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Salesforce AI-201 Exam Syllabus Topics:

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

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Salesforce Certified Agentforce Specialist Sample Questions (Q100-Q105):

NEW QUESTION # 100
What is the primary advantage of creating an individual retriever instead of the default retriever?

A. Individual retrievers can aggregate multiple data spaces and data model objects (DMOs) into a unified retriever output.
B. Individual retrievers automatically generate new search indexes and dynamically update vectors.
C. Individual retrievers allow the configuration of filters, specified fields, and how many results are returned.

Answer: C

Explanation:
The AgentForce Data Cloud and Retrieval Configuration Guide explains that individual retrievers offer customization flexibility beyond the default retriever. The guide states: "Individual retrievers allow specialists to define filters, select specific fields for retrieval, and configure result limits, providing fine-grained control over data recall and relevance."

NEW QUESTION # 101
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. Manually recreate the agent configuration, topics, and actions in production because change sets cannot be used.
B. Export agent components as JSON files and manually import them inte production using the Metadata API.
C. Create an outbound change set with all the necessary agent components, then upload to production.

Answer: C

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 # 102
Before deploying an Agentforce agent to production, which step is MOST critical?

A. Test with real-world scenarios and monitor outputs
B. Disable debug logs
C. Grant admin permissions
D. Increase API limits

Answer: A

Explanation:
Testing with real scenarios and monitoring outputs ensures accuracy, safety, and business alignment.

NEW QUESTION # 103
Universal Containers (UC) wants to ensure the effectiveness, reliability, and trust of its agents prior to deploying them in production. UC would like to efficiently test a large and repeatable number of utterances. What should the Agentforce Specialist recommend?

A. Deploy the agent in a QA sandbox environment and review the Utterance Analysis reports to review effectiveness.
B. Leverage the Agent Large Language Model (LLM) UI and test UC's agents with different utterances prior to activating the agent.
C. Create a CSV file with UC's test cases in Agentforce Testing Center using the testing template.

Answer: C

Explanation:
The goal of Universal Containers (UC) is to test its Agentforce agents for effectiveness, reliability, and trust before production deployment, with a focus on efficiently handling a large and repeatable number of utterances. Let's evaluate each option against this requirement and Salesforce's official Agentforce tools and best practices.

NEW QUESTION # 104
Universal Containers (UC) wants to improve the productivity of its sales team with generative AI technology. However, UC is concerned that public AI virtual assistants lack adequate company data to general useful responses. Which solution should UC consider?

A. fine-tune the Einstein AI model with CBM data.
B. Enable Agentforce and deploy to sales users.
C. Build Al model with Einstein discovery and deploy to sales users.

Answer: A

Explanation:
Universal Containers (UC) wants to harness generative AI to boost sales productivity. They are wary of public AI virtual assistants (like generic chatbots) that lack sufficient UC-specific data to generate useful business responses.

NEW QUESTION # 105
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