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Valid Agentforce-Specialist Exam Review, Agentforce-Specialist Valid Real Exam

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Salesforce Agentforce-Specialist Exam Syllabus Topics:

Topic
Details

Topic 1

Agentforce and Service Cloud: This section measures the skills of AI Engineers and focuses on building agents that answer questions based on Knowledge articles and connecting them to digital channels. It also covers identifying the correct generative AI features in Agentforce for Service Cloud scenarios.

Topic 2

Agentforce and Sales Cloud: This section assesses the skills of AI Developers and covers identifying the correct generative AI features in Agentforce for Sales Cloud scenarios. It also includes determining when to use Agentforce Sales Agents, such as Sales Development Representatives (SDRs) and Sales Coaches.

Topic 3

Agentforce and Data Cloud: This section measures the skills of AI Developers and addresses how Agentforce integrates with Data Cloud to improve response accuracy and personalize answers. It involves grounding with retrievers in Data Cloud to enhance agent performance.

Topic 4

Agentforce Concepts: This section assesses the skills of AI Engineers and covers how Agentforce works, including its reasoning engine, standard and custom topics, agent actions, and user security management. It also includes testing and deploying agents from sandbox to production environments.

Topic 5

Prompt Engineering: This section measures the skills of AI Developers and focuses on prompt engineering techniques. It covers identifying when to use Prompt Builder, managing prompt templates, selecting appropriate grounding techniques, and explaining the process for creating and executing prompt templates.

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Salesforce Certified Agentforce Specialist Sample Questions (Q168-Q173):

NEW QUESTION # 168
After configuring and saving a Salesforce Agentforce Data Library (regardless of the data source), which components are automatically created and available in Data Cloud?

A. A data stream, a search index, and a retriever
B. A data connector, an analytics dashboard, and a workflow rule
C. A data pipeline, an indexing engine, and a query processor

Answer: A

Explanation:
Why is "A data stream, a search index, and a retriever" the correct answer?
When a Salesforce Agentforce Data Library is configured and saved, it automatically creates three essential components in Data Cloud to facilitate AI-driven search and retrieval.
Key Components Created in Data Cloud:
* Data Stream
* This acts as the pipeline that brings data into Data Cloud.
* It enables real-time data ingestion from sources such as Salesforce records, PDFs, or external databases.
* Search Index
* After ingestion, data is indexed for efficient search and retrieval.
* This allows AI models to perform structured queries and retrieve relevant data faster.
* Retriever
* The retriever is an AI-powered search mechanism that uses the search index to fetch the most relevant data.
* It ensures that AI-generated responses are grounded in structured, reliable data.
Why Not the Other Options?
# A. A data pipeline, an indexing engine, and a query processor
* Incorrect because Data Cloud does not use a query processor in the same way as traditional databases.
* Instead, retrievers handle AI-powered data searches.
# B. A data connector, an analytics dashboard, and a workflow rule
* Incorrect because these components are not automatically created when setting up a Data Library.
* Analytics dashboards and workflow rules are separate tools used for reporting and automation.
Agentforce Specialist References
* Salesforce AI Specialist Material confirms that a Data Stream, Search Index, and Retriever are created automatically in Data Cloud when configuring a Data Library.

NEW QUESTION # 169
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 Copilot.
B. Turn on Einstein Generative AI.
C. Turn on Prompt Builder.

Answer: B

Explanation:
For Northern Trail Outfitters (NTO) to configure theEinstein Trust Layer, theEinstein 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.
* Option A(Turning on Einstein Copilot) is unrelated to the setup of the Einstein Trust Layer, which focuses more on generative AI interactions and data handling.
* Option C(Turning on Prompt Builder) is used for configuring and building AI-driven prompts, but it does not enable the Einstein Trust Layer.
SalesforceAgentforce SpecialistReferences:For more details on the Einstein Trust Layer and setup steps:
https://help.salesforce.com/s/articleView?id=sf.einstein_trust_layer_overview.htm

NEW QUESTION # 170
Universal Containers (UC) plans to implement prompt templates that utilize the standard foundation models.
What should UC consider when building prompt templates in Prompt Builder?

A. Include multiple-choice questions within the prompt to test the LLM's understanding of the context.
B. Train LLM with data using different writing styles including word choice, intensifiers, emojis, and punctuation.
C. Ask it to role-play as a character in the prompt template to provide more context to the LLM.

