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| Section | Weight | Objectives |
|---|---|---|
| Reasoning Engine & AI Actions | - Workflow mastery
| |
| Einstein Trust Layer & Security | - Data Masking
| |
| Prompt Engineering | 30% | - Agentforce AI Setup & Configuration
|
| Agent Force Concepts | 30% | - Data Cloud & Grounding Techniques
|
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NEW QUESTION # 26
Universal Containers is planning a marketing email about products that most closely match a customer's expressed interests. What should An Agentforce recommend to generate this email?
Answer: A
Explanation:
To generate an email about products that closely match a customer's expressed interests, An Agentforce 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.
NEW QUESTION # 27
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?
Answer: B
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.
NEW QUESTION # 28
Universal Containers wants to allow its service agents to query the current fulfillment 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 fulfillment process. How should an Agentforce Specialist apply the power of conversational AI to this use case?
Answer: C
Explanation:
Why is "Create a custom Agent action which calls a flow" the correct answer?
In Agentforce, the best way to allow service agents to query order fulfillment status from an external system (Oracle ERP) using natural language is to create a custom Agent action that invokes an existing autolaunched flow.
Key Considerations for This Approach:
Custom Agent Action Triggers the Flow
A custom Agent action is designed to call Salesforce flows, enabling external system integration.
The flow retrieves real-time fulfillment data from Oracle ERP and returns results to the agent.
Enables AI-Powered Query Execution
The Agent can understand natural language and map user utterances to the correct Agent action.
This ensures that agents receive accurate order fulfillment updates quickly.
No Need for Manual Data Entry
Instead of manually searching Oracle ERP, agents can query fulfillment status using AI-powered Agentforce workflows.
NEW QUESTION # 29
What is one key purpose of action instructions when creating a custom agent action in Agentforce?
Answer: B
Explanation:
According to the AgentForce Action Design and Configuration Guide, action instructions serve as the directive text that informs the Reasoning Engine about when and how to invoke a specific action. The documentation states: "Action instructions guide the reasoning engine by describing the action's purpose, inputs, and when it should be selected. Clear, concise instructions improve the LLM's accuracy in mapping user intent to the correct action."
NEW QUESTION # 30
Which part of the Einstein Trust Layer architecture leverages an organization's own data within a large language model (LLM) prompt to confidently return relevant and accurate responses?
Answer: C
Explanation:
Dynamic Grounding in the Einstein Trust Layer architecture ensures that large language model (LLM) prompts are enriched with organization-specific data (e.g., Salesforce records, Knowledge articles) to generate accurate and relevant responses. By dynamically injecting contextual data into prompts, it reduces hallucinations and aligns outputs with trusted business data.
NEW QUESTION # 31
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