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Salesforce AI-201 Exam Syllabus Topics:

Salesforce Certified Agentforce Specialist Sample Questions:

1. An account manager is preparing for an upcoming customer call and wishes to get a snapshot of key data points from accounts, contacts, leads, and opportunities in Salesforce. Which feature provides this?

A) Work Summaries
B) Sales Summaries
C) Sales Insight Summary

2. An agent must decide whether to resolve a Case automatically or escalate it to a human. Which design principle BEST supports this behavior?

A) Hard-coded escalation rules
B) Static response templates
C) Anonymous execution
D) Human-in-the-loop design

3. Universal Containers (UC) is using standard Service AI Grounding. UC created a custom rich text field to be used with Service AI Grounding. What should UC consider when using standard Service AI Grounding?

A) Service AI Grounding only works with Case and Knowledge objects.
B) Service AI Grounding visibility works m system mode.
C) Service AI Grounding only supports String and Text Area type fields.

4. Universal Containers has multiple Salesforce orgs, each with a unique customer service agent where a verification agent must pass customer identity data to downstream agents handling account modifications. The customer ID must remain secure and persistent across agent handoffs without exposure to large language model (LLM) modification. What is the most appropriate configuration?

A) Store customer identity information in conversation variables created by the first agent and have other agents read those same conversation variables.
B) Use the Agent API to start the downstream agent's session and pass the verified customer ID as a read-only context variable, ensuring security and preventing LLM alteration.
C) Implement a custom object to temporarily store verification status and have each agent query it via SOQL actions during execution.

5. Universal Containers wants to use an Al agent to answer questions about warranties, Warranty information has already been uploaded as unstructured data in Data Cloud. When answering user questions, the results must be filterable by product line and ranked by recent updates. Which approach should the Agentforce Specialist implement?

A) Apply semantic embeddings with default metadata filters to achieve the desired result
B) Use the default retriever which automatically accounts for regency ranking.
C) Build a custom retriever in Einstein Studio with product line filters and regency ranking.

Solutions: