Salesforce Prompt Builder & Agent Deployment

• To leverage Prompt Builder in Salesforce, select the appropriate prompt template type, develop the prompt within the prompt workspace, select resources for dynamically inserting CRM-derived grounding data, pick the model, and test/validate responses.

Agentforce Agent Deployment Options

• Deploy flows, Apex, and agent-related items using change sets or the Salesforce CLI/Metadata API.
• If a required field is missing during the setup of a retriever for PDF file ingestion in Data Cloud, update the search index to include the desired field.
• If agent answers are unsatisfactory when using PDF files as a knowledge source, verify the retriever's filter criteria and data source connection.
• When using Record Snapshots grounding, create a field set for all the fields to be grounded in a prompt template.
• Use Call Insights to enable the sales team with automatic post-call visibility into mentions of competitors, products, and custom phrases.
• Assign the Prompt Template Manager and Prompt Template User permission sets to users who need to create and execute prompt templates.

Consideration When Using Record Snapshots

• Note that empty data (fields without values or sections without limits) is filtered out.
• To optimize the retriever configuration for quickly returning AI agent responses, prioritize increasing the recency bias setting.
• Employ Einstein Reply Recommendations for quick, relevant, and grounded responses to high-volume chat interactions, maintaining consistency and accuracy.
• The AI retriever function within Data Cloud performs contextual searches over an indexed repository to fetch the most relevant documents, enabling grounding AI responses with trustworthy and verifiable information.
• Data Cloud stores and manages the indexed Knowledge articles for the Answer Questions with Knowledge action in Agentforce.
• Agentforce Testing Center does not consume Einstein Requests when running tests.
• REST API should be used to create a digest of account action plans using the generative API feature.
• Assign the Run Flows permission to the Agentforce Agent user to ensure the Agentforce Service Agent can run a new flow as part of a new Agent Action.
• To ensure an Agentforce Service Agent retrieves the right information, set up an Agentforce Data Library to store and index policy documents for AI retrieval.
• The 'Query Records' standard Agent action will be used by the planner service based on the user utterance, 'Show me all the customers in New York'.
• Ensure the assigned User permission set includes access to the prompt template used to access the Knowledge articles when testing Agent Builder and Experience Cloud site configurations.
• Prompt Builder best suits contacting leads at scale with hyper-relevant solutions and customized communications in the most efficient manner possible.
• For an Agentforce Agent User change to to address issues related to a new product replacement process assign the permission set so the agent user needs read access to the custom Product Replacement object
• A missing "Use SDR Agent" permission set is preventing sales reps from finding the new Agentforce Sales Development Representative (SDR) in production.
• When creating a custom action for Agentforce, test and iterate on Action Input to ensure the action performs as expected.
• A large language model (LLM) identifies the best matching topic and actions and the correct order of execution when understanding intent and executing an Agent Action.
• The preview button may be grayed out on checking the response of a Flex prompt template if the prompt has not been saved and activated.
• Sales reps can use the standard Agent action to explore opportunities similar to previously won opportunities.
• The Einstein Reply Recommendations functionality in Salesforce provides generative AI replies or draft emails based on recommended Knowledge articles when a customer chat is initiated.
• Create a custom Agent action to leverage a natural language service agent to query the current fulfillment status of an order with an existing autolaunched flow.
• A custom sales email template which is grounded with interest and product information should be used to generate a marketing email about products that most closely match a customer's expressed interests.
• One user does not see the generative AI-enabled field icon, the user does not have the Prompt Template User permission set assigned.
• The Data Retriever can be reconfigured to use a different data source.
• Flow should use Template-triggered prompt flow to bring data from unified Data Cloud objects to prompt templates.
• Before activating a custom Agent action, it is important to understand multiple real-world user utterances to ensure the action is being selected appropriately, Agent Builder is the tool to recommend.
• A scenario is that an AI agent must provide answers based on a curated set of policy documents that are stored, regularly updated, and indexed in the data library can be demonstrated by Agentforce Data Library.
• The Messaging Session object stores the conversation transcript between the customer and the agent.
• Review the Action Instructions to ensure they are unique when users are complaining that they are not getting the right summary based on their utterances.
• Apex classes must have at least 75% code coverage from unit tests, and all dependencies must be in the deployment package.
• For a new Einstein Generative AI feature for its sales team to create personalized and contextualized emails for its customers, with attributes that could have been derived from the recipient's contact record, the user does not have permission to access the fields.
• The 'Agent Action: Draft or Revise Sales Email' standard Agent action helps sales reps draft personalized emails to prospects by generating text based on previous successful communications
• Leadership needs to populate a dynamic form field by the Record Summary which is created by a large language model LLM
• Agentforce Data Library simplifies and enables the AI agent automates the ingestion and optical character recognition (OCR) processing of any PDF, and indexes them to enable regular SQL query retrieval to ground prompts and agents with relevant information
• Assign the action to a Topic first in Agent Builder for the salesforce Agentforce Platform.
• Deploy the agent in a Q/A sandbox environment and review Utterance Analysis reports to review effectiveness to ensure its effectiveness.
• The primary function of the reasoning engine in Agentforce is to identify agent topics and actions to respond to user utterances.
• Agentforce SDR only works with the standard Lead object.
• The way UC can utilize data from five unrelated objects using a flex template and use the five objects as inputs.
• The grounding technique to be used Use merge fields to reference the default related list of opportunities.
• Data preparation involves loading, chunking, vectorizing, and storing content in a search-optimized manner to support retrieval from the vector database
• To monitor Agents usability and the assignment of actions, the Agentforce specialist should run Agent Analytics.
• In refining its prompt design strategy, key practices UC prioritize are creating concise, clear, and consistent prompt templates with effective grounding, contextual role-playing, clear instructions, and iterative feedback.
• To add the sparkle icon, forgot to Reactivate the lightning page layout.
• Define filters to narrow the search results based on specific conditions.
• After configuring and saving a salesforce agentforce Data Library (regardless of the data source), the data stream, the search index, and a retriever components are automatically created and available in Data Cloud.
• The main benefit of using a Knowledge article in an Agentforce Data Library is that it provides a structured, searchable repository of approved documents so the agent can retrieve reliable information for each inquiry.
• The cause is that Salesforce Knowledge is not enabled in the organization for libraries or bases.
• Outbound Omni-Channel Flow is the tool that connects the service agent to the human agent queue for escalation/routing.
• When the 'Enrich event logs with conversation data' setting in the Agentforce configuration is enabled the specialist can "view session data including user input and Agent responses for sessions over the past 7 days."
• The large language model LLM interprets the user's request, generates a plan by identifying the appropriate topics and actions, and executes the actions to retrieve and display the open opportunities.
• Use the prompt builder to create a draft of a support bulletin post for new product patches
• a sales Email prompt template be used as the solution approach which should the admin leverage for the creation of different products.
• The number of tokens generated by the dynamic nature of the prompt template will vary by record the random nature of the report errors