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Pass Guaranteed The Best Salesforce - Agentforce-Specialist - Pdf Salesforce Certified Agentforce Specialist Dumps

TestsDumps Agentforce-Specialist valid test will assist you to pass your Agentforce-Specialist actual test with ease. You will never regret to choose our Agentforce-Specialist exam engine test. Here are some outstanding properties which can benefit all of you. The detailed explanations are offered where available to ensure you fully understand why to choose the correct answers. All the questions cover the main points which the Agentforce-Specialist Actual Exam required. The answers of each question are correct and verified by our IT experts which can ensure you 100% pass.

Salesforce Agentforce-Specialist Exam Syllabus Topics:

Topic
Details

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 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 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.

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Salesforce Agentforce-Specialist Study Material & Latest Agentforce-Specialist Exam Test

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Salesforce Certified Agentforce Specialist Sample Questions (Q26-Q31):

NEW QUESTION # 26
An account manager is preparing for an upcoming customer call and wishes to get a snapshot of key data points from accounts, contacts, leads, and opportunities in Salesforce.
Which feature provides this?

A. Work Summaries
B. Sales Summaries
C. Sales Insight Summary

Answer: C

Explanation:
Sales Insight Summary aggregates key data points from multiple Salesforce objects (accounts, contacts, leads, opportunities) into a consolidated view, enabling account managers to quickly access relevant information for customer calls.
* Option A (Sales Summaries): Typically refers to Einstein-generated summaries of specific interactions (e.g., emails, calls), not multi-object snapshots.
* Option C (Work Summaries): Focuses on summarizing customer service interactions (e.g., chat transcripts), not sales data.
* Option B (Sales Insight Summary): Directly provides a holistic snapshot of sales-related objects, aligning with the scenario.
References:
* Salesforce Help: Sales Insight Overview
* Describes Sales Insight Summary as "a unified view of account, contact, and opportunity data for sales readiness."

NEW QUESTION # 27
Which object stores the conversation transcript between the customer and the agent?

A. Messaging Session
B. Messaging End User
C. Case

Answer: A

Explanation:
Why is "Messaging Session" the correct answer?
In Agentforce, the Messaging Session object stores the conversation transcript between the customer and the agent.
Key Features of the Messaging Session Object:
* Stores the Entire Customer-Agent Conversation
* The Messaging Session object maintains a record of the full chat history, including timestamps, messages, and interactions.
* This ensures that past interactions can be referenced during follow-ups.
* Supports AI-Powered Work Summaries
* Einstein AI uses Messaging Sessions to generate summaries of chat interactions for agents.
* These summaries are stored and accessible for later reference.
* Links with Service Cloud for Case Resolution
* If a conversation escalates into a case, the Messaging Session object can be linked to it.
* This allows support teams to review the conversation history without switching contexts.
Why Not the Other Options?
# A. Messaging End User
* Incorrect because this object stores details about the customer (e.g., name, contact details) but not the conversation transcript.
# C. Case
* Incorrect because Cases store structured service requests but do not contain raw conversation transcripts.
* Instead, cases may reference the Messaging Session object.
Agentforce Specialist References
* Salesforce AI Specialist Material confirms that Messaging Sessions store chat conversations and support Einstein Work Summaries.

NEW QUESTION # 28
In a Knowledge-based data library configuration, what is the primary difference between the identifying fields and the content fields?

A. Identifying fields categorize articles for indexing purposes, while content fields provide a brief summary for display.
B. Identifying fields help locate the correct Knowledge article, while content fields enrich AI responses with detailed information.
C. Identifying fields highlight key terms for relevance scoring, while content fields store the full text of the article for retrieval.

