SALESFORCE AGENTFORCE-SPECIALIST EXAM SIMS - TEST AGENTFORCE-SPECIALIST CENTRES

Salesforce Agentforce-Specialist Exam Sims - Test Agentforce-Specialist Centres

Salesforce Agentforce-Specialist Exam Sims - Test Agentforce-Specialist Centres

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Salesforce Agentforce-Specialist Exam Syllabus Topics:

TopicDetails
Topic 1
  • 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 2
  • 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 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
  • 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 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.

Salesforce Certified Agentforce Specialist Sample Questions (Q140-Q145):

NEW QUESTION # 140
What is the main benefit of using a Knowledge article in an Agentforce Data Library?

  • A. It provides a structured, searchable repository of approved documents so the agent can retrieve reliable information for each inquiry..
  • B. Only the retriever for Knowledge articles allows for agents to access Knowledge from both inside the platform and on a customer's website.
  • C. The retriever for Knowledge articles has better accuracy and performance than the default retriever.

Answer: A

Explanation:
Why is "A structured, searchable repository of approved documents" the correct answer?
Using a Knowledge Article in an Agentforce Data Library ensures that agents can quickly access reliable and pre-approved information during customer interactions.
Key Benefits of Knowledge Articles in an Agentforce Data Library:
* Ensures Information Accuracy and Consistency
* Knowledge articles provide approved, well-structured responses, reducing the risk of misinformation.
* This ensures customer service consistency across different agents.
* Improves Searchability and AI-Grounded Responses
* Articles are indexed and retrieved efficiently by AI-powered search engines.
* AI-generated responses are grounded in accurate, structured knowledge, improving response quality.
* Enhances Customer Support and Agent Productivity
* Agents spend less time searching for information and more time resolving customer inquiries.
* Einstein AI can suggest the most relevant articles based on conversation context.
Why Not the Other Options?
# A. Only the retriever for Knowledge articles allows for agents to access Knowledge from both inside the platform and on a customer's website.
* Incorrect because other retrievers (e.g., standard Salesforce Data Cloud retrievers) can also provide knowledge access.
* Knowledge articles can be accessed via multiple retrieval mechanisms, not just one specific retriever.
# C. The retriever for Knowledge articles has better accuracy and performance than the default retriever.
* Incorrect because retriever accuracy depends on indexing and search configuration, not the article type.
* The default retriever works just as efficiently when properly configured.
Agentforce Specialist References
* Salesforce AI Specialist Material confirms that Knowledge articles provide structured, searchable, and approved information for AI-grounded responses.


NEW QUESTION # 141
What is a SalesforceAgentforce Specialistable to configure in Data Masking within the Einstein Trust Layer?

  • A. The encryption keys for masking
  • B. The profiles exempt from masking
  • C. The privacy data entities to be masked

Answer: C

Explanation:
In the Einstein Trust Layer, the SalesforceAgentforce Specialistcan configure privacy data entities to be masked (Option C). This ensures sensitive or personally identifiable information (PII) is obfuscated when processed by AI models.
* Data Masking Configuration:
* TheAgentforce Specialistdefines which fields or data types (e.g., email, phone number, Social Security Number) should be masked. For example, masking the Email field in a prompt response to protect user privacy.
* This is done through declarative settings in Salesforce, where entities (standard or custom fields) are flagged for masking.
* Why Other Options Are Incorrect:
* A. Profiles exempt from masking: Exemptions are typically managed via permissions (e.g., field-level security), not directly within Einstein Trust Layer's Data Masking settings.
* B. Encryption keys for masking: Encryption is separate from masking. Masking involves obfuscation (e.g., replacing "john@example.com" with "@"), not encryption, which uses keys to secure data.
References:
* Einstein Trust Layer Documentation: States that Data Masking allows admins to "define which fields should be masked to protect sensitive data."
* Trailhead Module: "Einstein Trust Layer Basics" explains configuring privacy entities for masking.
* Salesforce Help Article: "Secure AI with Einstein Trust Layer" details masking configurations for privacy compliance.


