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[General] Agentforce-Specialist Valid Exam Answers | New Agentforce-Specialist Dumps Pdf

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【General】 Agentforce-Specialist Valid Exam Answers | New Agentforce-Specialist Dumps Pdf

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Salesforce Agentforce-Specialist Exam Syllabus Topics:
TopicDetails
Topic 1
  • 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 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 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 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 (Q28-Q33):NEW QUESTION # 28
Universal Containers (UC) has configured an Agentforce Data Library using Knowledge articles. When testing in Agent Builder and the Experience Cloud site, the agent is not responding with grounded Knowledge article information. However, when tested in Prompt Builder, the response returns correctly. What should UC do to troubleshoot the issue?
  • A. Ensure the assigned User permission set includes access to the prompt template used to access the Knowledge articles.
  • B. Create a new permission set that assigns "Manage Knowledge" and assign it to the Agentforce Service Agent User.
  • C. Ensure the Data Cloud User permission set has been assigned to the Agentforce Service Agent User.
Answer: C
Explanation:
UC has set up an Agentforce Data Library with Knowledge articles, and while Prompt Builder retrieves the data correctly, the agent fails to do so in Agent Builder and Experience Cloud. Let's troubleshoot the issue.
* Option A: Create a new permission set that assigns "Manage Knowledge" and assign it to the Agentforce Service Agent User.The "Manage Knowledge" permission is for authoring and managing Knowledge articles, not for reading or retrieving them in an agent context. The Agentforce Service Agent User (a system user) needs read access to Knowledge, not management rights. This option is excessive and irrelevant to the grounding issue, making it incorrect.
* Option B: Ensure the assigned User permission set includes access to the prompt template used to access the Knowledge articles.Prompt templates in Prompt Builder don't require specific permissions beyond general Einstein Generative AI access. Since the Prompt Builder test works, the template and its grounding are accessible to the testing user. The issue lies with the agent's runtime access, not the template itself, making this incorrect.
* Option C: Ensure the Data Cloud User permission set has been assigned to the Agentforce Service Agent User.When Knowledge articles are grounded via an Agentforce Data Library, they are often ingested into Data Cloud for indexing and retrieval. The Agentforce Service Agent User, which runs the agent, needs the "Data Cloud User" permission set (or equivalent) to access Data Cloud resources, including the Data Library. If this permission is missing, the agent cannot retrieve Knowledge article data during runtime (e.g., in Agent Builder or Experience Cloud), even though Prompt Builder (running under a different user context) succeeds. This is a common setup oversight and aligns with the symptoms, making it the correct answer.
Why Option C is Correct:
The Agentforce Service Agent User's lack of Data Cloud access explains the failure in agent-driven contexts while Prompt Builder (likely run by an admin with broader permissions) succeeds. Assigning the "Data Cloud User" permission set resolves this, per Salesforce documentation.
References:
Salesforce Agentforce Documentation: Data Library Setup > Permissions - Requires Data Cloud access for agents.
Trailhead: Ground Your Agentforce Prompts - Notes Data Cloud User permission for Knowledge grounding.
Salesforce Help: Agentforce Security > Agent User Setup - Lists required permission sets.

NEW QUESTION # 29
Universal Containers' current AI data masking rules do not align with organizational privacy and security policies and requirements.
What should An Agentforce recommend to resolve the issue?
  • A. Enable data masking for sandbox refreshes.
  • B. Add new data masking rules in LLM setup.
  • C. Configure data masking in the Einstein Trust Layer setup.
Answer: C
Explanation:
When Universal Containers' AI data masking rules do not meet organizational privacy and security standards, the Agentforce Specialist should configure the data masking rules within the Einstein Trust Layer. The Einstein Trust Layer provides a secure and compliant environment where sensitive data can be masked or anonymized to adhere to privacy policies and regulations.
* Option A, enabling data masking for sandbox refreshes, is related to sandbox environments, which are separate from how AI interacts with production data.
* Option C, adding masking rules in the LLM setup, is not appropriate because data masking is managed through the Einstein Trust Layer, not the LLM configuration.
The Einstein Trust Layer allows for more granular control over what data is exposed to the AI model and ensures compliance with privacy regulations.
Salesforce Agentforce Specialist References:
For more information, refer to: https://help.salesforce.com/s/articleView?id=sf.
einstein_trust_layer_data_masking.htm