Answer: B

Explanation:
Comprehensive and Detailed In-Depth Explanation:In Agentforce, a Knowledge-based data library (e.g., via Salesforce Knowledge or Data Cloud grounding) uses identifying fields and content fields to support AI responses. Let's analyze their roles.
* Option A: Identifying fields help locate the correct Knowledge article, while content fields enrich AI responses with detailed information.In a Knowledge-based data library,identifying fields(e.g., Title, Article Number, or custom metadata) are used to search and pinpoint the relevant Knowledge article based on user input or context.Content fields(e.g., Article Body, Details) provide the substantive data that the AI uses to generate detailed, enriched responses. This distinction is critical for grounding Agentforce prompts and aligns with Salesforce's documentation on Knowledge integration, making it the correct answer.
* Option B: Identifying fields categorize articles for indexing purposes, while content fields provide a brief summary for display.Identifying fields do more than categorize-they actively locate articles, not just index them. Content fields aren't limited to summaries; they include full article content for response generation, not just display. This option underrepresents their roles and is incorrect.
* Option C: Identifying fields highlight key terms for relevance scoring, while content fields store the full text of the article for retrieval.While identifying fields contribute to relevance (e.g., via search terms), their primary role is locating articles, not just scoring. Content fields do store full text, but their purpose is to enrich responses, not merely enable retrieval. This option shifts focus inaccurately, making it incorrect.
Why Option A is Correct:The primary difference-identifying fields for locating articles and content fields for enriching responses-reflects their roles in Knowledge-based grounding, as per official Agentforce documentation.
References:
* Salesforce Agentforce Documentation: Grounding with Knowledge > Data Library Setup- Defines identifying vs. content fields.
* Trailhead: Ground Your Agentforce Prompts- Explains field roles in Knowledge integration.
* Salesforce Help: Knowledge in Agentforce- Confirms locating and enriching functions.

NEW QUESTION # 29
An Agentforce Specialist is creating a custom action in Agentforce. Which option is available for the Agentforce Specialist to choose for the custom Agent action?

A. Flows
B. SOQL
C. Apex Trigger

Answer: A

Explanation:
Comprehensive and Detailed In-Depth Explanation:The Agentforce Specialist is defining a custom action for an Agentforce agent in Agent Builder. Actions determine what the agent does (e.g., retrieve data, update records). Let's evaluate the options.
* Option A: Apex TriggerApex Triggers are event-driven scripts, not selectable actions in Agent Builder. While Apex can be invoked via other means (e.g., Flows), it's not a direct option for custom agent actions, making this incorrect.
* Option B: SOQLSOQL (Salesforce Object Query Language) is a query language, not an executable action type in Agent Builder. While actions can use queries internally, SOQL isn't a standalone option, making this incorrect.
* Option C: FlowsIn Agentforce Studio's Agent Builder, custom actions can be created using Salesforce Flows. Flows allow complex logic (e.g., data retrieval, updates, or integrations) and are explicitly supported as a custom action type. The specialist can select an existing Flow or create one, making this the correct answer.
* Option D: JavaScriptJavaScript isn't an option for defining agent actions in Agent Builder. It's used in Lightning Web Components, not agent configuration, making this incorrect.
Why Option C is Correct:Flows are a native, flexible option for custom actions in Agentforce, enabling tailored functionality for agents, as per official documentation.
References:
* Salesforce Agentforce Documentation: Agent Builder > Custom Actions- Lists Flows as a supported action type.
* Trailhead: Build Agents with Agentforce- Details Flow-based actions.
* Salesforce Help: Configure Agent Actions- Confirms Flows integration.

NEW QUESTION # 30
Universal Containers (UC) is looking to enhance its operational efficiency. UC has recently adopted Salesforce and is considering implementing Agent to improve its processes.
What is a key reason for implementing Agent?

A. Improving data entry and data cleansing
B. Streamlining workflows and automating repetitive tasks
C. Allowing AI to perform tasks without user interaction

Answer: B

Explanation:
The key reason for implementing Agent is its ability to streamline workflows and automate repetitive tasks
. By leveraging AI, Agent can assist users in handling mundane, repetitive processes, such as automatically generating insights, completing actions, and guiding users through complex processes, all of which significantly improve operational efficiency.
* Option A (Improving data entry and cleansing) is not the primary purpose of Agent, as its focus is on guiding and assisting users through workflows.
* Option B (Allowing AI to perform tasks without user interaction) does not accurately describe the role of Agent, which operates interactively to assist users in real time.
Salesforce Agentforce Specialist References:More details can be found in the Salesforce documentation:
https://help.salesforce.com/s/articleView?id=sf.einstein_copilot_overview.htm

NEW QUESTION # 31
......

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