Agentforce-Specialist Practice Questions

A.  

Configure a Prompt Defense policy in the Einstein Trust Layer to mask the sensitive account data from the reasoning engine until the user successfully completes the verification process.

B.  

Store the user’s verification status in a custom variable and apply an available when filter condition to the account lookup action, making the action invisible to the reasoning engine until the variable evaluates to true.

C.  

Add explicit natural language instructions within the subagent definition instructing the large language model to always prioritize the customer verification action before proceeding to the account lookup action.

A.  

It creates numerical representations of chunk content to enable meaning-based retrieval.

B.  

It encrypts the content so it can be stored securely within Data 360 data spaces.

C.  

It reduces the file size of the original document to reduce Data 360 costs.

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.

A.  

Service Agent

B.  

Employee Agent

C.  

Sales Agent

A.  

Configure a messaging Lightning web component using standard or custom Lightning Type for Agentforce.

B.  

Create an Omni-Channel flow that routes messages to the agent.

C.  

Configure MuleSoft to establish a secure API tunnel between the agent and the Digital Experience site.

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

A.  

Build a subagent action using a Salesforce Flow to query the Knowledge articles data model object at runtime and return matching content to the agent, ensuring the agent always retrieves live article data directly from the Knowledge object.

B.  

Create an Agentforce Data Library connected to the Salesforce Knowledge base, filtered to published articles only, enabling the agent to ground responses using retrieval-augmented generation powered semantic retrieval that automatically reflects Knowledge updates without requiring agent reconfiguration.

C.  

Configure a custom retriever in Einstein Studio connected to a Data 360 search index, applying filters to restrict results to documents tagged as current.

A.  

Use personal developer orgs unrepresentative of production data,

B.  

Use production org directly with test assertions.

C.  

Use sandbox environments replicated from production for safe testing,

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

A.  

View the user click path that led to each agent action.

B.  

View session data including user input and agent responses for sessions.

C.  

Generate details reports on all agent conversations over any time period.