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| Section | Weight | Objectives |
|---|---|---|
| Prompt Engineering | 20% | - Prompt template creation: field generation, flex types - Prompt management and user roles - Grounding techniques and best practices - Prompt Builder usage and use cases |
| Multi-Agent Interoperability | 5% | - Agent API usage scenarios - Agent-to-agent communication - Model Context Protocol (MCP) |
| Development Lifecycle | 15% | - Version control and maintenance - Deployment: sandbox to production - Testing agents in Testing Center - Monitoring, adoption and optimization |
| Data Cloud for Agentforce | 20% | - Agentforce Data Library types - Unstructured data processing: chunking, indexing - Retrievers and search types: keyword, vector, hybrid - Improving response accuracy with data grounding |
| AI Agents | 35% | - Agent types: Service, Sales, Employee - Topics and actions configuration - Channel integration: digital experience, email, Slack - Agent architecture and reasoning engine - Deterministic controls: filters and variables - Agent User security and permissions |
>> Latest Salesforce AI-201 Test Cram <<
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NEW QUESTION # 138
What is the role of the large language model (LLM) in understanding intent and executing an Agent Action?
Answer: A
Explanation:
In Agentforce, the large language model (LLM), powered by the Atlas Reasoning Engine, interprets user requests and drives Agent Actions.
NEW QUESTION # 139
An Agentforce Service Agent, who has been successfully assisting customers with service requests in Salesforce, is now unable to help customers with issues related to a new product replacement process. The company recently implemented a custom Product Replacement object in Salesforce to track and manage these replacements. Which Agentforce Agent User change must be implemented to address this issue?
Answer: C
Explanation:
Why is "Permission Set Read Access" the correct answer?
If an Agentforce Service Agent is unable to assist customers with the new Product Replacement process, it is likely due to missing object permissions.
Key Considerations for Object Access in Agentforce:
Custom Objects Require Permission Set Access
The new Product Replacement object must be explicitly assigned to the agent's permission set.
Without Read access, the agent cannot view or interact with the object.
Ensuring Full Data Access for Agents
In Setup -> Permission Sets, the admin should:
Grant Read access to the Product Replacement object
Ensure that related fields (e.g., status, replacement reason) are also accessible Aligning AI and Agent Workflows If Einstein AI is used to suggest solutions, the agent must have visibility into the Product Replacement object for context-aware responses.
NEW QUESTION # 140
What considerations should an Agentforce Specialist be aware of when using Record Snapshots grounding in a prompt template?
Answer: B
Explanation:
Record Snapshots grounding in Agentforce prompt templates allows the AI to access and use data from a specific Salesforce record (e.g., fields and related records) to generate contextually relevant responses. However, there are specific limitations to consider. Let's analyze each option based on official documentation.
NEW QUESTION # 141
Universal Containers (UC) has a legacy system that needs to integrate with Salesforce. UC wishes to create a digest of account action plans using the generative API feature. Which API service should UC use to meet this requirement?
Answer: B
Explanation:
To create a digest of account action plans using the generative API feature, Universal Containers should use the REST API. The REST API is ideal for integrating Salesforce with external systems and enabling interaction with Salesforce data, including generative capabilities like creating summaries or digests. It supports modern web standards and is suitable for flexible, lightweight interactions between Salesforce and legacy systems.
Metadata API is used for retrieving and deploying metadata, not for data operations like generating summaries.
SOAP API is an older API used for integration but is less flexible compared to REST for this specific use case.
NEW QUESTION # 142
Universal Containers wants to implement a customer verification process where sensitive account information can only be accessed after the customer passes identity verification. The agent must enforce this security rule deterministically without allowing the large language model (LLM) to bypass the verification requirement. What should an Agentforce Specialist recommend as the best solution?
Answer: A
Explanation:
The AgentForce Security and Deterministic Logic Guide specifies that sensitive actions must be gated through conditional filters linked to verification variables, not through natural language. It states: "For any process requiring secure, deterministic access, create a custom variable (e.g., IsCustomerVerified) that stores the verification status as a Boolean. Apply a filter expression to all protected actions (e.g., IsCustomerVerified = true). This ensures the LLM cannot bypass or alter access logic." This configuration ensures security and determinism because the execution of sensitive actions is programmatically enforced, not dependent on the LLM's understanding.
NEW QUESTION # 143
......
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