NEW QUESTION # 142
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?

  • A. Model Builder
  • B. Agent Builder
  • C. Prompt Builder

Answer: C

Explanation:
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.


NEW QUESTION # 143
How should an organization use the Einstein Trust layer to audit, track, and view masked data?

  • A. Utilize the audit trail that captures and stores all LLM submitted prompts in Data Cloud.
  • B. In Setup, use Prompt Builder to send a prompt to the LLM requesting for the masked data.
  • C. Access the audit trail in Setup and export all user-generated prompts.

Answer: A

Explanation:
TheEinstein Trust Layeris designed to ensure transparency, compliance, and security for organizations leveraging Salesforce's AI and generative AI capabilities. Specifically, for auditing, tracking, and viewing masked data, organizations can utilize:
* Audit Trail in Data Cloud: Theaudit trailcaptures and stores all prompts submitted to large language models (LLMs), ensuring that sensitive or masked data interactions are logged. This allows organizations to monitor and audit all AI-generated outputs, ensuring that data handling complies with internal and regulatory guidelines. TheData Cloudprovides the infrastructure for managing and accessing this audit data.
* Why not B?UsingPrompt Builderin Setup to send prompts to the LLM is for creating and managing prompts, not for auditing or tracking data. It does not interact directly with the audit trail functionality.
* Why not C?Although the audit trail can be accessed in Setup, the user-generated prompts are primarily tracked in the Data Cloud for broader control, auditing, and analysis. Setup is not the primary tool for exporting or managing these audit logs.
More information on auditing AI interactions can be found in theSalesforce AI Trust Layerdocumentation, which outlines how organizations can manage and track generative AI interactions securely.


NEW QUESTION # 144
Universal Containers has grounded a prompt template with a related list. During user acceptance testing (UAT), users are not getting the correct responses. What is causing this issue?

  • A. The related list is Read Only.
  • B. The related list prompt template option is not enabled.
  • C. The related list is not on the parent object's page layout.

Answer: C

Explanation:
Comprehensive and Detailed In-Depth Explanation:UC has grounded a prompt template with a related list, but the responses are incorrect during UAT. Grounding with related lists in Agentforce allows the AI to access data from child records linked to a parent object. Let's analyze the options.
* Option A: The related list is Read Only.Read-only status (e.g., via field-level security or sharing rules) might limit user edits, but it doesn't inherently prevent the AI from accessing related list data for grounding, as long as the running user (or system context) has read access. This is unlikely to cause incorrect responses and is not a primary consideration, making it incorrect.
* Option B: The related list prompt template option is not enabled.There's no specific "related list prompt template option" toggle in Prompt Builder. When grounding with a Record Snapshot or Flex template, related lists are included if properly configured (e.g., via object relationships). This option seems to be a misphrasing and doesn't align with documented settings, making it incorrect.
* Option C: The related list is not on the parent object's page layout.In Agentforce, grounding with related lists relies on the related list being defined and accessible in the parent object's metadata, often tied to its presence on the page layout. If the related list isn't on the layout, the AI might not recognize or retrieve its data correctly, leading to incomplete or incorrect responses. Salesforce documentation notes that related list data availability can depend on layout configuration, making this a plausible and common issue during UAT, and thus the correct answer.
Why Option C is Correct:The absence of the related list from the parent object's page layout can disrupt data retrieval for grounding, leading to incorrect AI responses. This is a known configuration consideration in Agentforce setup and testing, as per official guidance.
References:
* Salesforce Agentforce Documentation: Grounding with Related Lists- Notes dependency on page layout configuration.
* Trailhead: Ground Your Agentforce Prompts- Highlights related list setup for accurate grounding.
* Salesforce Help: Troubleshoot Prompt Responses- Lists layout issues as a common grounding problem.


NEW QUESTION # 145
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