Pass Guaranteed Quiz AI-201 - Perfect Salesforce Certified Agentforce Specialist Exam Details

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Salesforce AI-201 Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Prompt Engineering30%- Agentforce AI Setup & Configuration
  • 1. Advanced implementation strategies
- Prompt Builder & Template Creation
  • 1. Best practices
Topic 2: Reasoning Engine & AI Actions- Workflow mastery
  • 1. Custom Agent actions (Apex)
  • 2. Standard Agent actions
  • 3. Custom Agent actions (Flows)
Topic 3: Agent Force Concepts30%- Einstein GPT Integration
  • 1. Advanced implementation strategies
- Data Cloud & Grounding Techniques
  • 1. Real-world applications
Topic 4: Einstein Trust Layer & Security- Data Masking
  • 1. Configuration of privacy data entities
- Trust Layer & Security Features
  • 1. Enterprise-grade deployment

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Salesforce Certified Agentforce Specialist Sample Questions (Q176-Q181):

NEW QUESTION # 176
An Agentforce Specialist needs to create a prompt template that extracts the customer's name, phone number, and case number from a block of text, and nothing else. How should the Agentforce Specialist structure the prompt to ensure the large language model (LLM) doesn't include extra conversation or text?

Answer: A

Explanation:
According to the official AgentForce Prompt Template Design Guide, when extracting specific data such as customer name, phone number, and case number from unstructured text, the best practice is to use well-defined output instructions and examples. The documentation specifies:
"To ensure the LLM produces consistent and precise outputs, prompts must include explicit output formatting instructions and examples that demonstrate the desired structure." AgentForce guidance emphasizes structured output control to prevent the LLM from adding conversational or extraneous text. It states: "Always define your output schema clearly - for example, specify JSON or key-value pairs - and provide one or more examples of what the model should return. This ensures the model responds only with structured data and not natural language."


NEW QUESTION # 177
What should Universal Containers consider when deploying an Agentforce Service Agent with multiple topics and Agent Actions to production?

Answer: C

Explanation:
UC is deploying an Agentforce Service Agent with multiple topics and actions to production.


NEW QUESTION # 178
What is the role of the large language model (LLM) in executing an Agent Action?

Answer: B

Explanation:
In Agent, the role of the Large Language Model (LLM) is to analyze user inputs and identify the best matching actions that need to be executed. It uses natural language understanding to break down the user's request and determine the correct sequence of actions that should be performed.
By doing so, the LLM ensures that the tasks and actions executed are contextually relevant and are performed in the proper order. This process provides a seamless, AI-enhanced experience for users by matching their requests to predefined Salesforce actions or flows.


NEW QUESTION # 179
Universal Containers wants to test agents while preserving real data and isolating from production. Which environment should the company use with Testing Center?

Answer: A

Explanation:
The AgentForce Testing Center Implementation Guide specifies that organizations should perform all structured and regression testing in a sandbox environment replicated from production. The guide explains:
"Testing Center supports running tests safely in sandbox environments that mirror production data. This ensures realistic test conditions without impacting live systems or data."


NEW QUESTION # 180
Support agents at Universal Containers are using Agentforce to find troubleshooting information.
They've reported that the agent frequently provides knowledge articles that are outdated, even when newer versions of the articles are available. The administrator has confirmed that all articles are correctly chunked and indexed. Which configuration change in the Data Cloud hybrid search index best addresses this problem?

Answer: A

Explanation:
The AgentForce Data Cloud Retrieval and Ranking Guide highlights that when outdated Knowledge articles appear before newer ones, administrators should configure ranking factors that prioritize content based on recency. The documentation specifies: "Adding a recency ranking factor using the LastModifiedDate or LastPublishedDate fields ensures the retrieval prioritizes the most up-to-date documents, improving response relevance."


NEW QUESTION # 181
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