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Salesforce Agentforce-Specialist Exam Syllabus Topics:

Topic	Details
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	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 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	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.

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Salesforce Certified Agentforce Specialist Sample Questions (Q43-Q48):

NEW QUESTION # 43
Universal Containers is very concerned about security compliance and wants to understand:
Which prompt text is sent to the large language model (LLM)
* How it is masked
* The masked response
What should theAgentforce Specialistrecommend?

A. Enable audit trail in the Einstein Trust Layer.
B. Review the debug logs of the running user.
C. Ingest the Einstein Shield Event logs into CRM Analytics.

Answer: A

Explanation:
To addresssecurity complianceconcerns and provide visibility into theprompt text sent to the LLM, how it ismasked, and themasked response, theAgentforce Specialistshould recommend enabling theaudit trail in the Einstein Trust Layer. This feature captures and logs the prompts sent to the large language model (LLM) along with the masking of sensitive information and the AI's response. This audit trail ensures full transparency and compliance with security requirements.
* Option A (Einstein Shield Event logs)is focused on system events rather than specific AI prompt data.
* Option B (debug logs)would not provide the necessary insight into AI prompt masking or responses.
For further details, refer toSalesforce's Einstein Trust Layer documentationabout auditing and security measures.

NEW QUESTION # 44
Universal Containers (UC) has recently received an increased number of support cases. As a result, UC has hired more customer support reps and has started to assign some of the ongoing cases to newer reps.
Which generative AI solution should the new support reps use to understand the details of a case without reading through each case comment?

A. Einstein Copilot
B. Einstein Sales Summaries
C. Einstein Work Summaries

Answer: C

Explanation:
New customer support reps atUniversal Containerscan useEinstein Work Summariesto quickly understand the details of a case without reading through each case comment.Work Summariesleverage generative AI to provide a concise overview of ongoing cases, summarizing all relevant information in an easily digestible format.
* Einstein Copilotcan assist with a variety of tasks but is not specifically designed for summarizing case details.
* Einstein Sales Summariesare focused on summarizing sales-related activities, which is not applicable for support cases.
For more details, refer toSalesforce documentation on Einstein Work Summaries.

NEW QUESTION # 45
An Agentforce implements Einstein Sales Emails for a sales team. The team wants to send personalized follow-up emails to leads based on their interactions and data stored in Salesforce. The Agentforce Specialist needs to configure the system to use the most accurate and up-to-date information for email generation.
Which grounding technique should the Agentforce Specialist use?

A. Automatic grounding using Draft with Einstein feature
B. Ground with Apex Merge Fields
C. Ground with Record Merge Fields

Answer: A

Explanation:
ForEinstein Sales Emailsto generate personalized follow-up emails, it is crucial to ground the email content with the most up-to-date and accurate information. Grounding refers to connecting the AI model with real- time data. The most appropriate technique in this case isGround with Record Merge Fields. This method ensures that the content in the emails pulls dynamic and accurate data directly from Salesforce records, such as lead or contact information, ensuring the follow-up is relevant and customized based on the specific record.
* Record Merge Fieldsensure the generated emails are highly personalized using data like lead name, company, or other Salesforce fields directly from the records.
* Apex Merge Fieldsare typically more suited for advanced, custom logic-driven scenarios but are not the most straightforward for this use case.
* Automatic grounding using Draft with Einsteinis a different feature where Einstein automatically drafts the email, but it does not specifically ground the content with record-specific data likeRecord Merge Fields.
:
Salesforce Einstein Sales Emails Documentation:https://help.salesforce.com/s/articleView?id=release-notes.
rn_einstein_sales_emails.htm

NEW QUESTION # 46
Northern Trail Outfitters (NTO) wants to configure Einstein Trust Layer in its production org but is unable to see the option on the Setup page.
After provisioning Data Cloud, which step must an Al Specialist take to make this option available to NTO?

A. Turn on Einstein Copilot.
B. Turn on Prompt Builder.
C. Turn on Einstein Generative AI.

Answer: C

Explanation:
For Northern Trail Outfitters (NTO) to configure theEinstein Trust Layer, theEinstein Generative AI feature must be enabled. The Einstein Trust Layer is closely tied to generative AI capabilities, ensuring that AI-generated content complies with data privacy, security, and trust standards.
* Option A(Turning on Einstein Copilot) is unrelated to the setup of the Einstein Trust Layer, which focuses more on generative AI interactions and data handling.
* Option C(Turning on Prompt Builder) is used for configuring and building AI-driven prompts, but it does not enable the Einstein Trust Layer.
SalesforceAgentforce SpecialistReferences:For more details on the Einstein Trust Layer and setup steps:
https://help.salesforce.com/s/articleView?id=sf.einstein_trust_layer_overview.htm

NEW QUESTION # 47
A data scientist needs to view and manage models in Einstein Studio, and also needs to create prompt templates in Prompt Builder. Which permission sets should an Agentforce Specialist assign to the data scientist?

A. Prompt Template Manager and Prompt Template User
B. Prompt Template User and Data Cloud Admin
C. Data Cloud Admin and Prompt Template Manager

Answer: C

Explanation:
Comprehensive and Detailed In-Depth Explanation:
The data scientist requires permissions for Einstein Studio (model management) and Prompt Builder (template creation). Note: "Einstein Studio" may be a misnomer for Data Cloud's model management or a related tool, but we'll interpret based on context. Let's evaluate.
* Option A: Prompt Template Manager and Prompt Template UserThere's no distinct "Prompt Template Manager" or "Prompt Template User" permission set in Salesforce-Prompt Builder access is typically via "Einstein Generative AI User" or similar. This option lacks coverage for Einstein Studio
/Data Cloud, making it incorrect.
* Option B: Data Cloud Admin and Prompt Template ManagerThe "Data Cloud Admin" permission set grants access to manage models in Data Cloud (assumed as Einstein Studio's context), including viewing and editing AI models. "Prompt Template Manager" isn't a real set, but Prompt Builder creation is covered by "Einstein Generative AI Admin" or similar admin-level access (assumed intent).
This combination approximates the needs, making it the closest correct answer despite naming ambiguity.
* Option C: Prompt Template User and Data Cloud Admin"Prompt Template User" isn't a standard set, and user-level access (e.g., Einstein Generative AI User) typically allows execution, not creation.
The data scientist needs to create templates, so this lacks sufficient Prompt Builder rights, making it incorrect.
Why Option B is Correct (with Caveat):
"Data Cloud Admin" covers model management in Data Cloud (likely intended as Einstein Studio), and
"Prompt Template Manager" is interpreted as admin-level Prompt Builder access (e.g., Einstein Generative AI Admin). Despite naming inconsistencies, this fits the requirements per Salesforce permissions structure.
References:
Salesforce Data Cloud Documentation: Permissions- Details Data Cloud Admin for models.
Trailhead: Set Up Einstein Generative AI- Covers Prompt Builder admin access.
Salesforce Help: Agentforce Permission Sets- Aligns with admin-level needs.

NEW QUESTION # 48
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