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Salesforce AI-201 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Prompt Engineering | 20% | - Grounding techniques and best practices - Prompt template creation: field generation, flex types - Prompt Builder usage and use cases - Prompt management and user roles |
| Data Cloud for Agentforce | 20% | - Agentforce Data Library types - Retrievers and search types: keyword, vector, hybrid - Unstructured data processing: chunking, indexing - Improving response accuracy with data grounding |
| AI Agents | 35% | - Agent types: Service, Sales, Employee - Channel integration: digital experience, email, Slack - Agent User security and permissions - Topics and actions configuration - Deterministic controls: filters and variables - Agent architecture and reasoning engine |
| Development Lifecycle | 15% | - Version control and maintenance - Deployment: sandbox to production - Testing agents in Testing Center - Monitoring, adoption and optimization |
| Multi-Agent Interoperability | 5% | - Model Context Protocol (MCP) - Agent API usage scenarios - Agent-to-agent communication |
Salesforce Certified Agentforce Specialist Sample Questions:
1. What is an appropriate use case for leveraging Agentforce Sales Agent in a sales context?
A) Enable a sates team to use natural language to invoke defined sales tasks grounded in relevant data and be able to ensure company policies are applied. conversationally and in the now or work.
B) Instantly review and read incoming messages or emails that are then logged to the correct opportunity, contact, and account records to provide a full view of customer interactions and communications.
C) Enable a sales team by providing them with an interactive step-by-step guide based on business rules to ensure accurate data entry into Salesforce and help close deals fatter.
2. Universal Containers is planning a marketing email about products that most closely match a customer's expressed interests. What should An Agentforce recommend to generate this email?
A) Standard email marketing template using Apex or flows for matching interest in products
B) Custom sales email template which is grounded with interest and product information
C) Standard email draft with Einstein and choose standard email template
3. What is the role of the large language model (LLM) in executing an Agent Action?
A) Identify the best matching actions and correct order of execution
B) Find similar requests and provide actions that need to be executed
C) Determine a user's access and sort actions by priority to be executed
4. An Agentforce needs to create a Sales Email with a custom prompt template. They need to ground on the following data.
Opportunity Products Events near the customer Tone and voice examples
How should the Agentforce Specialist obtain related items?
A) Utilize a standard email template and manually insert the required data fields.
B) Call prompt initiated flow to fetch and ground the required data.
C) Create a flex template that takes the records in question as inputs.
5. What considerations should an Agentforce Specialist be aware of when using Record Snapshots grounding in a prompt template?
A) Empty data, such as fields without values or sections without limits, is filtered out.
B) Email addresses associated with the object are excluded.
C) Activities such as tasks and events are excluded.
Solutions:
| Question # 1 Answer: A | Question # 2 Answer: B | Question # 3 Answer: A | Question # 4 Answer: B | Question # 5 Answer: C |





