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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 Feb. 28, 2026 (see below)
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.
Universal Containers has set up a Service Agent to allow customers to look up their order status. The topic setup includes:
Name: Order Inquiry
Classification Description: Handles user requests to look up order status, including tracking details and delivery estimates for orders placed within the last 90 days.
Scope: Your job is only to assist authenticated users in looking up the status of their orders placed within the last 90 days. If the order is pending delivery, provide the tracking number and estimated delivery date. Do not handle inquiries for orders older than 90 days.
Which information will be used by the Agentforce reasoning engine to choose this topic?
The AgentForce Reasoning Engine Guide explains that the engine relies primarily on the Classification Description and Scope fields to determine which topic best matches the user's intent. The documentation notes: ''Classification Description defines the purpose and context of a topic, while Scope provides the operational boundaries for when and how that topic should be triggered. Together, they guide the LLM in selecting the appropriate topic at runtime.''
Option A includes ''Topic Name,'' which is used mainly for administrative organization, not reasoning. Option B omits the Classification Description, which contains the intent signal critical for matching. Therefore, Option C is correct since both the Classification Description and Scope are essential for topic selection by the reasoning engine.
Reference (AgentForce Documents / Study Guide):
AgentForce Reasoning Engine Overview: ''How Topics Are Selected''
AgentForce Builder Guide: ''Role of Classification Description and Scope in Topic Selection''
AgentForce Study Guide: ''Optimizing Topic Matching Logic''
Universal Containers plans to enhance the customer support team's productivity using AI.
Which specific use case necessitates the use of Prompt Builder?
The use case that necessitates the use of Prompt Builder is creating a draft of a support bulletin post for new product patches. Prompt Builder allows the Agentforce Specialist to create and refine prompts that generate specific, relevant outputs, such as drafting support communication based on product information and patch details.
Option B (agent performance score) would likely involve predictive modeling, not prompt generation.
Option C (estimating support ticket volume) would require data analysis and predictive tools, not prompt building.
For more details, refer to Salesforce's Prompt Builder documentation for generative AI content creation.
What should An Agentforce consider when using related list merge fields in a prompt template associated with an Account object in Prompt Builder?
When using related list merge fields in a prompt template associated with the Account object in Prompt Builder, the Activities related list is not supported due to it being a polymorphic field. Polymorphic fields can reference multiple different types of objects, which makes them incompatible with some merge field operations in prompt generation.
Option B is incorrect because person accounts do not limit the availability of merge fields for the Account object.
Option C is irrelevant since even if no related lists are available at runtime, the prompt can still generate based on other available data fields.
For more information, refer to Salesforce documentation on supported fields and limitations in Prompt Builder.
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