NEW QUESTION # 30
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. Train LLM with data using different writing styles including word choice, intensifiers, emojis, and punctuation.
  • B. Include multiple-choice questions within the prompt to test the LLM's understanding of the context.
  • 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 # 31
A business stakeholder wants to use Al to generate a summary based on Data Cloud data.
Which method(s) should the stakeholder use to access Data Cloud data from Prompt Builder?
  • A. Using only external APIs to import Data Cloud data into Prompt Builder
  • B. Using Data Cloud related lists and fetching Data Cloud data using prompt-initiated flows
  • C. Accessing data model objects (DMQs) directly in Flex templates, using Data Cloud related lists, and fetching Data Cloud data using prompt-initiated flows
Answer: B
Explanation:
The Prompt Builder and Data Cloud Integration Guide explains that Data Cloud information can be accessed directly through Data Cloud related lists or prompt-initiated flows, which fetch relevant data dynamically. The documentation states: "Prompt Builder supports retrieving Data Cloud data using related lists for contextual grounding or invoking flows that query Data Cloud objects at runtime. This enables AI prompts to generate summaries, recommendations, or insights directly from unified customer profiles." Option A is incorrect because direct access to data model objects (DMOs) in Flex templates is not supported in Prompt Builder. Option C (external APIs) is unnecessary, as Prompt Builder has native integration with Data Cloud.
Thus, Option B is the correct and Salesforce-documented method to access Data Cloud data from Prompt Builder.
References (AgentForce Documents / Study Guide):
* Salesforce Prompt Builder Guide: "Integrating with Data Cloud"
* AgentForce Study Guide: "Fetching Data Cloud Data with Prompt-Initiated Flows"
* Salesforce Data Cloud Documentation: "Using Related Lists in Prompt Templates"

NEW QUESTION # 32
Universal Containers has implemented an agent that answers questions based on Knowledge articles. Which topic and Agent Action will be shown in the Agent Builder?
  • A. General Q&A topic and Knowledge Article Answers action.
  • B. General FAQ topic and Answers Questions with Knowledge Action.
  • C. General CRM topic and Answers Questions with LLM Action.
Answer: B
Explanation:
Comprehensive and Detailed In-Depth Explanation:
UC's agent answers questions using Knowledge articles, configured in Agent Builder. Let's identify the topic and action.
* Option A: General Q&A topic and Knowledge Article Answers action."General Q&A" is not a standard topic name in Agentforce, and "Knowledge Article Answers" isn't a predefined action. This lacks specificity and doesn't match documentation, making it incorrect.
* Option B: General CRM topic and Answers Questions with LLM Action."General CRM" isn't a default topic, and "Answers Questions with LLM" suggests raw LLM responses, not Knowledge- grounded ones. This doesn't align with the Knowledge focus, making it incorrect.
* Option C: General FAQ topic and Answers Questions with Knowledge Action.In Agent Builder, the "General FAQ" topic is a common default or starting point for question-answering agents. The
"Answers Questions with Knowledge" action (sometimes styled as "Answer with Knowledge") is a prebuilt action that retrieves and grounds responses with Knowledge articles. This matches UC's implementation and is explicitly supported in documentation, making it the correct answer.
Why Option C is Correct:
"General FAQ" and "Answers Questions with Knowledge" are the standard topic-action pair for Knowledge- based question answering in Agentforce, per Salesforce resources.
References:
Salesforce Agentforce Documentation: Agent Builder > Actions- Lists "Answers Questions with Knowledge." Trailhead: Build Agents with Agentforce- Describes FAQ topics with Knowledge actions.
Salesforce Help: Knowledge in Agentforce- Confirms this configuration.

NEW QUESTION # 33
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