Our Salesforce Certified Agentforce Specialist AI-201 questions PDF is a complete bundle of problems presenting the versatility and correlativity of questions observed in past exam papers. These questions are bundled into Salesforce Certified Agentforce Specialist PDF questions following the official study guide. Salesforce AI-201 PDF Questions are a portable, printable document that simultaneously plays on multiple devices. Our Salesforce AI-201 PDF questions consists of problems in all aspects, whether theoretical, practical, or analytical.
| Section | Weight | Objectives |
|---|---|---|
| Einstein Trust Layer & Security | - Trust Layer & Security Features
| |
| Prompt Engineering | 30% | - Prompt Builder & Template Creation
|
| Agent Force Concepts | 30% | - Data Cloud & Grounding Techniques
|
| Reasoning Engine & AI Actions | - Workflow mastery
|
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NEW QUESTION # 253
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: C
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 # 254
Universal Containers wants to use an existing prompt template inside Flow as part of automation.
Answer: A
NEW QUESTION # 255
Universal Containers (UC) has a legacy system that needs to integrate with Salesforce. UC wishes to create a digest of account action plans using the generative API feature. Which API service should UC use to meet this requirement?
Answer: B
Explanation:
To create a digest of account action plans using the generative API feature, Universal Containers should use the REST API. The REST API is ideal for integrating Salesforce with external systems and enabling interaction with Salesforce data, including generative capabilities like creating summaries or digests. It supports modern web standards and is suitable for flexible, lightweight interactions between Salesforce and legacy systems.
Metadata API is used for retrieving and deploying metadata, not for data operations like generating summaries.
SOAP API is an older API used for integration but is less flexible compared to REST for this specific use case.
NEW QUESTION # 256
A Salesforce Administrator is exploring the capabilities of Agent to enhance user interaction within their organization. They are particularly interested in how Agent processes user requests and the mechanism it employs to deliver responses. The administrator is evaluating whether Agent directly interfaces with a large language model (LLM) to fetch and display responses to user inquiries, facilitating a broad range of requests from users. How does Agent handle user requests In Salesforce?
Answer: C
Explanation:
Agent is designed to enhance user interaction within Salesforce by leveraging Large Language Models (LLMs) to process and respond to user inquiries. When a user submits a request, Agent analyzes the input using natural language processing techniques. It then utilizes LLM technology to generate an appropriate and contextually relevant response, which is displayed directly to the user within the Salesforce interface.
NEW QUESTION # 257
Universal Containers is setting up the data library configuration within the Agentforce Builder.
What is true regarding Agentforce Data Libraries?
Answer: C
Explanation:
The correct statement regarding the configuration limit of Agentforce Data Libraries is that An agent can have only one data library assigned to it (C).
Agentforce Data Libraries are the mechanism by which an agent is "grounded" in an organization's internal, trusted knowledge (using Retrieval Augmented Generation or RAG). To ensure that the agent's focus remains sharp and its retrieval process is efficient and accurate, there is a one-to-one relationship between an Agentforce Agent and the Data Library it uses for grounding.
NEW QUESTION # 258
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