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  1. Home
  2. Salesforce Certification
  3. Agentforce-Specialist Exam
  4. Salesforce.Agentforce-Specialist.v2025-09-29.q108 Dumps
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Question 31

Universal Containers (UC) wants to build an Agentforce Service Agent that provides the latest, active, and relevant policy and compliance information to customers. The agent must:
* Semantically search HR policies, compliance guidelines, and company procedures.
* Ensure responses are grounded on published Knowledge.
* Allow Knowledge updates to be reflected immediately without manual reconfiguration.What should UC do to ensure the agent retrieves the right information?

Correct Answer: B
Comprehensive and Detailed In-Depth Explanation:UC requires an Agentforce Service Agent to deliver accurate, up-to-date policy and compliance info with specific criteria. Let's evaluate.
* Option A: Enable the agent to search all internal records and past customer inquiries.Searching all records and inquiries risks irrelevant or outdated responses, conflicting with the need for published Knowledge grounding and immediate updates. This lacks specificity, making it incorrect.
* Option B: Set up an Agentforce Data Library to store and index policy documents for AI retrieval.The Agentforce Data Library integrates with Salesforce Knowledge, indexing HR policies, compliance guidelines, and procedures for semantic search. It ensures grounding in published Knowledge articles, and updates (e.g., new article versions) are reflected instantly without reconfiguration, as the library syncs with Knowledge automatically. This meets all UC requirements, making it the correct answer.
* Option C: Manually add policy responses into the AI model to prevent hallucinations.Manually embedding responses into the model isn't feasible-Agentforce uses pretrained LLMs, not custom training. It also doesn't support real-time updates, making this incorrect.
Why Option B is Correct:The Data Library meets all criteria-semantic search, Knowledge grounding, and instant updates-per Salesforce's recommended approach.
References:
* Salesforce Agentforce Documentation: Data Library > Knowledge Integration - Details indexing and updates.
* Trailhead: Build Agents with Agentforce - Covers Data Library for accurate responses.
* Salesforce Help: Grounding with Knowledge - Confirms real-time sync.
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Question 32

Where should theAgentforce Specialistgo to add/update actions assigned to a copilot?

Correct Answer: A
To add or update actions assigned to a copilot, An Agentforce can manage this through several areas:
* Copilot Actions Page: This is the central location where copilot actions are managed and configured.
* Record Page for the Copilot Action: From the record page, individual copilot actions can be updated or modified.
* Copilot Action Library Tab: This tab serves as a repository where predefined or custom actions for Copilot can be accessed and modified.
These areas provide flexibility in managing and updating the actions assigned to Copilot, ensuring that the AI assistant remains aligned with business requirements and processes.
The other options are incorrect:
* Bmisses the Copilot Action Library, which is crucial for managing actions.
* Cincludes the Copilot Detail page, which isn't the primary place for action management.
References:
* Salesforce Documentation onManaging Copilot Actions
* SalesforceAgentforce SpecialistGuide onCopilot Action Management
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Question 33

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?

Correct Answer: A
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.
:
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)
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Question 34

The sales team at a hotel resort would like to generate a guest summary about the guests' interests and provide recommendations based on their activity preferences captured in each guest profile. They want the summary to be available only on the contact record page. Which AI capability should the team use?

Correct Answer: C
Comprehensive and Detailed In-Depth Explanation:The hotel resort team needs an AI-generated guest summary with recommendations, displayed exclusively on the contact record page. Let's assess the options.
* Option A: Model BuilderModel Builder in Salesforce creates custom predictive AI models (e.g., for scoring or classification) using Data Cloud or Einstein Platform data. It's not designed for generating text summaries or embedding them on record pages, making it incorrect.
* Option B: Agent BuilderAgent Builder in Agentforce Studio creates autonomous AI agents for tasks like lead qualification or customer service. While agents can provide summaries, they operate in conversational interfaces (e.g., chat), not as static content on a record page. This doesn't meet the location-specific requirement, making it incorrect.
* Option C: Prompt BuilderEinstein Prompt Builder allows creation of prompt templates that generate text (e.g., summaries, recommendations) using Generative AI. The template can pull data from contact records (e.g., activity preferences) and be embedded as a Lightning component on the contact record page via a Flow or Lightning App Builder. This ensures the summary is available only where specified, meeting the team's needs perfectly and making it the correct answer.
Why Option C is Correct:Prompt Builder's ability to generate contextual summaries and integrate them into specific record pages via Lightning components aligns with the team's requirements, as supported by Salesforce documentation.
References:
* Salesforce Agentforce Documentation: Prompt Builder > Embedding Prompts- Details placement on record pages.
* Trailhead: Build Prompt Templates in Agentforce- Covers summaries from object data.
* Salesforce Help: Customize Record Pages with AI- Confirms Prompt Builder integration.
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Question 35

An administrator is responsible for ensuring the security and reliability of Universal Containers' (UC) CRM data. UC needs enhanced data protection and up-to-date AI capabilities. UC also needs to include relevant information from a Salesforce record to be merged with the prompt.
Which feature in the Einstein Trust Layer best supports UC's need?

Correct Answer: B
Dynamic grounding with secure data retrieval is a key feature in Salesforce's Einstein Trust Layer, which provides enhanced data protection and ensures that AI-generated outputs are both accurate and securely sourced. This feature allows relevant Salesforce data to be merged into the AI-generated responses, ensuring that the AI outputs are contextually aware and aligned with real-time CRM data.
Dynamic grounding means that AI models are dynamically retrieving relevant information from Salesforce records (such as customer records, case data, or custom object data) in a secure manner. This ensures that any sensitive data is protected during AI processing and that the AI model's outputs are trustworthy and reliable for business use.
The other options are less aligned with the requirement:
* Data masking refers to obscuring sensitive data for privacy purposes and is not related to merging Salesforce records into prompts.
* Zero-data retention policy ensures that AI processes do not store any user data after processing, but this does not address the need to merge Salesforce record information into a prompt.
References:
* Salesforce Developer Documentation on Einstein Trust Layer
* Salesforce Security Documentation for AI and Data Privacy
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