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Salesforce Certified Agentforce Specialist (AI-201) Exam Questions
- Topic 1: AI Agents: This domain covers configuring agent behavior, understanding the reasoning engine, selecting topics and actions for agent types, managing Agent User security, choosing appropriate agent types, and connecting agents to various channels.
- Topic 2: Prompt Engineering: This section focuses on using Prompt Builder, managing user roles, creating prompt templates with field generation and flex types, selecting grounding techniques, and applying best practices for effective prompts.
- Topic 3: Data Cloud for Agentforce: This domain covers Agentforce Data Library types, improving responses with unstructured data through chunking and indexing, understanding retrievers, and selecting keyword, vector, or hybrid search types.
- Topic 4: Development Lifecycle: This area addresses testing agents in Testing Center, deploying from sandbox to production, and managing agent adoption and monitoring.
- Topic 5: Multi-Agent Interoperability: This domain explains Model Context Protocol (MCP), agent-to-agent communication, and when to use Agent API for system interactions.
Free Salesforce Salesforce Certified Agentforce Specialist (AI-201) Exam Actual Questions
Note: Premium Questions for Salesforce Certified Agentforce Specialist (AI-201) were last updated On May. 04, 2026 (see below)
Universal Containers is considering leveraging the Einstein Trust Layer in conjunction with Einstein Generative AI Audit Data.
Which audit data is available using the Einstein Trust Layer?
Universal Containers is considering the use of the Einstein Trust Layer along with Einstein Generative AI Audit Data. The Einstein Trust Layer provides a secure and compliant way to use AI by offering features like data masking and toxicity assessment.
The audit data available through the Einstein Trust Layer includes information about masked data---which ensures sensitive information is not exposed---and the toxicity score, which evaluates the generated content for inappropriate or harmful language.
Salesforce Agentforce Specialist Documentation - Einstein Trust Layer: Details the auditing capabilities, including logging of masked data and evaluation of generated responses for toxicity to maintain compliance and trust.
The Agentforce Specialist for Cloud Kicks wants to create an agent that will allow the sales staff to schedule their daily tasks and assist in providing detailed explanations behind product prices and deals.
Following Salesforce best practices, which type of agent should they create?
An Agentforce Specialist needs to create a prompt template to fill a custom field named Latest Opportunities Summary on the Account object with information from the three most recently opened opportunities. How should the Agentforce Specialist gather the necessary data for the prompt template?
In Salesforce Agentforce, a prompt template designed to populate a custom field (like 'Latest Opportunities Summary' on the Account object) requires dynamic data to be fed into the template for AI to generate meaningful output. Here, the task is to gather data from the three most recently opened opportunities related to an account. The most robust and flexible way to achieve this is by using a Flow (Option B). Salesforce Flows allow the Agentforce Specialist to define logic to query the Opportunity object, filter for the three most recent opportunities (e.g., using a Get Records element with a sort by CreatedDate descending and a limit of 3), and pass this data as variables into the prompt template. This approach ensures precise control over the data retrieval process and can handle complex filtering or sorting requirements.
Option A: Selecting the 'latest Opportunities related list as a merge field' is not a valid option in Agentforce prompt templates. Merge fields can pull basic field data (e.g., {!Account.Name}), but they don't natively support querying or aggregating related list data like the three most recent opportunities.
Option C: There is no 'Account Opportunity object' in Salesforce; this seems to be a misnomer (perhaps implying the Opportunity object or a junction object). Even if interpreted as selecting the Opportunity object as a resource, prompt templates don't directly query related objects without additional logic (e.g., a Flow), making this incorrect.
Option B: Flows integrate seamlessly with prompt templates via dynamic inputs, allowing the Specialist to retrieve and structure the exact data needed (e.g., Opportunity Name, Amount, Close Date) for the AI to summarize.
Thus, Option B is the correct method to gather the necessary data efficiently and accurately.
Salesforce Agentforce Documentation: 'Integrate Flows with Prompt Templates' (Salesforce Help: https://help.salesforce.com/s/articleView?id=sf.agentforce_flow_prompt_integration.htm&type=5)
Trailhead: 'Build Flows for Agentforce' (https://trailhead.salesforce.com/content/learn/modules/flows-for-agentforce)
Universal Containers wants to keep retrieval accurate as product documentation changes frequently.
Which approach should the company implement?
Comprehensive and Detailed Explanation From Exact Extract of AgentForce Documents:
According to the official AgentForce implementation guidelines and RAG (Retrieval-Augmented Generation) architecture within Salesforce, maintaining retrieval accuracy depends on ensuring that embeddings and indexed content remain synchronized with the most recent data. When product documentation or knowledge base content changes, the underlying text used for vector embeddings must also be updated to reflect the new information.
The AgentForce documentation clearly specifies that when content is modified, the recommended practice is to rebuild the search index. This process regenerates the document chunks, re-embeds them using the latest model, and updates the index used by the retrieval system. This ensures that queries return the most current and relevant responses aligned with the updated content.
Leaving embeddings unchanged (Option A) would cause retrievals to surface outdated or irrelevant information, as the underlying semantic representations would no longer match the source material. Similarly, manually deleting stale data chunks (Option C) does not ensure a full refresh of vector data and can lead to incomplete or inconsistent results.
Therefore, as per AgentForce best practices, the correct approach is Option B -- Rebuild the search index, ensuring that all embeddings, chunks, and indexed data are aligned with the latest version of the content.
Universal Containers (UC) plans to automatically populate the Description field on the Account object.
Which type of prompt template should UC use?
Context of the Question
Universal Containers (UC) wants to automatically populate the Description field on the Account object. The AI-driven solution must generate textual data and write it directly into a field.
Field Generation Prompt Template
Primary Use Case: A Field Generation prompt template is specifically designed to create or fill in fields on a record with AI-generated text.
Auto-population: By configuring a Field Generation prompt template, admins can define the instructions, data inputs, and desired output for the AI. The resulting text then populates the specified field, such as the Account Description.
Why Not Flex or Sales Email Prompt Templates?
Flex Prompt Template: Used to combine or manipulate data across objects, merges, or references from multiple sources in more advanced, flexible prompts. Typically not the go-to for straightforward text generation on a single field.
Sales Email Prompt Template: Focused on drafting or summarizing emails for sales reps (like crafting outreach or follow-up messages). This template is not specifically built to populate a field on a record.
Conclusion
For automatically populating the Description field with AI-generated content, the Field Generation prompt template (Option A) is the correct choice.
Salesforce Agentforce Specialist Reference & Documents
Salesforce Documentation: Prompt Template Types
Explains various template types (Field Generation, Flex, Email, etc.) and their typical use cases.
Salesforce Agentforce Specialist Study Guide
Highlights Field Generation prompt templates for populating or updating record fields with AI-generated text.
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