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Salesforce AI-201 Exam Syllabus Topics:

Section	Weight	Objectives
Topic 1: Einstein Trust Layer & Security		- Data Masking 1. Configuration of privacy data entities - Trust Layer & Security Features 1. Enterprise-grade deployment
Topic 2: Prompt Engineering	30%	- Prompt Builder & Template Creation 1. Best practices - Agentforce AI Setup & Configuration 1. Advanced implementation strategies
Topic 3: Reasoning Engine & AI Actions		- Workflow mastery 1. Custom Agent actions (Flows) 2. Custom Agent actions (Apex) 3. Standard Agent actions
Topic 4: Agent Force Concepts	30%	- Data Cloud & Grounding Techniques 1. Real-world applications - Einstein GPT Integration 1. Advanced implementation strategies

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Salesforce Certified Agentforce Specialist Sample Questions (Q157-Q162):

NEW QUESTION # 157
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?

A. Turn on Einstein Generative AI.
B. Turn on Prompt Builder.
C. Turn on Agent.

Answer: A

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 # 158
Which metric provides the MOST insight into whether an Agentforce agent is delivering business value?

A. Prompt length
B. Model response time
C. Number of conversations
D. Task success and resolution rate

Answer: D

Explanation:
Business value is best measured by successful task completion and resolution outcomes.

NEW QUESTION # 159
Which design choice MOST reduces the risk of hallucinations?

A. Open-ended instructions
B. Higher temperature settings
C. Larger prompts
D. Strong grounding in Salesforce data

Answer: D

Explanation:
Grounding responses in trusted Salesforce data significantly reduces hallucinations.

NEW QUESTION # 160
A sales manager is using Agent Assistant to streamline their daily tasks. They ask the agent to Show me a list of my open opportunities. How does the large language model (LLM) in Agentforce identify and execute the action to show the sales manager a list of open opportunities?

A. The LLM interprets the user's request, generates a plan by identifying the apcMopnete topics and actions, and executes the actions to retrieve and display the open opportunities
B. Using a dialog pattern. the LLM matches the user query to the available topic, action and steps then performs the steps for each action, such as retrieving a fast of open opportunities.
C. The LLM uses a static set of rules to match the user's request with predefined topics and actions, bypassing the need for dynamic interpretation and planning.

Answer: A

Explanation:
Agentforce's LLM dynamically interprets natural language requests (e.g., "Show me open opportunities"), generates an execution plan using the planner service, and retrieves data via actions (e.g., querying Salesforce records). This contrasts with static rules (B) or rigid dialog patterns (C), which lack contextual adaptability. Salesforce documentation highlights the planner's role in converting intents into actionable steps while adhering to security and business logic.

NEW QUESTION # 161
Universal Containers (UC) has implemented Generative AI within Salesforce to enable summarization of a custom object called Guest. Users have reported mismatches in the generated information. In refining its prompt design strategy, which key practices should UC prioritize?

A. Submit a prompt review case to Salesforce and conduct thorough testing In the playground to refine outputs until they meet user expectations.
B. Create concise, clear, and consistent prompt templates with effective grounding, contextual role- playing, clear instructions, and iterative feedback.
C. Enable prompt test mode, allocate different prompt variations to a subset of users for evaluation, and standardize the most effective model based on performance feedback.

Answer: B

Explanation:
For Universal Containers (UC) to refine its Generative AI prompt design strategy and improve the accuracy of the generated summaries for the custom object Guest, the best practice is to focus on crafting concise, clear, and consistent prompt templates. This includes:
Effective grounding: Ensuring the prompt pulls data from the correct sources.
Contextual role-playing: Providing the AI with a clear understanding of its role in generating the summary.
Clear instructions: Giving unambiguous directions on what to include in the response.
Iterative feedback: Regularly testing and adjusting prompts based on user feedback.

NEW QUESTION # 162
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