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[General] 100% Pass Salesforce - Perfect Agentforce-Specialist Training Pdf

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【General】 100% Pass Salesforce - Perfect Agentforce-Specialist Training Pdf

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Salesforce Agentforce-Specialist Exam Syllabus Topics:
TopicDetails
Topic 1
  • 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 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 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 4
  • 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.
Topic 5
  • 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.

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Salesforce Certified Agentforce Specialist Sample Questions (Q31-Q36):NEW QUESTION # 31
Universal Containers wants to implement a customer verification process where sensitive account information can only be accessed after the customer passes identity verification. The agent must enforce this security rule deterministically without allowing the large language model (LLM) to bypass the verification requirement.
What should an Agentforce Specialist recommend as the best solution?
  • A. Include detailed verification instructions in the agent's topic instructions explaining when customers should be verified and rely on the LLM to follow these guidelines consistently across all interactions.
  • B. Use context variables to store verification status in the messaging session and configure the agent to check these variables through natural language prompts during each sensitive action.
  • C. Create a custom variable IsCustomerVerified set by a verification action, then apply a conditional filter using the expression IsCustomerVerified equals true to all sensitive data actions, ensuring deterministic access control that the LLM can't alter.
Answer: C
Explanation:
The AgentForce Security and Deterministic Logic Guide specifies that sensitive actions must be gated through conditional filters linked to verification variables, not through natural language. It states: "For any process requiring secure, deterministic access, create a custom variable (e.g., IsCustomerVerified) that stores the verification status as a Boolean. Apply a filter expression to all protected actions (e.g., IsCustomerVerified
= true). This ensures the LLM cannot bypass or alter access logic."
This configuration ensures security and determinism because the execution of sensitive actions is programmatically enforced, not dependent on the LLM's understanding.
Option A is incorrect because natural language-based checks are non-deterministic.
Option B relies solely on topic instructions, which can be ignored or misinterpreted by the LLM.
Therefore, Option C is the only solution that provides deterministic, system-enforced access control.
References (AgentForce Documents / Study Guide):
AgentForce Security Configuration Guide: "Using Conditional Filters for Deterministic Access" AgentForce Implementation Handbook: "Verification Variables and Secure Action Flow" AgentForce Study Guide: "Protecting Sensitive Data in AI Workflows"

NEW QUESTION # 32
Universal Containers would like to route SMS text messages to a service rep from an Agentforce Service Agent. Which Service Channel should the company use in the flow to ensure it's routed properly?
  • A. Messaging
  • B. Live Agent
  • C. Route Work Action
Answer: A
Explanation:
Comprehensive and Detailed In-Depth Explanation:UC wants to route SMS text messages from an Agentforce Service Agent to a service rep using a flow. Let's identify the correct Service Channel.
* Option A: MessagingIn Salesforce, the "Messaging" Service Channel (part of Messaging for In-App and Web or SMS) handles text-based interactions, including SMS. When integrated with Omni-Channel Flow, the "Route Work" action uses this channel to route SMS messages to agents. This aligns with UC' s requirement for SMS routing, making it the correct answer.
* Option B: Route Work Action"Route Work" is an action in Omni-Channel Flow, not a Service Channel. It uses a channel (e.g., Messaging) to route work, so this is a component, not the channel itself, making it incorrect.
* Option C: Live Agent"Live Agent" refers to an older chat feature, not the current Messaging framework for SMS. It's outdated and unrelated to SMS routing, making it incorrect.
* Option D: SMS ChannelThere's no standalone "SMS Channel" in Salesforce Service Channels-SMS is encompassed within the "Messaging" channel. This is a misnomer, making it incorrect.
Why Option A is Correct:The "Messaging" Service Channel supports SMS routing in Omni-Channel Flow, ensuring proper handoff from the Agentforce Service Agent to a rep, per Salesforce documentation.
References:
* Salesforce Agentforce Documentation: Omni-Channel Integration > Messaging- Details SMS in Messaging channel.
* Trailhead: Omni-Channel Flow Basics- Confirms Messaging for SMS.
* Salesforce Help: Service Channels- Lists Messaging for text-based routing.

