NEW AGENTFORCE-SPECIALIST EXAM QUESTION, AGENTFORCE-SPECIALIST CHEAP DUMPS

New Agentforce-Specialist Exam Question, Agentforce-Specialist Cheap Dumps

New Agentforce-Specialist Exam Question, Agentforce-Specialist Cheap Dumps

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Tags: New Agentforce-Specialist Exam Question, Agentforce-Specialist Cheap Dumps, New Agentforce-Specialist Real Test, Agentforce-Specialist VCE Dumps, Agentforce-Specialist Test Fee

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Salesforce Agentforce-Specialist Exam Syllabus Topics:

TopicDetails
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 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 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
  • 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.

Salesforce Certified Agentforce Specialist Sample Questions (Q56-Q61):

NEW QUESTION # 56
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. Data Masking
  • B. Prompt Defense
  • C. Dynamic Grounding

Answer: C

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 # 57
An Agentforce is creating a custom action in Einstein Copilot.
Which option is available for theAgentforce Specialistto choose for the custom copilot action?

  • A. Apex trigger
  • B. Flows
  • C. SOQL

Answer: B

Explanation:
When creating acustom actionin Einstein Copilot, one of the available options is to useFlows. Flows are a powerful automation tool in Salesforce, allowing theAgentforce Specialistto define custom logic and actions within the Copilot system. This makes it easy to extend Copilot's functionality without needing custom code.
WhileApex triggersandSOQLare important Salesforce tools,Flowsare the recommendedmethod for creating custom actions within Einstein Copilot because they are declarative and highly adaptable.
For further guidance, refer toSalesforce Flow documentationandEinstein Copilot customization resources.


NEW QUESTION # 58
An Agentforce has created a copilot custom action using flow as the reference action type. However, it is not delivering the expected results to the conversation preview, and therefore needs troubleshooting.
What should theAgentforce Specialistdo to identify the root cause of the problem?

  • A. Copilot Builder within the Dynamic Panel, confirm selected action and observe the values in Input and Output sections.
  • B. In Copilot Builder, verify the utterance entered by the user and review session event logs for debug information.
  • C. In Copilot Builder within the Dynamic Panel, turn on dynamic debugging to show the inputs and outputs.

Answer: C

Explanation:
When troubleshooting acopilot custom actionusing flow as the reference action type, enablingdynamic debuggingwithinCopilot Builder's Dynamic Panelis the most effective way to identify the root cause. By turning on dynamic debugging, theAgentforce Specialistcan see detailed logs showing both theinputs and outputsof the flow, which helps identify where the action might be failing or not delivering the expected results.
* Option B, confirming selected actions and observing the Input and Output sections, is useful for monitoring flow configuration but does not provide the deep diagnostic details available with dynamic debugging.
* Option C, verifying the user utterance and reviewing session event logs, could provide helpful context, but dynamic debugging is the primary tool for identifying issues with inputs and outputs in real time.
SalesforceAgentforce SpecialistReferences:To explore more about dynamic debugging in Copilot Builder, see:https://help.salesforce.com/s/articleView?id=sf.copilot_custom_action_debugging.htm


NEW QUESTION # 59
Universal Containers (UC) uses Salesforce Service Cloud to support its customers and agents handling cases.
UC is considering implementing Agent and extending Service Cloud to mobile users.
When would Agent implementation be most advantageous?

  • A. When the goal is to streamline customer support processes and improve response times
  • B. When the main objective is to enhance data security and compliance measures
  • C. When the focus is on optimizing marketing campaigns and strategies

Answer: A

Explanation:
Agent implementation would be most advantageous in Salesforce Service Cloud when the goal is to streamline customer support processes and improve response times. Agent can assist agents by providing real-time suggestions, automating repetitive tasks, and generating contextual responses, thus enhancing service efficiency.
* Option B (data security) is not the primary focus of Agent, which is more about improving operational efficiency.
* Option C (marketing campaigns) falls outside the scope of Service Cloud and Agent's primary benefits, which are aimed at improving customer service and case management.
For further reading, refer to Salesforce documentation on Agent for Service Cloud and how it improves support processes.


NEW QUESTION # 60
What is the role of the large language model (LLM) in understanding intent and executing an Agent Action?

  • A. Determine a user's topic access and sort actions by priority to be executed.
  • B. Identify the best matching topic and actions and correct order of execution.
  • C. Find similar requested topics and provide the actions that need to be executed.

Answer: B

Explanation:
Comprehensive and Detailed In-Depth Explanation:In Agentforce, the large language model (LLM), powered by the Atlas Reasoning Engine, interprets user requests and drives Agent Actions. Let's evaluate its role.
* Option A: Find similar requested topics and provide the actions that need to be executed.While the LLM can identify similar topics, its role extends beyond merely finding them-it matches intents to specific topics and determines execution. This option understates the LLM's responsibility for ordering actions, making it incomplete and incorrect.
* Option B: Identify the best matching topic and actions and correct order of execution.The LLM analyzes user input to understand intent, matches it to the best-fitting topic (configured in Agent Builder), and selects associated actions. It also determines the correct sequence of execution based on the agent's plan (e.g., retrieve data before updating a record). This end-to-end process-from intent recognition to action orchestration-is the LLM's core role in Agentforce, making this the correct answer.
* Option C: Determine a user's topic access and sort actions by priority to be executed.Topic access is governed by Salesforce permissions (e.g., user profiles), not the LLM. While the LLM prioritizes actions within its plan, its primary role is intent matching and executionordering, not access control, making this incorrect.
Why Option B is Correct:The LLM's role in identifying topics, selecting actions, and ordering execution is central to Agentforce's autonomous functionality, as detailed in Salesforce documentation.
References:
* Salesforce Agentforce Documentation: Atlas Reasoning Engine- Outlines LLM's intent and action handling.
* Trailhead: Understand Agentforce Technology- Explains topic matching and execution.
* Salesforce Help: Agentforce Actions- Confirms LLM's role in orchestrating responses.


NEW QUESTION # 61
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