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Salesforce AI-201 Exam Syllabus Topics:

Section	Weight	Objectives
Multi-Agent Interoperability	5%	- Agent API usage scenarios - Agent-to-agent communication - Model Context Protocol (MCP)
Development Lifecycle	15%	- Deployment: sandbox to production - Version control and maintenance - Monitoring, adoption and optimization - Testing agents in Testing Center
Prompt Engineering	20%	- Prompt Builder usage and use cases - Prompt template creation: field generation, flex types - Grounding techniques and best practices - Prompt management and user roles
AI Agents	35%	- Topics and actions configuration - Agent architecture and reasoning engine - Agent types: Service, Sales, Employee - Agent User security and permissions - Channel integration: digital experience, email, Slack - Deterministic controls: filters and variables
Data Cloud for Agentforce	20%	- Improving response accuracy with data grounding - Unstructured data processing: chunking, indexing - Retrievers and search types: keyword, vector, hybrid - Agentforce Data Library types

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Salesforce Certified Agentforce Specialist Sample Questions (Q143-Q148):

NEW QUESTION # 143
Universal Containers' current AI data masking rules do not align with organizational privacy and security policies and requirements. What should An Agentforce recommend to resolve the issue?

A. Add new data masking rules in LLM setup.
B. Enable data masking for sandbox refreshes.
C. Configure data masking in the Einstein Trust Layer setup.

Answer: C

Explanation:
When Universal Containers' AI data masking rules do not meet organizational privacy and security standards, the Agentforce Specialist should configure the data masking rules within the Einstein Trust Layer. The Einstein Trust Layer provides a secure and compliant environment where sensitive data can be masked or anonymized to adhere to privacy policies and regulations.

NEW QUESTION # 144
Universal Containers (UC) needs to save agents time with AI-generated case summaries. UC has implemented the Work Summary feature. What does Einstein consider when generating a summary?

A. Generation is grounded with conversation context and Knowledge articles.
B. Generation is grounded with conversation context, Knowledge articles, and cases.
C. Generation is grounded with existing conversation context only.

Answer: B

Explanation:
When generating a Work Summary, Einstein leverages multiple sources of information to provide a comprehensive and accurate case summary for agents.
Conversation Context:
Einstein analyzes the details of the customer interaction, including chat or email threads, to extract relevant information for the summary.
Knowledge Articles:
It considers linked Knowledge Articles or articles referred to during the case resolution process, ensuring the summary incorporates accurate resolutions or additional resources provided to the customer.
Cases:
Einstein also examines historical cases and related case records to ground the summary in context from past resolutions or interactions.

NEW QUESTION # 145
Universal Containers (UC) wants to empower its marketing team with Al capabilities that help employees quickly find campaign data, generate creative content, and manage project tasks. The solution should also allow marketers to receive personalized support, surface relevant information, and complete work directly in Salesforce. Which Al solution should UC implement?

A. Service Agent
B. Sales Coach Agent
C. Employee Agent

Answer: C

Explanation:
According to the AgentForce Solutions Overview and Employee Agent documentation, the Employee Agent is designed to empower internal teams, such as marketing, sales, HR, and operations, by providing AI-driven assistance within Salesforce. The guide explains: "Employee Agents help internal users find information, automate tasks, generate content, and manage projects directly in Salesforce. They surface personalized insights, support productivity, and leverage enterprise knowledge sources." In the given scenario, the marketing team requires capabilities for content creation, data lookup, and task management-all within Salesforce. This exactly matches the described functionality of an Employee Agent.

NEW QUESTION # 146
An Agentforce turned on Einstein Generative AI in Setup. Now, the Agentforce Specialist would like to create custom prompt templates in Prompt Builder. However, they cannot access Prompt Builder in the Setup menu. What is causing the problem?

A. The large language model (LLM) was not configured correctly in Data Cloud.
B. The Prompt Template User permission set was not assigned correctly.
C. The Prompt Template Manager permission set was not assigned correctly.

Answer: C

Explanation:
In order to access and create custom prompt templates in Prompt Builder, the Agentforce Specialist must have the Prompt Template Manager permission set assigned. Without this permission, they will not be able to access Prompt Builder in the Setup menu, even though Einstein Generative AI is enabled.

NEW QUESTION # 147
Why is starting with a narrowly scoped Agentforce use case considered a best practice?

A. It reduces Salesforce license costs
B. It limits risk and simplifies monitoring
C. It eliminates user training
D. It avoids the need for prompts

Answer: B

Explanation:
A narrow scope limits unintended behavior and makes monitoring, tuning, and governance easier.

NEW QUESTION # 148
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