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| Section | Weight | Objectives |
|---|---|---|
| Agent Force Concepts | 30% | - Data Cloud & Grounding Techniques
|
| Prompt Engineering | 30% | - Agentforce AI Setup & Configuration
|
| Einstein Trust Layer & Security | - Trust Layer & Security Features
| |
| Reasoning Engine & AI Actions | - Workflow mastery
|
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NEW QUESTION # 263
Universal Containers, dealing with a high volume of chat inquiries, implements Einstein Work Summaries to boost productivity. After an agent-customer conversation, which additional information does Einstein generate and fill, apart from the "summary"'
Answer: A
Explanation:
Einstein Work Summaries automatically generate concise summaries of customer interactions (e.g., chat transcripts). Beyond the "summary" field, it extracts and populates Issue (key problem discussed) and Resolution (action taken to resolve the issue). These fields help agents and upervisors quickly grasp the conversation's context without reviewing the full transcript.
NEW QUESTION # 264
Universal Containers recently launched a pilot program to integrate conversational AI into its CRM business operations with Agentforce Agents. How should the Agentforce Specialist monitor Agents' usability and the assignment of actions?
Answer: B
Explanation:
Monitoring the usability and action assignments of Agentforce Agents requires insights into how agents perform, how users interact with them, and how actions are executed within conversations. Salesforce provides Agent Analytics (Option C) as a built-in capability specifically designed for this purpose. Agent Analytics offers dashboards and reports that track metrics such as agent response times, user satisfaction, action invocation frequency, and success rates. This tool allows the Agentforce Specialist to assess usability (e.g., are agents meeting user needs?) and monitor action assignments (e.g., which actions are triggered and how often), providing actionable data to optimize the pilot program.
NEW QUESTION # 265
Universal Containers (UC) has configured an Agentforce Data Library using Knowledge articles.
When testing in Agent Builder and the Experience Cloud site, the agent is not responding with grounded Knowledge article information. However, when tested in Prompt Builder, the response returns correctly. What should UC do to troubleshoot the issue?
Answer: C
Explanation:
UC has set up an Agentforce Data Library with Knowledge articles, and while Prompt Builder retrieves the data correctly, the agent fails to do so in Agent Builder and Experience Cloud.
NEW QUESTION # 266
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?
Answer: B
Explanation:
When Universal Containers' AI data masking rules do not meet organizational privacy and security standards, the Agentforce Specialist should configure the data masking rules within the Einstein Trust Layer. The Einstein Trust Layer provides a secure and compliant environment where sensitive data can be masked or anonymized to adhere to privacy policies and regulations.
NEW QUESTION # 267
An agent must comply with regional data regulations (e.g., GDPR). Which Salesforce capability MOST directly supports this?
Answer: A
Explanation:
The Einstein Trust Layer enforces data residency, masking, and compliance policies.
NEW QUESTION # 268
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