deploy external AI models into the Salesforce platform, making it possible to leverage models hosted outside of Salesforce infrastructure while still benefiting from the platform's native AI capabilities. * Option B, App Builder, is primarily used to build and configure applications in Salesforce, not to integrate AI models. * Option C, Copilot Builder, focuses on building assistant-like tools rather than integrating external AI models. Model Builder enables seamless integration with external systems and models, allowing Salesforce users to use external LLMs for generating AI-driven insights and automation. Salesforce AI Specialist References: For more details, check the Model Builder guide here: https://help.salesforce.com/s/articleView?id=sf.model_builder_external_models.htm 75) What is the primary function of the planner service in the Einstein Copilot system? A. Generating record queries based on conversation history B. Offering real-time language translation during conversations C. Identifying copilot actions to respond to user utterances The primary function of the planner service in the Einstein Copilot system is to identify copilot actions that should be taken in response to user utterances. This service is responsible for analyzing the conversation and determining the appropriate actions (such as querying records, generating a response, or taking another action) that the Einstein Copilot should perform based on user input. 76) 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. For Universal Containers (UC) to refine its Generative AI prompt design strategy and improve the accuracy of the generated summaries for the custom object Guest, the best practice is to focus on crafting concise, 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. References: * Salesforce Prompt Design Best Practices: https://help.salesforce.com/s/articleView?id=sf.prompt_design_best_practices.htm 77) What is the role of the large language model (LLM) in executing an Einstein Copilot Action? A. Find similar requests and provide actions that need to be executed B. Identify the best matching actions and correct order of execution C. Determine a user's access and sort actions by priority to be executed In Einstein Copilot, the role of the Large Language Model (LLM) is to analyze user inputs and identify the best matching actions that need to be executed. It uses natural language understanding to break down the user' s request and determine the correct sequence of actions that should be performed. By doing so, the LLM ensures that the tasks and actions executed are contextually relevant and are performed in the proper order. This process provides a seamless, AI-enhanced experience for users by matching their requests to predefined Salesforce actions or flows. The other options are incorrect because: A mentions finding similar requests, which is not the primary role of the LLM in this context. C focuses on access and sorting by priority, which is handled more by security models and governance than by the LLM. References: Salesforce Einstein Documentation on Einstein Copilot Actions Salesforce AI Documentation on Large Language Models 78) Universal Containers wants to be able to detect with a high level confidence if content generated by a large language model (LLM) contains toxic language. Which action should an Al Specialist take in the Trust Layer to confirm toxicity is being appropriately managed? A. Access the Toxicity Detection log in Setup and export all entries where isToxicityDetected is true. B. Create a flow that sends an email to a specified address each time the toxicity score from the response exceeds a predefined threshold. C. Create a Trust Layer audit report within Data Cloud that uses a toxicity detector type filter to display toxic responses and their respective scores. 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 within 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 Cis correct because it enables visibility into toxic language detection within 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. References: * Salesforce Trust Layer Documentation: https://help.salesforce.com/s/articleView?id=sf.einstein_trust_layer_audit.htm 79) How should an organization use the Einstein Trust layer to audit, track, and view masked data? A. Utilize the audit trail that captures and stores all LLM submitted prompts in Data Cloud. B. In Setup, use Prompt Builder to send a prompt to the LLM requesting for the masked data. C. Access the audit trail in Setup and export all user-generated prompts. The Einstein Trust Layer is designed to ensure transparency, compliance, and security for organizations leveraging Salesforce's AI and generative AI capabilities. Specifically, for auditing, tracking, and viewing masked data, organizations can utilize: * Audit Trail in Data Cloud: The audit trail captures and stores all prompts submitted to large language models (LLMs), ensuring that sensitive or masked data interactions are logged. This allows organizations to monitor and audit all AI-generated outputs, ensuring that data handling complies with internal and regulatory guidelines. The Data Cloud provides the infrastructure for managing and accessing this audit data. * Why not B? Using Prompt Builder in Setup to send prompts to the LLM is for creating and managing prompts, not for auditing or tracking data. It does not interact directly with the audit trail functionality. * Why not C? Although the audit trail can be accessed in Setup, the user-generated prompts are primarily tracked in the Data Cloud for broader control, auditing, and analysis. Setup is not the primary tool for exporting or managing these audit logs. More information on auditing AI interactions can be found in the Salesforce AI Trust Layer documentation, which outlines how organizations can manage and track generative AI interactions securely. 80) Universal Containers' service team wants to customize the standard case summary response from Einstein Copilot. What should the AI Specialist do to achieve this? A. Customize the standard Record Summary template for the Case object, B. Summarize the Case with a standard copilot action. C. Create a custom Record Summary prompt template for the Case object. To customize the case summary response from Einstein Copilot, the AI Specialist should create a custom Record Summary prompt template for the Case object. This allows Universal Containers to tailor the way case data is summarized, ensuring the output aligns with specific business requirements or user preferences. * Option A(customizing the standard Record Summary template) does not provide the flexibility required for deep customization. * Option B(standard Copilot action) won't allow customization; it will only use default settings. Refer to Salesforce Prompt Builder documentation for guidance on creating custom templates for record summaries. 