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| Section | Weight | Objectives |
|---|---|---|
| Reasoning Engine & AI Actions | - Workflow mastery
| |
| Agent Force Concepts | 30% | - Einstein GPT Integration
|
| Einstein Trust Layer & Security | - Data Masking
| |
| Prompt Engineering | 30% | - Prompt Builder & Template Creation
|
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NEW QUESTION # 106
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: C
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 # 107
Universal Containers (UC) is discussing its AI strategy in an agile Scrum meeting. Which business requirement would lead An Agentforce to recommend connecting to an external foundational model via Einstein Studio (Model Builder)?
Answer: C
Explanation:
Einstein Studio (Model Builder) allows organizations to connect and utilize external foundational models while fine-tuning them with company-specific data. This capability is particularly suited to businesses like Universal Containers (UC) that require customization of foundational models to better align with their unique data and use cases.
NEW QUESTION # 108
Universal Containers is rolling out a new generative AI initiative. Which Prompt Builder limitations should the Agentforce Specialist be aware of?
Answer: C
Explanation:
When rolling out a new Generative AI initiative in Salesforce using Prompt Builder, it's important to understand its current limitations. One key limitation is that changes to prompt templates (creation, edits, or deletions) are not logged in the Setup Audit Trail, which means admins won't have a historical record of modifications for compliance or troubleshooting.
NEW QUESTION # 109
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?
Answer: A
Explanation:
To access externally-hosted models, such as a large language model (LLM) hosted on AWS, the Model Builder in Salesforce is the appropriate tool. Model Builder allows teams to integrate and deploy external AI models into the Salesforce platform, making it possible to leverage models hosted outside of Salesforce infrastructure while still benefiting from the platform's native AI capabilities.
NEW QUESTION # 110
Universal Containers (UC) needs to create a custom prompt template that can be called from a Lightning web component. Which prompt template type should UC create?
Answer: A
Explanation:
The AgentForce Developer Integration Guide specifies that Flex prompt templates are the correct type for custom or embedded integrations, such as invoking a prompt from a Lightning Web Component (LWC).
Flex templates are designed for general-purpose use cases and can be called programmatically via Apex, Flow, or LWC APIs. They offer flexible input and output structures, allowing developers to integrate AgentForce reasoning into custom applications and UI components.
NEW QUESTION # 111
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