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NEW QUESTION # 61
Universal Containers (UC) is looking to enhance its operational efficiency. UC has recently adopted Salesforce and is considering implementing Agent to improve its processes.
What is a key reason for implementing Agent?
Answer: A
Explanation:
The key reason for implementingAgentis its ability tostreamline workflowsandautomate repetitive tasks.
By leveraging AI, Agent can assist users in handling mundane, repetitive processes, such as automatically generating insights, completing actions, and guiding users through complex processes, all of which significantly improve operational efficiency.
* Option A(Improving data entry and cleansing) is not the primary purpose of Agent, as its focus is on guiding and assisting users through workflows.
* Option B(Allowing AI to perform tasks without user interaction) does not accurately describe the role of Agent, which operates interactively to assist users in real time.
Salesforce Agentforce Specialist References:
More details can be found in the Salesforce documentation:https://help.salesforce.com/s/articleView?id=sf.
einstein_copilot_overview.htm
NEW QUESTION # 62
What is the correct process to leverage Prompt Builder in a Salesforce org?
Answer: B
Explanation:
When usingPrompt Builderin a Salesforce org, the correct process involves several important steps:
* Select the appropriate prompt template typebased on the use case.
* Develop the promptwithin theprompt workspace, where the template is created and customized.
* Select CRM-derived grounding datato be dynamically inserted into the prompt, ensuring that the AI- generated responses are based on accurate and relevant data.
* Pick the model to usefor generating responses, either using Salesforce's built-in models or custom ones.
* Test and validatethe generated responses to ensure accuracy and effectiveness.
* Option Bis correct as it follows the proper steps for usingPrompt Builder.
* Option AandOption Cdo not capture the full process correctly.
:
Salesforce Prompt Builder Documentation:https://help.salesforce.com/s/articleView?id=sf.
prompt_builder_overview.htm
NEW QUESTION # 63
An Agentforce at Universal Containers (UC) is building with no-code tools only. They have many small accounts that are only touched periodically by a specialized sales team, and UC wants to maximize the sales operations team's time. UC wants to help prep the sales team for the calls by summarizing past purchases, interests in products shown by the Contact captured via Data Cloud, and a recap of past email and phone conversations for which there are transcripts.
Which approach should the Agentforce Specialist recommend to achieve this use case?
Answer: A
Explanation:
For no-code implementations, Prompt Builder allows Agentforce Specialists to create prompt templates that dynamically ground responses in Salesforce CRM data (e.g., past purchases) and Data Cloud insights (e.
g., product interests) without custom coding. The standard foundation model (e.g., Einstein GPT) can synthesize this data into summaries, leveraging structured and unstructured sources (e.g., email/phone transcripts). Fine-tuning (B) or custom models (C) require code and are unnecessary here, as the use case does not involve unique data patterns requiring model retraining.
Reference:
Salesforce Help Article: Prompt Builder for No-Code AI ("Grounding in CRM and Data Cloud" section).
Einstein GPT Implementation Guide: "Generating Summaries with Pre-Built Models."
NEW QUESTION # 64
An Agentforce is creating a custom action in Agent.
Which option is available for the Agentforce Specialist to choose for the custom copilot action?
Answer: B
Explanation:
When creating a custom action in Agent, one of the available options is to use Flows. Flows are a powerful automation tool in Salesforce, allowing the Agentforce Specialist to define custom logic and actions within the Copilot system. This makes it easy to extend Copilot's functionality without needing custom code.
While Apex triggers and SOQL are important Salesforce tools, Flows are the recommended method for creating custom actions within Agent because they are declarative and highly adaptable.
For further guidance, refer to Salesforce Flow documentation and Agent customization resources.
NEW QUESTION # 65
What is the primary function of the reasoning engine in Agentforce?
Answer: C
Explanation:
Why is "Identifying agent topics and actions to respond to user utterances" the correct answer?
InAgentforce, thereasoning engineplays a critical role ininterpreting user queriesanddetermining the appropriate agent response.
Key Functions of the Reasoning Engine in Agentforce:
* Analyzing User Intent
* The reasoning engineinterpretsthe meaning behindnatural language user inputs.
* It maps user utterances topredefined topicsto determine the correct AI-generated response.
* Selecting the Appropriate Agent Action
* The engineevaluates available actionsand selects the best responsebased on the detected topic.
* For example, if a user asks,"What is my current account balance?", the reasoning engine:
* Identifies the topic: "Account Information"
* Chooses the correct action: "Retrieve account balance"
* Executes the actionandreturns the response
* Ensuring AI Accuracy and Context Awareness
* The reasoning enginegrounds AI-generated responsesin relevantSalesforce data, ensuring accurate outputs.
Why Not the Other Options?
#B. Offering real-time natural language response during conversations.
* Incorrectbecause real-timenatural language processing(NLP) is handled by thelarge language model (LLM), not thereasoning engine.
* Thereasoning engine focuses on action selection, notlinguistic processing.
#C. Generating record queries based on conversation history.
* Incorrectbecausequery generationis handled byCopilot Actions (e.g., Query Records), not the reasoning engine.
* The reasoning enginedecideswhich query should be run, but does not generate queries itself.
Agentforce Specialist References
* Salesforce AI Specialist Materialexplains that thereasoning engine identifies topics and selects agent actions.
* Salesforce Instructions for the Certificationconfirm thatthe reasoning engine determines AI workflow execution.
NEW QUESTION # 66
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