Answer: C

Explanation:
Comprehensive and Detailed In-Depth Explanation:UC is using Prompt Builder with standard foundation models (e.g., via Atlas Reasoning Engine). Let's assess best practices for prompt design.
* Option A: Include multiple-choice questions within the prompt to test the LLM's understanding of the context.Prompt templates are designed to generate responses, not to test the LLM with multiple- choice questions. This approach is impractical and not supported by Prompt Builder's purpose, making it incorrect.
* Option B: Ask it to role-play as a character in the prompt template to provide more context to the LLM.A key consideration in Prompt Builder is crafting clear, context-rich prompts. Instructing the LLM to adopt a role (e.g., "Act as a sales expert") enhances context and tailors responses to UC's needs, especially with standard models. This is a documented best practice for improving output relevance, making it the correct answer.
* Option C: Train LLM with data using different writing styles including word choice, intensifiers, emojis, and punctuation.Standard foundation models in Agentforce are pretrained and not user- trainable. Prompt Builder users refine prompts, not the LLM itself, making this incorrect.
Why Option B is Correct:Role-playing enhances context for standard models, a recommended technique in Prompt Builder for effective outputs, as per Salesforce guidelines.
References:
* Salesforce Agentforce Documentation: Prompt Builder > Best Practices- Recommends role-based context.
* Trailhead: Build Prompt Templates in Agentforce- Highlights role-playing for clarity.
* Salesforce Help: Prompt Design Tips- Suggests contextual roles.

NEW QUESTION # 171
Universal Containers (UC) wants to implement an AI-powered customer service agent that can:
* Retrieve proprietary policy documents that are stored as PDFs.
* Ensure responses are grounded in approved company data, not generic LLM knowledge.What should UC do first?

A. Set up an Agentforce Data Library for AI retrieval of policy documents.
B. Add the files to the content, and then select the data library option.
C. Expand the AI agent's scope to search all Salesforce records.

Answer: A

Explanation:
Comprehensive and Detailed In-Depth Explanation:To implement an AI-powered customer service agent that retrieves proprietary policy documents (stored as PDFs) and ensures responses are grounded in approved company data, UC must first establish a foundation for the AI to access and use this data. TheAgentforce Data Library(Option A) is the correct starting point. A Data Library allows UC to upload PDFs containing policy documents, index them into Salesforce Data Cloud's vector database, and make them available for AI retrieval. This setup ensures the agent can perform Retrieval-Augmented Generation (RAG), grounding its responses in the specific, approved content from the PDFs rather than relying on generic LLM knowledge, directly meeting UC's requirements.
* Option B: Expanding the AI agent's scope to search all Salesforce records is too broad and unnecessary at this stage. The requirement focuses on PDFs with policy documents, not all Salesforce data (e.g., cases, accounts), making this premature and irrelevant as a first step.
* Option C: "Add the files to the content, and then select the data library option" is vague and not a precise process in Agentforce. While uploading files is part of setting up a Data Library, the phrasing suggests adding files to Salesforce Content (e.g., ContentDocument) without indexing, which doesn't enable AI retrieval. Setting up the Data Library (A) encompasses the full process correctly.
* Option A: This is the foundational step-creating a Data Library ensures the PDFs are uploaded, indexed, and retrievable by the agent, fulfilling both retrieval and grounding needs.
Option A is the correct first step for UC to achieve its goals.
References:
* Salesforce Agentforce Documentation: "Set Up a Data Library" (Salesforce Help:https://help.salesforce.
com/s/articleView?id=sf.agentforce_data_library.htm&type=5)
* Salesforce Data Cloud Documentation: "Ground AI Responses with Data Cloud" (https://help.
salesforce.com/s/articleView?id=sf.data_cloud_agentforce.htm&type=5)

NEW QUESTION # 172
Universal Containers is planning a marketing email about products that most closely match a customer's expressed interests.
What should An Agentforce recommend to generate this email?

A. Standard email draft with Einstein and choose standard email template
B. Standard email marketing template using Apex or flows for matching interest in products
C. Custom sales email template which is grounded with interest and product information

Answer: C

Explanation:
To generate an email about products that closely match a customer's expressed interests, An Agentforce should recommend using acustom sales email templatethat isgrounded with interest and product information. This ensures that the email content is personalized based on the customer's preferences, increasing the relevance of the marketing message.
Using grounding ensures that the generative AI pulls the correct data related to customer interests and product matches, making the email more effective.
For more information, refer toSalesforce documentationon grounding AI-generated content and email personalization strategies.

NEW QUESTION # 173
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