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Salesforce AI-201 Exam Syllabus Topics:

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

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Salesforce Certified Agentforce Specialist Sample Questions (Q179-Q184):

NEW QUESTION # 179
Which scenario best illustrates the use of Model Context Protocol (MCP) in an enterprise Al deployment?

A. A legal assistant agent using MCP to dynamically find a document classification API to analyze case files
B. A sales agent discovering other agents' capabilities using Agent Cards
C. A customer service agent engaging another agent in real-time conversation to resolve tickets

Answer: A

Explanation:
The Model Context Protocol (MCP) in AgentForce and Salesforce AI architecture enables agents to dynamically discover and connect to external tools or APIs during runtime. The documentation defines it as: "MCP allows LLMs to query registered tool endpoints and retrieve their schemas, enabling dynamic tool discovery and invocation in enterprise AI environments."

NEW QUESTION # 180
What is one key purpose of action instructions when creating a custom agent action in Agentforce?

A. Action instructions define the temperature of the large language model (LLM) powering the Reasoning Engine.
B. Action instructions tell the user how to call this action in a conversation.
C. Action instructions help the reasoning engine decide which action to use.

Answer: C

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 # 181
A Salesforce Agentforce Specialist is reviewing the feedback from a customer about the ineffectiveness of the prompt template. What should the Agentforce Specialist do to ensure the prompt template's effectiveness?

A. Periodically change the templates grounding object.
B. Use the Prompt Builder Scorecard to help monitor.
C. Monitor and refine the template based on user feedback.

Answer: B

Explanation:
To address the ineffectiveness of a prompt template reported by a customer, the Salesforce Agentforce Specialist should use the Prompt Builder Scorecard (Option B). This tool is explicitly designed to evaluate and monitor prompt templates against key criteria such as relevance, accuracy, safety, and grounding. By leveraging the scorecard, the specialist can systematically identify weaknesses in the template and make data-driven refinements. While monitoring and refining based on user feedback (Option A) is a general best practice, the Prompt Builder Scorecard is Salesforce's recommended tool for structured evaluation, aligning with documented processes for maintaining prompt effectiveness. Changing the grounding object (Option C) without proper evaluation is reactive and does not address the root cause.

NEW QUESTION # 182
Universal Containers (UC) has configured a data library and wants to restrict indexing of knowledge articles to articles which are only publicly available in their knowledge base, UC also wants the agent to link sources that the large language model (LLM) grounded its response on.
Which settings should help UC with this?

A. In the data library setting window, under Knowledge Settings, enable Use Public Knowledge Article and select Show sources,
B. In the data library setting window, under Knowledge Settings, enable Use Public Knowledge Article. It is not possible to display articles that the LLM grounded its response in.
C. Use Data Categories to categorize publicly available articles to index. Sources are automatically displayed when knowledge articles are categorized as Public.

Answer: A

Explanation:
According to the AgentForce Data Library Configuration Guide, administrators can restrict indexing and retrieval of Knowledge articles to publicly available ones and enable source visibility for LLM-grounded responses. The documentation states:
"Within the data library settings, under Knowledge Settings, enable `Use Public Knowledge Articles' to ensure only publicly visible content is indexed. To display citations, enable `Show Sources' so the agent links the specific articles or data records used to ground its response."

NEW QUESTION # 183
Universal Containers (UC) wants to improve the productivity of its sales team with generative AI technology. However, UC is concerned that public AI virtual assistants lack adequate company data to general useful responses. Which solution should UC consider?

A. Build Al model with Einstein discovery and deploy to sales users.
B. fine-tune the Einstein AI model with CBM data.
C. Enable Agentforce and deploy to sales users.

Answer: B

Explanation:
Universal Containers (UC) wants to harness generative AI to boost sales productivity. They are wary of public AI virtual assistants (like generic chatbots) that lack sufficient UC-specific data to generate useful business responses.

NEW QUESTION # 184
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