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Quiz 2026 Salesforce Agentforce-Specialist–Reliable Exam Lab Questions

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Salesforce Agentforce-Specialist Exam Syllabus Topics:

Topic
Details

Topic 1

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 2

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 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 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 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.

>> Agentforce-Specialist Exam Lab Questions <<

Free PDF Quiz Agentforce-Specialist - The Best Salesforce Certified Agentforce Specialist Exam Lab Questions

After cracking the Salesforce Certified Agentforce Specialist (Agentforce-Specialist) exam you will receive the credential badge. It will pave your way toward well-paying jobs or promotions in any reputed tech company. At PDF4Test have customizable Salesforce Agentforce-Specialist practice exams for the students to review and improve their preparation. The Salesforce Agentforce-Specialist Practice Test material product of PDF4Test are created by experts with the dedication to help customers crack the Salesforce Agentforce-Specialist exam on the first attempt.

Salesforce Certified Agentforce Specialist Sample Questions (Q81-Q86):

NEW QUESTION # 81
How does the AI Retriever function within Data Cloud?

A. It monitors and aggregates data quality metrics across various data pipelines to ensure only high- integrity data is used for strategic decision-making.
B. It automatically extracts and reformats raw data from diverse sources into standardized datasets for use in historical trend analysis and forecasting.
C. It performs contextual searches over an indexed repository to quickly fetch the most relevant documents, enabling grounding AI responses with trustworthy, verifiable information.

Answer: C

Explanation:
Comprehensive and Detailed In-Depth Explanation:The AI Retriever is a key component in Salesforce Data Cloud, designed to support AI-driven processes like Agentforce by retrieving relevant data. Let's evaluate each option based on its documented functionality.
* Option A: It performs contextual searches over an indexed repository to quickly fetch the most relevant documents, enabling grounding AI responses with trustworthy, verifiable information.
The AI Retriever in Data Cloud uses vector-based search technology to query an indexed repository (e.
g., documents, records, or ingested data) and retrieve the most relevant results based on context. It employs embeddings to match user queries or prompts with stored data, ensuring AI responses (e.g., in Agentforce prompt templates) are grounded in accurate, verifiable information from Data Cloud. This enhances trustworthiness by linking outputs to source data, making it the primary function of the AI Retriever. This aligns with Salesforce documentation and is the correct answer.
* Option B: It monitors and aggregates data quality metrics across various data pipelines to ensure only high-integrity data is used for strategic decision-making.Data quality monitoring is handled by other Data Cloud features, such as Data Quality Analysis or ingestion validation tools, not the AI Retriever. The Retriever's role is retrieval, not quality assessment or pipeline management. This option is incorrect as it misattributes functionality unrelated to the AI Retriever.
* Option C: It automatically extracts and reformats raw data from diverse sources into standardized datasets for use in historical trend analysis and forecasting.Data extraction and standardization are part of Data Cloud's ingestion and harmonization processes (e.g., via Data Streams or Data Lake), not the AI Retriever's function. The Retriever works with already-indexed data to fetch results, not to process or reformat raw data. This option is incorrect.
Why Option A is Correct:The AI Retriever's core purpose is to perform contextual searches over indexed data, enabling AI grounding with reliable information. This is critical for Agentforce agents to provide accurate responses, as outlined in Data Cloud and Agentforce documentation.
References:
* Salesforce Data Cloud Documentation: AI Retriever- Describes its role in contextual searches for grounding.
* Trailhead: Data Cloud for Agentforce- Explains how the AI Retriever fetches relevant data for AI responses.
* Salesforce Help: Grounding with Data Cloud- Confirms the Retriever's search functionality over indexed repositories.

NEW QUESTION # 82
Which scenario best demonstrates when an Agentforce Data Library is most useful for improving an AI agent' s response accuracy?

A. When data is being retrieved from Snowflake using zero-copy for vectorization and retrieval.
B. When the AI agent must provide answers based on a curated set of policy documents that are stored, regularly updated, and indexed in the data library.
C. When the AI agent needs to combine data from disparate sources based on mutually common data, such as Customer Id and Product Id for grounding.

