PASS GUARANTEED QUIZ PERFECT SALESFORCE - AGENTFORCE-SPECIALIST - VALID SALESFORCE CERTIFIED AGENTFORCE SPECIALIST TEST DISCOUNT

Pass Guaranteed Quiz Perfect Salesforce - Agentforce-Specialist - Valid Salesforce Certified Agentforce Specialist Test Discount

Pass Guaranteed Quiz Perfect Salesforce - Agentforce-Specialist - Valid Salesforce Certified Agentforce Specialist Test Discount

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Tags: Valid Agentforce-Specialist Test Discount, Valid Exam Agentforce-Specialist Registration, Agentforce-Specialist Test Practice, Agentforce-Specialist Simulated Test, Hot Agentforce-Specialist Questions

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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 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 3
  • 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 4
  • 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 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 (Q130-Q135):

NEW QUESTION # 130
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. Create a new permission set that assigns "Manage Knowledge" and assign it to the Agentforce Service Agent User.
  • B. Ensure the assigned User permission set includes access to the prompt template used to access the Knowledge articles.
  • C. Ensure the Data Cloud User permission set has been assigned to the Agentforce Service Agent User.

Answer: C

Explanation:
Comprehensive and Detailed In-Depth 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 # 131
Universal Containers has seen a high adoption rate of a new feature that uses generative AI to populate a summary field of a custom object, Competitor Analysis. All sales users have the same profile but one user cannot see the generative AlI-enabled field icon next to the summary field.
What is the most likely cause of the issue?

  • A. The user does not have the Prompt Template User permission set assigned.
  • B. The prompt template associated with summary field is not activated for that user.
  • C. The user does not have the field Generative AI User permission set assigned.

Answer: C

Explanation:
In Salesforce, Generative AI capabilities are controlled by specific permission sets. To use features such as generating summaries with AI, users need to have the correct permission sets that allow access to these functionalities.
* Generative AI User Permission Set: This is a key permission set required to enable the generative AI capabilities for a user. In this case, the missingGenerative AI Userpermission set prevents the user from seeing the generative AI-enabled field icon. Without this permission, the generative AI feature in the Competitor Analysis custom object won't be accessible.
* Why not A?ThePrompt Template Userpermission set relates specifically to users who need access to prompt templates for interacting with Einstein GPT, but it's not directly related to the visibility of AI- enabled field icons.
* Why not B?While a prompt template might need to be activated, this is not the primary issue here. The question states that other users with the same profile can see the icon, so the problem is more likely to be permissions-based for this particular user.
For more detailed information, you can review Salesforce documentation onpermission setsrelated to AI capabilities atSalesforce AI DocumentationandEinstein GPTpermissioning guidelines.


NEW QUESTION # 132
After creating a foundation model in Einstein Studio, which hyperparameter should An Agentforce use to adjust the balance between consistency and randomness of a response?

  • A. Presence Penally
  • B. Temperature
  • C. Variability

Answer: B

Explanation:
The Temperature hyperparameter controls the randomness of model outputs:
* Low Temperature (e.g., 0.2): More deterministic, consistent responses.
* High Temperature (e.g., 1.0): More creative, varied responses.
* Presence Penalty (Option A): Discourages repetition of tokens, unrelated to randomness.
* Variability (Option B): Not a standard hyperparameter in Einstein Studio.
References:
* Einstein Studio Documentation: Model Hyperparameters
* Explicitly states "Temperature adjusts the balance between predictable and random outputs."


NEW QUESTION # 133
Universal Containers (UC) uses a file upload-based data library and custom prompt to support AI-driven training content. However, users report that the AI frequently returns outdated documents. Which corrective action should UC implement to improve content relevancy?

  • A. Configure a custom retriever that includes a filter condition limiting retrieval to documents updated within a defined recent period, ensuring that only current content is used for AI responses.
  • B. Continue using the default retriever without filters, because periodic re-uploads will eventually phase out outdated documents without further configuration or the need for custom retrievers.
  • C. Switch the data library source from file uploads to a Knowledge-based data library, because Salesforce Knowledge bases automatically manage document recency, ensuring current documents are returned.