81) Universal Containers is planning a marketing email about products that most closely match a customer's expressed interests. What should an AI Specialist recommend to generate this email? A. Standard email marketing template using Apex or flows for matching interest in products B. Custom sales email template which is grounded with interest and product information C. Standard email draft with Einstein and choose standard email template To generate an email about products that closely match a customer's expressed interests, an AI Specialist should recommend using a custom sales email template that is grounded with interest and product information. This ensures that the email content is personalized based on the customer's preferences, increasing the relevance of the marketing message. Using grounding ensures that the generative AI pulls the correct data related to customer interests and product matches, making the email more effective. For more information, refer to Salesforce documentation on grounding AI-generated content and email personalization strategies. 82) A support team handles a high volume of chat interactions and needs a solution to provide quick, relevant responses to customer inquiries. Responses must be grounded in the organization's knowledge base to maintain consistency and accuracy. Which feature in Einstein for Service should the support team use? A. Einstein Service Replies B. Einstein Reply Recommendations C. Einstein Knowledge Recommendations The support team should use Einstein Reply Recommendations to provide quick, relevant responses to customer inquiries that are grounded in the organization's knowledge base. This feature leverages AI to recommend accurate and consistent replies based on historical interactions and the knowledge stored in the system, ensuring that responses are aligned with organizational standards. * Einstein Service Replies (Option A) is focused on generating replies but doesn't have the same emphasis on grounding responses in the knowledge base. * Einstein Knowledge Recommendations (Option C) suggests knowledge articles to agents, which is more about assisting the agent in finding relevant articles than providing automated or AI-generated responses to customers. Salesforce AI Specialist References: For more information on Einstein Reply Recommendations: https://help.salesforce.com/s/articleView?id=sf.einstein_reply_recommendations_overview.htm 83) When configuring a prompt template, an AI Specialist previews the results of the prompt template they've written. They see two distinct text outputs: Resolution and Response. Which information does the Resolution text provide? A. It shows the full text that is sent to the Trust Layer. B. It shows the response from the LLM based on the sample record. C. It shows which sensitive data is masked before it is sent to the LLM. When previewing a prompt template in Salesforce, the Resolution text provides the response 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 B is correct because Resolution displays the actual response generated by the LLM. Option A refers to sending the text to the Trust Layer, but that's not what Resolution represents. Option C relates to data masking, which is shown elsewhere, not under Resolution. Salesforce Prompt Builder Overview: https://help.salesforce.com/s/articleView?id=sf.prompt_builder_overview.htm 84) Universal Containers (UC) has a mature Salesforce org with a lot of data in cases and Knowledge articles. Uc is concerned that there are many legacy fields, with data that might not be applicable for Einstein AI to draft accurate email responses. Which solution should UC use to ensure Einstein AI can draft resposes from a defined data source? A. Service Replies B. Service AI Grounding C. Work Summaries 85) The marketing team at Universal Containers is looking for a way personalize emails based on customer behavior, preferences, and purchase history. Why should the team use Einstein Copilot as the solution? A. To generate relevant content when engaging with each customer B. To analyze past campaign performance C. To send automated emails to all customers 86) A service agent is looking at a custom object that stores travel information. They recently received a weather alert and now need to cancel flights for the customers that are related with this itinerary. The service agent needs to review the Knowledge articles about cancelling and rebooking the customer flights. Which Einstein Copilot capability helps the agent accomplish this? A. Execute tasks based on available actions, answering questions using information from accessible knowledge articles B. Invoke a flow which makes a call to external data to create a knowledge article C. Generate a knowledge article based off the prompts that the agent enters to create steps to cancel flights 87) An AI Specialist at Universal Containers is working on a prompt template to generate personalized emails for product demonstration requests from customers. It is important for the AI-generated email to adhere strictly to the guidelines, using only associated opportunity information, and to encourage the recipient to take the desired action. How should the AI Specialist include these instructions on a new line in the prompt template? A. Surround them with triple quotes (“””) B. Make sure merged fields are defined C. Use curly bracket {} to encapsulate instructions 88) An AI Specialist wants to use the related lists from an account in a custom prompt template. What should the AI Specialist consider when configuring the prompt template? A. The text encoding (for example, UTF-8, ASCII) option B. The maximum number of related list merge fields C. The choice between XML and JSON rendering formats for the list 89) An AI Specialist has created a copilot custom action using flow as the reference action type. However, it is not delivering the expected results to the conversation preview, and therefore needs troubleshooting. What should the AI Specialist do to identify the root cause of the problem? A. In Copilot Builder within the Dynamic Panel, turn on dynamic debugging to show the inputs and outputs. B. Copilot Builder within the Dynamic Panel, confirm selected action and observe the values in Input and Output sections. C. In Copilot Builder, verify the utterance entered by the user and review session event logs for debug information 90) Universal Containers (UC) wants to create a new Sales Email prompt template in Prompt Builder using the “Save As” function. However, UC notices that the new template produces different results compared to the standard Sales Email prompt due to missing hyperparameters. What should UC do to ensure the new prompt template produces results comparable to the standard Sales Email prompts? A. Use Model Playground to create a model configuration with the specified parameters B. Manually add the hyperparameters to the new template C. Revert to using the standard template without modifications 91) An administrator wants to check the response of the Flex prompt template they’ve built, but the preview button is greyed out. What is the reason for this? A. The records related to the prompt have not been selected B. The prompt has not been saved and activated C. A merge field has not been inserted in the prompt 92) Universal Containers (UC) recently rolled out Einstein Generative capabilities and has creat

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