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Salesforce Agentforce-Specialist Exam Syllabus Topics:

Topic
Details

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 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 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 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 Certified Agentforce Specialist Sample Questions (Q154-Q159):

NEW QUESTION # 154
Which part of the Einstein Trust Layer architecture leverages an organization's own data within a large language model (LLM) prompt to confidently return relevant and accurate responses?

A. Prompt Defense
B. Dynamic Grounding
C. Data Masking

Answer: B

Explanation:
Dynamic Grounding in the Einstein Trust Layer architecture ensures that large language model (LLM) prompts are enriched with organization-specific data (e.g., Salesforce records, Knowledge articles) to generate accurate and relevant responses. By dynamically injecting contextual data into prompts, it reduces hallucinations and aligns outputs with trusted business data.
* Prompt Defense (A) focuses on blocking malicious inputs or prompt injections but does not enhance responses with organizational data.
* Data Masking (B) redacts sensitive information but does not contribute to grounding responses in business context.

NEW QUESTION # 155
Universal Containers has a strict change management process that requires all possible configuration to be completed in a sandbox which will be deployed to production. TheAgentforce Specialistis tasked with setting up Work Summaries for Enhanced Messaging. Einstein Generative AI is already enabled in production, and the Einstein Work Summaries permission set is already available in production.
Which other configuration steps should theAgentforce Specialisttake in the sandbox that can be deployed to the production org?

A. From the Epstein setup menu, select Turn on Einstein: create custom fields to store Issue, Resolution, and Summary: create a Quick Action that updates these fields: and add the wrap up componert to the Messaging session record page layout.
B. create custom fields to store Issue, Resolution, and Summary; create a Quick Action that updates these fields: add the Wrap Up component to the Messaging Session record paae layout: and create Permission Set Assignments for the intended Agents.
C. Create custom fields to store issue, Resolution, and Summary; create a Quick Action that updates these fields: and ado the Wrap up component to the Messaging session record page lavcut.

Answer: C

Explanation:
* Context of the Question
* Universal Containers (UC) has a strict change management process that requires all possible configuration be completed in a sandbox and deployed to Production.
* Einstein Generative AI is already enabled in Production, and the "Einstein Work Summaries" permission set is already available in Production.
* TheAgentforce Specialistneeds to configureWork Summaries for Enhanced Messagingin the sandbox.
* What Can Actually Be Deployed from Sandbox to Production?
* Custom Fields: Metadata that is easily created in sandbox and then deployed.
* Quick Actions: Also metadata-based and can be deployed from sandbox to production.
* Layout Components: Page layout changes (such as adding the Wrap Up component) can be added to a change set or deployment package.
* Why Option C is Correct
* No Need to Turn on Einstein in Sandbox for Deployment: Einstein Generative AI is already enabled in Production; turning it on in the sandbox is typically a manual step if you want to test, but that step itself is not "deployable" in the sense of metadata.
* Permission Set Assignments(as in Option A) are not deployable metadata. You can deploy the Permission Set itself but not the specific user assignments. Since the question specifically asks
"Which other configuration steps should be takenin the sandboxthatcanbe deployed to the production org?", user assignment is not one of them.
* Why Not Option A or B?
* Option A: Mentions creating permission set assignments for agents. This cannot be directly deployed from sandbox to Production, as permission set assignments are user-specific and considered "data," not metadata.
* Option B: Mentions "Turn on Einstein." But Einstein Generative AI is already enabled in Production. Additionally, "Turning on Einstein" is typically an org-level setting, not a deployable metadata item.
* ConclusionThe main deployable items you can reliably create and test in a sandbox, and then migrate to Production, are:
* Custom Fields(Issue, Resolution, Summary).
* A Quick Actionthat updates those fields.
* Page Layout Changeto include the Wrap Up component.
Therefore,Option Cis correct and focuses on actions that are truly deployable as metadata from a sandbox to Production.
SalesforceAgentforce SpecialistReferences & Documents
* Salesforce Trailhead:Work Summaries with Einstein GPTProvides an overview of how to configure Work Summaries, including the need for custom fields, quick actions, and UI components.
* Salesforce Documentation:Deploying Metadata Between OrgsExplains what can and cannot be deployed via change sets (e.g., custom fields, page layouts, quick actions vs. user permission set assignments).
* SalesforceAgentforce SpecialistStudy GuideOutlines which Einstein Generative AI and Work Summaries configurations are deployable as metadata.

NEW QUESTION # 156
Based on the user utterance, 'Show me all the customers in New York', which standard Agent action will the planner service use?

A. Fetch Records
B. Select Records
C. Query Records

Answer: C

Explanation:
Why is Query Records the Correct Answer?
In Agentforce, the Planner Service is responsible for interpreting user requests and selecting the appropriate Copilot Action to fulfill them. When a user issues a command like:"Show me all the customers in New York", the system must retrieve a list of customers filtered by location.
The Query Records action is designed precisely for this purpose.
Key Features of Query Records in Agentforce:
* Retrieves Data Based on Specific Field Values
* This action fetches Salesforce records that match a set of criteria, such as customers located in New York.
* Uses standard or custom object fields (e.g., BillingState = 'New York').
* Works with Large Language Models (LLMs) and Copilot Actions
* When a user asks for filtered data, Query Records is the default action assigned by the Planner Service.
* Optimized for Structured Data Retrieval
* Ensures AI retrieves relevant CRM records quickly and accurately.
Why Not the Other Options?
# B. Fetch Records
* This is not a standard term in Einstein Copilot or Agentforce.
* No defined Agentforce action exists under this name.
# C. Select Records
* Select Records is used to pick records from an already presented list, not to retrieve them initially.
* If the user had already retrieved records and wanted to refine their selection, Select Records might be appropriate.
* However, since the user's request is to retrieve records, Query Records is the correct action.
Agentforce Specialist References
This information is confirmed from the Salesforce AI Specialist Material and Questions Document, where the Query Records action is explicitly defined as the appropriate standard action for retrieving filtered CRM records.

NEW QUESTION # 157
Universal Containers' current AI data masking rules do not align with organizational privacy and security policies and requirements.
What should An Agentforce recommend to resolve the issue?

A. Enable data masking for sandbox refreshes.
B. Configure data masking in the Einstein Trust Layer setup.
C. Add new data masking rules in LLM setup.

Answer: B

Explanation:
WhenUniversal Containers' AI data masking rulesdo not meet organizational privacy and security standards, theAgentforce Specialistshould configure thedata maskingrules within theEinstein Trust Layer.
TheEinstein Trust Layerprovides a secure and compliant environment where sensitive data can be masked or anonymized to adhere to privacy policies and regulations.
* Option A, enabling data masking for sandbox refreshes, is related to sandbox environments, which are separate from how AI interacts with production data.
* Option C, adding masking rules in the LLM setup, is not appropriate because data masking is managed through theEinstein Trust Layer, not the LLM configuration.
The Einstein Trust Layer allows for more granular control over what data is exposed to the AI model and ensures compliance with privacy regulations.
SalesforceAgentforce SpecialistReferences:For more information, refer to:https://help.salesforce.com/s
/articleView?id=sf.einstein_trust_layer_data_masking.htm

NEW QUESTION # 158
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. Apex Trigger
B. Flows
C. SOQL

Answer: B

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 # 159
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