Answer: A

Explanation:
Comprehensive and Detailed In-Depth Explanation:UC's issue is that theirfile upload-based Data Library (where PDFs or documents are uploaded and indexed into Data Cloud's vector database) is returning outdated training content in AI responses. To improve relevancy by ensuring only current documents are retrieved, the most effective solution is toconfigure a custom retriever with a filter(Option B). In Agentforce, a custom retriever allows UC to define specific conditions-such as a filter on a "Last Modified Date" or similar timestamp field-to limit retrieval to documents updated within a recent period (e.g., last 6 months). This ensures the AI grounds its responses in the most current content, directly addressing the problem of outdated documents without requiring a complete overhaul of the data source.
* Option A: Switching to aKnowledge-based Data Library(using Salesforce Knowledge articles) could work, as Knowledge articles have versioning and expiration features to manage recency. However, this assumes UC's training content is already in Knowledge articles (not PDFs) and requires migrating all uploaded files, which is a significant shift not justified by the question's context. File-based libraries are still viable with proper filtering.
* Option B: This is the best corrective action. A custom retriever with a date filter leverages the existing file-based library, refining retrieval without changing the data source, making it practical and targeted.
* Option C: Relying on periodic re-uploads with the default retriever is passive andinefficient. It doesn't guarantee recency (old files remain indexed until manually removed) and requires ongoing manual effort, failing to proactively solve the issue.
Option B provides a precise, scalable solution to ensure content relevancy in UC's AI-driven training system.
References:
* Salesforce Agentforce Documentation: "Custom Retrievers for Data Libraries" (Salesforce Help:
https://help.salesforce.com/s/articleView?id=sf.agentforce_custom_retrievers.htm&type=5)
* Salesforce Data Cloud Documentation: "Filter Retrieval for AI" (https://help.salesforce.com/s
/articleView?id=sf.data_cloud_retrieval_filters.htm&type=5)
* Trailhead: "Manage Data Libraries in Agentforce" (https://trailhead.salesforce.com/content/learn
/modules/agentforce-data-libraries)


NEW QUESTION # 134
Universal Containers (UC) is tracking web activities in Data Cloud for a unified contact, and wants to use that in a prompt template to help extract insights from the data.
Assuming that the Contact object is one of the objects associated with the prompt template, what is a valid way for DC to do this?

  • A. Create a prompt template that takes a list of all Data Cloud activity records as input to pass to the large language model (LLM).
  • B. Call the prompt directly from Data Cloud with a web tracing activity included in the prompt definition.
  • C. Add the activity records as an enrichment related list to the Contact then pass the Contact into a prompt template workspace using related list grounding.

Answer: C

Explanation:
To integrate web activity data from Data Cloud into a prompt template, the correct approach is to enrich the Contact object with the activity records as a related list and use related list grounding (Option B).Here's why:
* Data Cloud Integration: Data Cloud unifies web activity data and associates it with the unified Contact record. By adding these activities as a related list to the Contact, the data becomes accessible to the prompt template.
* Prompt Template Grounding: Salesforce prompt templates support grounding on related records.
When the Contact is passed to the prompt template, the template can reference the related web activity records (via the related list) to extract insights.
* Structured Data Handling: This method aligns with Salesforce best practices for grounding, ensuring the large language model (LLM) receives structured, context-rich data without overwhelming it with raw activity lists.
Why Other Options Are Incorrect:
* A. Calling the prompt directly from Data Cloud: Prompt templates are invoked within Salesforce, not directly from Data Cloud. Grounding requires associating data with Salesforce objects, not ad-hoc web activity inclusion.
* C. Passing a list of activity records as input: While technically possible, this bypasses Salesforce's grounding framework, which relies on object relationships. It also risks exceeding LLM input limits and lacks scalability.
References:
* Salesforce Data Cloud Implementation Guide: Explains how to enrich standard/custom objects with related data for AI use cases.
* Prompt Template Documentation: Highlights grounding on related lists to leverage contextual data for LLM prompts.
* Trailhead Module: "Einstein Prompt Builder Basics" demonstrates grounding techniques using related records.


NEW QUESTION # 135
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