NEW QUESTION # 33
When creating a custom retriever in Einstein Studio, which step is considered essential?
  • A. Select the search index, specify the associated data model object (DMO) and data space, and optionally define filters to narrow search results.
  • B. Configure the search index, choose vector or hybrid search, choose the fields for filtering, the data space and model, then define the ranking method.
  • C. Define the output configuration by specifying the maximum number of results to return, and map the output fields that will ground the prompt.
Answer: A
Explanation:
Comprehensive and Detailed In-Depth Explanation:In Salesforce's Einstein Studio (part of the Agentforce ecosystem), creating acustom retrieverinvolves setting up a mechanism to fetch data for AI prompts or responses. Theessential stepis defining the foundation of the retriever: selecting thesearch index, specifying thedata model object (DMO), and identifying thedata space(Option A). These elements establish where and what the retriever searches:
* Search Index: Determines the indexed dataset (e.g., a vector database in Data Cloud) the retriever queries.
* Data Model Object (DMO): Specifies the object (e.g., Knowledge Articles, Custom Objects) containing the data to retrieve.
* Data Space: Defines the scope or environment (e.g., a specific Data Cloud instance) for the data.
Filters are noted as optional in Option A, which is accurate-they enhance precision but aren't mandatory for the retriever to function. This step is foundational because without it, the retriever lacks a target dataset, rendering it unusable.
* Option B: Defining output configuration (e.g., max results, field mapping) is important for shaping the retriever's output, but it's a secondary step. The retriever must first know where to search (A) before output can be configured.
* Option C: This option includes advanced configurations (vector/hybrid search, filtering fields, ranking method), which are valuable but not essential. A basic retriever can operate without specifying search type or ranking, as defaults apply, but it cannot function without a search index, DMO, and data space.
* Option A: This is the minimum required step to create a functional retriever, making it essential.
Option A is the correct answer as it captures the core, mandatory components of retriever setup in Einstein Studio.
References:
* Salesforce Agentforce Documentation: "Custom Retrievers in Einstein Studio" (Salesforce Help:
https://help.salesforce.com/s/ar ... vers.htm&type=5)
* Trailhead: "Einstein Studio for Agentforce" (https://trailhead.salesforce.com/content/learn/modules
/einstein-studio-for-agentforce)

NEW QUESTION # 34
Choose 1 option.
Universal Containers (UC) needs to create a custom prompt template that can be called from a Lightning web component.
Which prompt template type should UC create?
  • A. Field Generation
  • B. Sales Email
  • C. Flex
Answer: C
Explanation:
The AgentForce Developer Integration Guide specifies that Flex prompt templates are the correct type for custom or embedded integrations, such as invoking a prompt from a Lightning Web Component (LWC).
Flex templates are designed for general-purpose use cases and can be called programmatically via Apex, Flow, or LWC APIs. They offer flexible input and output structures, allowing developers to integrate AgentForce reasoning into custom applications and UI components.
Option A, Field Generation, is used to populate or update Salesforce fields, not for external invocation.
Option B, Sales Email, is specific to generating pre-formatted communication messages and cannot be invoked directly from LWCs.
Therefore, the correct template type for a prompt used within a Lightning Web Component is Option C - Flex
, as it is purpose-built for dynamic, reusable, and programmatic use cases.
Reference: AgentForce Developer Guide - "Using Flex Prompt Templates with Lightning Web Components."

NEW QUESTION # 35
Universal Containers (UC) is looking to improve its sales team's productivity by providing real-time insights and recommendations during customer interactions.
Why should UC consider using Agentforce Sales Agent?
  • A. To streamline the sales process and increase conversion rates
  • B. To track customer interactions for future analysis
  • C. To automate the entire sales process for maximum efficiency
Answer: A
Explanation:
Agentforce Sales Agent provides real-time insights and AI-powered recommendations, which are designed to streamline the sales processand help sales representatives focus on key tasks toincrease conversion rates. It offers features like lead scoring, opportunity prioritization, and proactive recommendations, ensuring that sales teams can interact with customers efficiently and close deals faster.
* Option A: While tracking customer interactions is beneficial, it is only part of the broader capabilities offered by Agentforce Sales Agent and is not the primary objective for improving real-time productivity.
* Option B: Agentforce Sales Agent does not automate the entire sales process but provides actionable recommendations to assist the sales team.
* Option C: This aligns with the tool's core purpose of enhancing productivity and driving sales success.
Reference:
"Einstein Next Best Action for Sales Teams | Salesforce Trailhead" .

NEW QUESTION # 36
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