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Salesforce AI-201 Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Einstein Trust Layer & Security- Trust Layer & Security Features
  • 1. Enterprise-grade deployment
- Data Masking
  • 1. Configuration of privacy data entities
Topic 2: Agent Force Concepts30%- Einstein GPT Integration
  • 1. Advanced implementation strategies
- Data Cloud & Grounding Techniques
  • 1. Real-world applications
Topic 3: Reasoning Engine & AI Actions- Workflow mastery
  • 1. Standard Agent actions
  • 2. Custom Agent actions (Flows)
  • 3. Custom Agent actions (Apex)
Topic 4: Prompt Engineering30%- Prompt Builder & Template Creation
  • 1. Best practices
- Agentforce AI Setup & Configuration
  • 1. Advanced implementation strategies

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Salesforce Certified Agentforce Specialist Sample Questions (Q42-Q47):

NEW QUESTION # 42
Universal Containers, dealing with a high volume of chat inquiries, implements Einstein Work Summaries to boost productivity. After an agent-customer conversation, which additional information does Einstein generate and fill, apart from the "summary"'

Answer: C

Explanation:
Einstein Work Summaries automatically generate concise summaries of customer interactions (e.g., chat transcripts). Beyond the "summary" field, it extracts and populates Issue (key problem discussed) and Resolution (action taken to resolve the issue). These fields help agents and upervisors quickly grasp the conversation's context without reviewing the full transcript.


NEW QUESTION # 43
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?

Answer: B

Explanation:
Since security and data privacy are critical, the best option for the Agentforce Specialist is to integrate the fine-tuned LLM (Large Language Model) into Salesforce by adding it to Einstein Studio Model Builder. Einstein Studio allows organizations to bring their own AI models (BYOM), ensuring the model is securely managed within Salesforce's environment, adhering to data privacy standards.


NEW QUESTION # 44
An Agentforce Specialist is tasked with analyzing Agent interactions, looking into user inputs, requests, and queries to identify patterns and trends. What functionality allows the Agentforce Specialist to achieve this?

Answer: B

Explanation:
The task requires analyzing user inputs, requests, and queries to identify patterns and trends in Agentforce interactions.


NEW QUESTION # 45
How does Secure Data Retrieval ensure that only authorized users can access necessary Salesforce data for dynamic grounding?

Answer: C

Explanation:
Secure Data Retrieval enforces Salesforce's security model by dynamically grounding data access in the permissions of the user executing the prompt. This ensures compliance with CRUD (Create, Read, Update, Delete) and FLS (Field-Level Security) settings, preventing unauthorized access to sensitive data. For example, if a user lacks access to a specific object or field, the AI model cannot retrieve it for dynamic grounding.


NEW QUESTION # 46
Universal Containers wants to use an external large language model (LLM) in Prompt Builder.
What should An Agentforce recommend?

Answer: B

Explanation:
Bring Your Own Large Language Model (BYO-LLM) functionality in Einstein Studio allows organizations to integrate and use external large language models (LLMs) within the Salesforce ecosystem. Universal Containers can leverage this feature to connect and ground prompts with external LLMs, allowing for custom AI model use cases and seamless integration with Salesforce data.


NEW QUESTION # 47
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