AI-201 Exam Questions And Answers - Latest Salesforce Salesforce Certified Agentforce Specialist - Test AI-201 Cram Pdf

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Salesforce AI-201 Exam Syllabus Topics:

Section	Weight	Objectives
Prompt Engineering	20%	- Grounding techniques 1. Data grounding for reducing hallucinations 2. Best practices for prompt design - Prompt Builder usage 1. Field generation and flex templates 2. Prompt templates and configuration
Testing, Deployment & Lifecycle	15%	- Agent lifecycle management 1. Testing and validation strategies 2. Sandbox to production deployment
Data Cloud & Grounding	20%	- Data integration for AI agents 1. Using Data Cloud for retrieval augmentation 2. Connecting external data sources
Governance & Observability	10%	- AI governance 1. Monitoring agent behavior 2. Trust layer and compliance concepts
AI Agents	35%	- Agent setup and orchestration 1. Standard and custom topics 2. Standard and custom agent actions - Agent behavior configuration 1. Agent reasoning engine concepts 2. Filters and variables for deterministic behavior

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Salesforce Certified Agentforce Specialist Sample Questions (Q212-Q217):

NEW QUESTION # 212
An Agentforce 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 Agentforce Specialist needs to configure the system to use the most accurate and up-to-date information for email generation. Which grounding technique should the Agentforce Specialist use?

A. Automatic grounding using Draft with Einstein feature
B. Ground with Apex Merge Fields
C. Ground with Record Merge Fields

Answer: A

Explanation:
For Einstein Sales Emails to generate personalized follow-up emails, it is crucial to ground the email content with the most up-to-date and accurate information. Grounding refers to connecting the AI model with real-time data. The most appropriate technique in this case is Ground with Record Merge Fields. This method ensures that the content in the emails pulls dynamic and accurate data directly from Salesforce records, such as lead or contact information, ensuring the follow-up is relevant and customized based on the specific record.
Record Merge Fields ensure the generated emails are highly personalized using data like lead name, company, or other Salesforce fields directly from the records.
Apex Merge Fields are typically more suited for advanced, custom logic-driven scenarios but are not the most straightforward for this use case.
Automatic grounding using Draft with Einstein is a different feature where Einstein automatically drafts the email, but it does not specifically ground the content with record-specific data like Record Merge Fields.

NEW QUESTION # 213
Universal Containers deployed the new Agentforce Sales Development Representative (SDR) Into production, but sales reps are saying they can't find it. What is causing this issue?

A. Sales rep users are missing the Use SDR Agent permission set.
B. Sales rep users do not have access to the SDR Agent object.
C. Sales rep users profiles are missing the Allow SDR Agent permission.

Answer: A

Explanation:
Why is "Sales rep users are missing the Use SDR Agent permission set" the correct answer?
If sales reps are unable to find the Agentforce Sales Development Representative (SDR) Agent, the most likely cause is missing permissions. The "Use SDR Agent" permission set is required for users to access and interact with the SDR Agent in Agentforce.
Key Considerations for This Issue:
Permission Set Restriction
Users must have the "Use SDR Agent" permission set to access Agentforce SDR in their Salesforce environment.
If they lack this permission, the SDR Agent will not appear in their interface.
Agentforce Role-Based Access Control
Agentforce assigns specific permissions based on user roles.
Sales reps require explicit permission to access the SDR Agent.
Fixing the Issue
The Salesforce Admin should assign the "Use SDR Agent" permission set to all relevant sales reps.
This is done in Setup Permission Sets Assign to Users.

NEW QUESTION # 214
Universal Containers is using Agentforce for Sales to find similar opportunities to help close deals faster. The team wants to understand the criteria used by the Agent to match opportunities.

A. Matched opportunities were created in the last 12 months.
B. Matched opportunities have a status of Closed Won from the last 12 months.
C. Matched opportunities are limited to the same account.

Answer: B

NEW QUESTION # 215
Cloud Kicks (CK) recently finished the development of a new prompt template that uses its own large language model (LLM). CK is deploying a prompt template from a sandbox to a production org, and is receiving an error. When trying to deploy the change set, CK is getting an error related to the LLM used in the prompt template. What is the cause of the error?

A. BYOLLM is not yet supported for in prompt templates in production.
B. The name of the LLM does not match in sandbox and production.
C. The prompt does not specify that it is a custom LLM.

Answer: B

Explanation:
As documented in the AgentForce Prompt Template and BYOLLM (Bring-Your-Own-LLM) Deployment Guide, each prompt template references a specific LLM configuration by name and ID. When migrating components between environments (e.g., from sandbox to production), the referenced LLM must also exist in the target org with the exact same name and identifier.
If the LLM configuration is missing or named differently in production, the deployment fails, as the prompt template cannot resolve its model dependency.

NEW QUESTION # 216
Universal Containers (UC) currently tracks Leads with a custom object. UC is preparing to implement the Sales Development Representative (SDR) Agent. Which consideration should UC keep in mind?

A. Agentforce SDR only works on Opportunities.
B. Agentforce SDR only supports custom objects associated with Accounts.
C. Agentforce SDR only works with the standard Lead object.

Answer: C

Explanation:
Universal Containers (UC) uses a custom object for Leads and plans to implement the Agentforce Sales Development Representative (SDR) Agent. The SDR Agent is a prebuilt, configurable AI agent designed to assist sales teams by qualifying leads and scheduling meetings. Let's evaluate the options based on its functionality and limitations.

NEW QUESTION # 217
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