Salesforce Agentforce-Specialist Test Dumps

C.   Turn on Service AI Grounding and Grounding with Knowledge.

C.   Enable audit trail in the Einstein Trust Layer.

Answer Description
Explanation

To addresssecurity complianceconcerns and provide visibility into theprompt text sent to the LLM, how it ismasked, and themasked response, theAgentforce Specialistshould recommend enabling theaudit 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 toSalesforce's Einstein Trust Layer documentationabout auditing and security measures.

B.   Ask it to role-play as a character in the prompt template to provide more context to the LLM.

Answer Description
Explanation

Comprehensive and Detailed In-Depth Explanation:UC is using Prompt Builder with standard foundation models (e.g., via Atlas Reasoning Engine). Let’s assess best practices for prompt design.
Option A: Include multiple-choice questions within the prompt to test the LLM’sunderstanding of the context.Prompt templates are designed to generate responses, not to test the LLM with multiple- choice questions. This approach is impractical and not supported by Prompt Builder’s purpose, making it incorrect.
Option B: Ask it to role-play as a character in the prompt template to provide more context to the LLM.A key consideration in Prompt Builder is crafting clear, context-rich prompts. Instructing the LLM to adopt a role (e.g., “Act as a sales expert”) enhances context and tailors responses to UC’s needs, especially with standard models. This is a documented best practice for improving output relevance, making it the correct answer.
Option C: Train LLM with data using different writing styles including word choice, intensifiers, emojis, and punctuation.Standard foundation models in Agentforce are pretrained and not user- trainable. Prompt Builder users refine prompts, not the LLM itself, making this incorrect.
Why Option B is Correct:Role-playing enhances context for standard models, a recommended technique in Prompt Builder for effective outputs, as per Salesforce guidelines.

B.   Safe

Answer Description
Explanation

In theEinstein Trust Layer, thetoxicity scoringsystem 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 1indicates that the content is deemedsafe.
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 theEinstein Trust Layer.
For further reference, check Salesforce’s official Einstein Trust Layer documentationregardingtoxicity scoringfor AI-generated content.

A.   Model Builder

Answer Description
Explanation

To accessexternally-hosted models, such as a large language model (LLM) hosted on AWS, the Model Builderin Salesforce is the appropriate tool.Model Builderallows 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.

B.   Service Replies

Answer Description
Explanation

Service Replies: This generative AI feature automates and assists in generating accurate, contextual, and efficient replies for customer service agents. It uses past interactions, case data, and the context of the conversation to provide draft responses, thereby enhancing productivity and reducing response times.
Case Summaries: Summarizes case information but does not assist directly in replying to customer chats.
Case Escalation: Refers to moving cases to higher-level support teams but does not address the need to improve chat response productivity.
Thus,Service Repliesis the best feature for this requirement as it directly aligns with improving agent efficiency in replying to chats.

C.   To streamline the sales process and increase conversion rates

Answer Description
Explanation

Agentforce Sales Agent provides real-time insights and AI-powered recommendations, which are designed to streamline the sales processand help sales representatives focus on key tasks to increase conversion rates. It offers features like lead scoring, opportunity prioritization, and proactive recommendations, ensuring that sales teams can interact with customers efficiently and close deals faster.
Option A: While tracking customer interactions is beneficial, it is only part of the broader capabilities offered by Agentforce Sales Agent and is not the primary objective for improving real-time productivity.
Option B: Agentforce Sales Agent does not automate the entire sales process but provides actionable recommendations to assist the sales team.
Option C: This aligns with the tool's core purpose of enhancing productivity and driving sales success.

C.   Assign the action to a Topic first on Action Builder.