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Salesforce AI-201 Exam Syllabus Topics:

Section	Weight	Objectives
Topic 1: Prompt Engineering	20%	- Prompt Builder usage 1. Prompt templates and configuration 2. Field generation and flex templates - Grounding techniques 1. Data grounding for reducing hallucinations 2. Best practices for prompt design
Topic 2: AI Agents	35%	- Agent setup and orchestration 1. Standard and custom agent actions 2. Standard and custom topics - Agent behavior configuration 1. Filters and variables for deterministic behavior 2. Agent reasoning engine concepts
Topic 3: Data Cloud & Grounding	20%	- Data integration for AI agents 1. Connecting external data sources 2. Using Data Cloud for retrieval augmentation
Topic 4: Testing, Deployment & Lifecycle	15%	- Agent lifecycle management 1. Sandbox to production deployment 2. Testing and validation strategies
Topic 5: Governance & Observability	10%	- AI governance 1. Monitoring agent behavior 2. Trust layer and compliance concepts

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Salesforce Certified Agentforce Specialist Sample Questions (Q58-Q63):

NEW QUESTION # 58
Universal Containers (UC) uses a file upload-based data library and custom prompt to support AI- driven training content. However, users report that the AI frequently returns outdated documents.
Which corrective action should UC implement to improve content relevancy?

A. Configure a custom retriever that includes a filter condition limiting retrieval to documents updated within a defined recent period, ensuring that only current content is used for AI responses.
B. Switch the data library source from file uploads to a Knowledge-based data library, because Salesforce Knowledge bases automatically manage document recency, ensuring current documents are returned.
C. Continue using the default retriever without filters, because periodic re-uploads will eventually phase out outdated documents without further configuration or the need for custom retrievers.

Answer: A

Explanation:
UC's issue is that their file upload-based Data Library (where PDFs or documents are uploaded and indexed into Data Cloud's vector database) is returning outdated training content in AI responses. To improve relevancy by ensuring only current documents are retrieved, the most effective solution is to configure a custom retriever with a filter (Option B). In Agentforce, a custom retriever allows UC to define specific conditions-such as a filter on a "Last Modified Date" or similar timestamp field-to limit retrieval to documents updated within a recent period (e.g., last
6 months). This ensures the AI grounds its responses in the most current content, directly addressing the problem of outdated documents without requiring a complete overhaul of the data source.

NEW QUESTION # 59
A support team handles a high volume of chat interactions and needs a solution to provide quick, relevant responses to customer inquiries. Responses must be grounded in the organization's knowledge base to maintain consistency and accuracy. Which feature in Einstein for Service should the support team use?

A. Einstein Reply Recommendations
B. Einstein Knowledge Recommendations
C. Einstein Service Replies

Answer: C

Explanation:
Einstein Service Replies: This feature is designed to generate contextual, AI-powered response suggestions for agents during chat and email interactions. Crucially, these replies can be grounded in your organization's knowledge base, ensuring consistency and accuracy. This aligns perfectly with the requirement for quick, relevant, and consistent responses.

NEW QUESTION # 60
Universal Containers wants to automatically populate the Description field on the Account object.

A. Sales Email
B. Flex
C. Field Generation

Answer: C

NEW QUESTION # 61
Universal Containers has a strict change management process that requires all possible configuration to be completed in a sandbox which will be deployed to production. The Agentforce Specialist is tasked with setting up Work Summaries for Enhanced Messaging. Einstein Generative AI is already enabled in production, and the Einstein Work Summaries permission set is already available in production. Which other configuration steps should the Agentforce Specialist take in the sandbox that can be deployed to the production org?

A. Create custom fields to store issue, Resolution, and Summary; create a Quick Action that updates these fields: and ado the Wrap up component to the Messaging session record page lavcut.
B. From the Epstein setup menu, select Turn on Einstein: create custom fields to store Issue, Resolution, and Summary: create a Quick Action that updates these fields: and add the wrap up componert to the Messaging session record page layout.
C. Create custom fields to store issue, Resolution, and Summary; create a Quick Action that updates these fields: add the Wrap Up component to the Messaging Session record paae layout: and create Permission Set Assignments for the intended Agents.

Answer: A

Explanation:
Universal Containers (UC) has a strict change management process that requires all possible configuration be completed in a sandbox and deployed to Production.
Einstein Generative AI is already enabled in Production, and the "Einstein Work Summaries" permission set is already available in Production.
The Agentforce Specialist needs to configure Work Summaries for Enhanced Messaging in the sandbox.
What Can Actually Be Deployed from Sandbox to Production?
Custom Fields: Metadata that is easily created in sandbox and then deployed.
Quick Actions: Also metadata-based and can be deployed from sandbox to production.
Layout Components: Page layout changes (such as adding the Wrap Up component) can be added to a change set or deployment package.

NEW QUESTION # 62
Universal Containers wants to allow its service agents to query the current fulfillment status of an order with natural language. There is an existing auto launched flow to query the information from Oracle ERP, which is the system of record for the order fulfillment process. How should An Agentforce apply the power of conversational AI to this use case?

A. Create a custom copilot action which calls a flow.
B. Create a Flex prompt template in Prompt Builder.
C. Configure the Integration Flow Standard Action in Agent.

Answer: A

Explanation:
To enable Universal Containers service agents to query the current fulfillment status of an order using natural language and leverage an existing auto-launched flow that queries Oracle ERP, the best solution is to create a custom copilot action that calls the flow. This action will allow Agent to interact with the flow and retrieve the required order fulfillment information seamlessly. Custom copilot actions can be tailored to call various backend systems or flows in response to user requests.

NEW QUESTION # 63
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