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Salesforce AI-201 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Data Cloud & Grounding | 20% | - Data integration for AI agents
|
| AI Agents | 35% | - Agent behavior configuration
|
| Governance & Observability | 10% | - AI governance
|
| Testing, Deployment & Lifecycle | 15% | - Agent lifecycle management
|
| Prompt Engineering | 20% | - Prompt Builder usage
|
Salesforce Certified Agentforce Specialist Sample Questions:
1. Universal Containers' data science team is hosting a generative large language model (LLM) on Amazon Web Services (AWS). What should the team use to access externally-hosted models in the Salesforce Platform?
A) Model Builder
B) Copilot Builder
C) App Builder
2. An Agentforce configured Data Masking within the Einstein Trust Layer. How should the Agentforce Specialist begin validating that the correct fields are being masked?
A) Request the Einstein Generative AI Audit Data from the Security section of the Setup menu.
B) Use a Flow-based resource in Prompt Builder to debug the fields' merge values using Flow Debugger.
C) Enable the collection and storage of Einstein Generative AI Audit Data on the Einstein Feedback setup page.
3. An Al Specialist is tasked with configuring a generative model to create personalized sales emails using customer data stored in Salesforce. The AI Specialist has already fine-tuned a large language model (LLM) on the OpenAI platform. Security and data privacy are critical concerns for the client. How should the Agentforce Specialist integrate the custom LLM into Salesforce?
A) Add the fine-tuned LLM in Einstein Studio Model Builder.
B) Enable model endpoint on OpenAl and make callouts to the model to generate emails.
C) Create an application of the custom LLM and embed it in Sales Cloud via iFrame.
4. After an agent selects a topic, what is an important factor the reasoning engine uses to select the action?
A) The explicit order of actions in the topic
B) The priority given to each action
C) The name and instructions of the actions
5. A Salesforce Administrator is exploring the capabilities of Agent to enhance user interaction within their organization. They are particularly interested in how Agent processes user requests and the mechanism it employs to deliver responses. The administrator is evaluating whether Agent directly interfaces with a large language model (LLM) to fetch and display responses to user inquiries, facilitating a broad range of requests from users. How does Agent handle user requests In Salesforce?
A) Agent will trigger a flow that utilizes a prompt template to generate the message.
B) Agent will perform an HTTP callout to an LLM provider.
C) Agent analyzes the user's request and LLM technology is used to generate and display the appropriate response.
Solutions:
| Question # 1 Answer: A | Question # 2 Answer: C | Question # 3 Answer: A | Question # 4 Answer: B | Question # 5 Answer: C |

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