Answer: B

Explanation:
Comprehensive and Detailed In-Depth Explanation:The Agentforce Data Library enhances AI accuracy by grounding responses in curated, indexed data. Let's assess the scenarios.
* Option A: When the AI agent must provide answers based on a curated set of policy documents that are stored, regularly updated, and indexed in the data library.The Data Library is designed to store and index structured content (e.g., Knowledge articles, policy documents) for semantic search and grounding. It excels when an agent needs accurate, up-to-date responses from a managed corpus, like policy documents, ensuring relevance and reducing hallucinations. This is a prime use case per Salesforce documentation, making it the correct answer.
* Option B: When the AI agent needs to combine data from disparate sources based on mutually common data, such as Customer Id and Product Id for grounding.Combining disparate sources is more suited to Data Cloud's ingestion and harmonization capabilities, not the Data Library, which focuses on indexed content retrieval. This scenario is less aligned, making it incorrect.
* Option C: When data is being retrieved from Snowflake using zero-copy for vectorization and retrieval.Zero-copy integration with Snowflake is a Data Cloud feature, but the Data Library isn't specifically tied to this process-it's about indexed libraries, not direct external retrieval. This is a different context, making it incorrect.
Why Option A is Correct:The Data Library shines in curated, indexed content scenarios like policy documents, improving agent accuracy, as per Salesforce guidelines.
References:
* Salesforce Agentforce Documentation: Data Library > Use Cases- Highlights curated content grounding.
* Trailhead: Ground Your Agentforce Prompts- Describes Data Library accuracy benefits.
* Salesforce Help: Agentforce Data Library- Confirms policy document scenario.

NEW QUESTION # 83
Choose 1 option.
Universal Containers (UC) is preparing to use the Agentforce Testing Center to ensure the reliability of a new agent. UC has a CSV file with test cases and is reviewing the documentation to understand best practices and limitations.
Which best practice should the company follow to avoid modifying CRM data while running tests in the Testing Center?

A. Run tests in the production environment to ensure real-time data accuracy.
B. Limit the number of test cases to 50 per test to minimize data changes.
C. Use the Testing Center only in the sandbox environment.

Answer: C

Explanation:
According to the AgentForce Testing and Validation Guidelines, all automated or large-scale test runs in Testing Center should be executed in a sandbox environment to prevent any unintended modifications to live CRM data.
Running tests in production can trigger record updates, create cases, or call actions that alter live data, violating best practice standards for safe validation. Testing in a sandbox ensures the environment mirrors production logic while maintaining data isolation.
Option A contradicts this best practice, as production testing risks data integrity. Option B does not prevent data changes - limiting test volume does not safeguard against unintended record modifications.
Therefore, the correct approach is Option C - Use the Testing Center only in the sandbox environment to maintain data safety and compliance.
Reference: AgentForce Testing Center Documentation - "Running Safe and Isolated Tests in Sandbox Environments."

NEW QUESTION # 84
An Agentforce turned on Einstein Generative AI in Setup. Now, the Agentforce Specialist would like to create custom prompt templates in Prompt Builder. However, they cannot access Prompt Builder in the Setup menu.
What is causing the problem?

A. The large language model (LLM) was not configured correctly in Data Cloud.
B. The Prompt Template User permission set was not assigned correctly.
C. The Prompt Template Manager permission set was not assigned correctly.

Answer: C

Explanation:
In order to access and create custom prompt templates inPrompt Builder, the Agentforce Specialist must have thePrompt Template Managerpermission set assigned. Without this permission, they will not be able to accessPrompt Builderin the Setup menu, even thoughEinstein Generative AIis enabled.
* Option Bis correct because thePrompt Template Managerpermission set is required to usePrompt Builder.
* Option A(Prompt Template User permission set) is incorrect because this permission allows users to use prompts, but not create or manage them.
* Option C(LLM configuration in Data Cloud) is unrelated to the ability to accessPrompt Builder.
:
Salesforce Prompt Builder Permissions:https://help.salesforce.com/s/articleView?id=sf.
prompt_builder_permissions.htm

NEW QUESTION # 85
Universal Containers (UC) wants to improve the efficiency of addressing customer questions and reduce agent handling time with AI- generated responses. The agents should be able to leverage their existing knowledge base and identify whether the responses are coming from the large language model (LLM) or from Salesforce Knowledge.
Which step should UC take to meet this requirement?

A. Turn on Service AI Grounding, Grounding with Case, and Service Replies.
B. Turn on Service AI Grounding and Grounding with Knowledge.
C. Turn on Service Replies, Service AI Grounding, and Grounding with Knowledge.

Answer: B

Explanation:
To meetUniversal Containers'goal of improving efficiency and reducing agent handling time with AI- generated responses, the best approach is to enableService Replies,Service AI Grounding, andGrounding with Knowledge.
* Service Repliesgenerates responses automatically.
* Service AI Groundingensures that the AI is using relevant case data.
* Grounding with Knowledgeensures that responses are backed by Salesforce Knowledge articles, allowing agents to identify whether a response is coming from theLLMorSalesforce Knowledge.
* Option Cdoes not includeService Replies, which is necessary for generating AI responses.
* Option Alacks theGrounding with Knowledge, which is essential for identifying response sources.
For more details, refer toSalesforce Service AI documentationon grounding and service replies.

NEW QUESTION # 86
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