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Salesforce AI-201 Exam Syllabus Topics:

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

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Salesforce Certified Agentforce Specialist Sample Questions (Q128-Q133):

NEW QUESTION # 128
Universal Containers wants to keep retrieval accurate as product documentation changes frequently. Which approach should the company implement?

A. Rebuild the search index.
B. Manually delete the stale data chunks.
C. Leave embedding unchanged even if content is updated.

Answer: A

Explanation:
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.

NEW QUESTION # 129
Universal Containers has seen a high adoption rate of a new feature that uses generative AI to populate a summary field of a custom object, Competitor Analysis. All sales users have the same profile but one user cannot see the generative AlI-enabled field icon next to the summary field.
What is the most likely cause of the issue?

A. The user does not have the field Generative AI User permission set assigned.
B. The prompt template associated with summary field is not activated for that user.
C. The user does not have the Prompt Template User permission set assigned.

Answer: A

Explanation:
In Salesforce, Generative AI capabilities are controlled by specific permission sets. To use features such as generating summaries with AI, users need to have the correct permission sets that allow access to these functionalities.
Generative AI User Permission Set: This is a key permission set required to enable the generative AI capabilities for a user. In this case, the missing Generative AI User permission set prevents the user from seeing the generative AI-enabled field icon. Without this permission, the generative AI feature in the Competitor Analysis custom object won't be accessible.

NEW QUESTION # 130
What is the correct process to leverage Prompt Builder in a Salesforce org?

A. Select the appropriate prompt template type to use, develop the prompt within the prompt workspace, select resources to dynamically insert CRM-derived grounding data, pick the model to use, and test and validate the generated responses.
B. Enable the target object for generative prompting, develop the prompt within the prompt workspace, select records to fine-tune and ground the response, enable the Trust Layer, and associate the prompt to an action.
C. Select the appropriate prompt template type to use, select one of Salesforce's standard prompts, determine the object to associate the prompt, select a record to validate against, and associate the prompt to an action.

Answer: A

Explanation:
When using Prompt Builder in a Salesforce org, the correct process involves several important steps:
Select the appropriate prompt template type based on the use case.
Develop the prompt within the prompt workspace, where the template is created and customized.
Select CRM-derived grounding data to be dynamically inserted into the prompt, ensuring that the AI-generated responses are based on accurate and relevant data.
Pick the model to use for generating responses, either using Salesforce's built-in models or custom ones.
Test and validate the generated responses to ensure accuracy and effectiveness.

NEW QUESTION # 131
An Agentforce is creating a custom action for Agentforce. Which setting should the a ensure the action performs as expected?

A. Action Instructions
B. Action Input
C. Action Name

Answer: A

Explanation:
When creating a custom action for Einstein Bots in Salesforce (including Agentforce), Action Instructions are critical for defining how the bot processes and executes the action. These instructions guide the bot on the logic to follow, such as API calls, data transformations, or conditional steps. Testing and iterating on the instructions ensures the bot understands how to handle dynamic inputs, external integrations, and decision-making.
Salesforce documentation emphasizes that Action Instructions directly impact the bot's ability to execute workflows accurately. For example, poorly defined instructions may lead to incorrect API payloads or failure to parse responses. The Einstein Bot Developer Guide highlights that refining instructions is essential for aligning the bot's behavior with business requirements.

NEW QUESTION # 132
Universal Containers' administrator has developed a new agent in a sandbox environment and now wants to deploy it to production. What should the administrator do to deploy an agent?

A. Create an outbound change set with all the necessary agent components, then upload to production.
B. Export agent components as JSON files and manually import them inte production using the Metadata API.
C. Manually recreate the agent configuration, topics, and actions in production because change sets cannot be used.

Answer: A

Explanation:
As per the AgentForce Deployment and Lifecycle Management Guide, AgentForce agents, including their topics, actions, and prompt templates, can be deployed from sandbox to production using Salesforce change sets.
Administrators should create an outbound change set in the sandbox environment that includes all relevant components (Agent definition, prompt templates, topic configurations, flows, and permissions) and then upload it to production for validation and deployment. This process ensures consistency, auditability, and proper dependency tracking between environments.

NEW QUESTION # 133
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