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NEW QUESTION # 149
Choose 1 option.
Cloud Kicks wants to integrate its agent with its custom website. The goal is for customers to interact with the custom agent chat interface.
Which approach provides the framework for the custom web application to communicate with the agent?
Answer: B
Explanation:
The AgentForce API Integration Guide defines the Agent API as the framework that enables external web or mobile applications to communicate directly with Salesforce-hosted agents. This API supports message exchange, session management, and context persistence - allowing developers to build custom chat interfaces while maintaining secure, real-time connectivity with the AgentForce reasoning engine.
Option A (A2A) is for inter-agent collaboration within Salesforce, not for external web integration. Option B (MCP) - Model Context Protocol - is used for context sharing between models and tools, not for front- end integration.
Therefore, the correct framework for enabling communication between a custom website chat interface and an AgentForce agent is Option C - Agent API, as it provides the structured interface for external client applications.
Reference: AgentForce Integration Manual - "Using the Agent API for Web and Application-Based Interactions."
NEW QUESTION # 150
Universal Containers has deployed several specialized Agentforce Employee Agents, such as IT Support, HR Assistant, and Procurement, to assist with internal tasks. Recently, UC's help desk has reported a high volume of failed interactions because employees are frequently selecting the incorrect agent to handle their requests, for example, asking the HR Assistant agent to reset a network password. UC wants to improve the user experience, scale their deployment, and centralize control without requiring employees to guess which agent to use.
Which architectural approach should the Agentforce Specialist recommend to resolve this issue?
Answer: C
Explanation:
The correct answer is B because the problem is not that users need stricter validation; the problem is that users are being forced to choose the right specialized agent themselves. A Single Org Multi-Agent architecture provides a centralized entry point that interprets the employee's intent and routes the request to the correct specialized agent or capability. That removes the guesswork, improves user experience, and scales better as more departmental agents are added. Option A is wrong because validation rules on sessions do not solve intent routing and would create brittle blocking behavior.
Option C still leaves routing responsibility distributed across separate agents and adds extra user friction. Salesforce's Multi-Agent Orchestration guidance describes connecting agents with specialized agents to extend capabilities and coordinate work across agents.
NEW QUESTION # 151
Universal Containers (UC) wants to make a sales proposal and directly use data from multiple unrelated objects (standard and custom) in a prompt template. How should UC accomplish this?
Answer: B
Explanation:
UC needs to incorporate data from multiple unrelated objects (standard and custom) into a prompt template for a sales proposal. Let's evaluate the options based on Agentforce capabilities.
Option A: Create a prompt template passing in a special custom object that connects the records temporarily.
While a custom object could theoretically act as a junction to link unrelated records, this approach requires additional setup (e.g., creating the object, populating it with data via automation), and there's no direct mechanism in Prompt Builder to "pass in" such an object to a prompt template without grounding or flow support. This is inefficient and not a native feature, making it incorrect.
Option B: Create a prompt template-triggered flow to access the data from standard and custom objects.There' s no such thing as a "prompt template-triggered flow" in Salesforce. Flows can invoke prompt templates (e.g., via the "Prompt Template" action), but the reverse-triggering a flow from a prompt template-is not a standard construct. While a flow could gather data from unrelated objects and pass it to a prompt, this option' s terminology is inaccurate, and it's not the most direct solution, making it incorrect.
Option C: Create a Flex template to add resources with standard and custom objects as inputs.In Agentforce's Prompt Builder, a Flex template (short for Flexible Prompt Template) allows users to define dynamic inputs, including data from multiple Salesforce objects (standard or custom), even if they're unrelated. Resources can be added to the template (e.g., via merge fields or Data Cloud queries), enabling the prompt to pull data directly from specified objects without requiring a junction object or complex flows. This is ideal for generating a sales proposal using disparate data sources and aligns with Salesforce's documentation on Flex templates, making it the correct answer.
Why Option C is Correct:
Flex templates are designed for scenarios requiring flexible data inputs, allowing UC to directly reference multiple unrelated objects in the prompt template. This simplifies the process and leverages Prompt Builder's native capabilities, as outlined in Salesforce documentation.
References:
Salesforce Agentforce Documentation: Prompt Builder > Flex Templates - Describes adding multiple object resources as inputs.
Trailhead: Build Prompt Templates in Agentforce - Highlights Flex templates for dynamic data scenarios.
Salesforce Help: Create Flexible Prompts - Confirms support for standard and custom object data.
NEW QUESTION # 152
Universal Containers' current AI data masking rules do not align with organizational privacy and security policies and requirements.
What should An Agentforce recommend to resolve the issue?
Answer: B
Explanation:
WhenUniversal Containers' AI data masking rulesdo not meet organizational privacy and security standards, theAgentforce Specialistshould configure thedata maskingrules within theEinstein Trust Layer.
TheEinstein Trust Layerprovides a secure and compliant environment where sensitive data can be masked or anonymized to adhere to privacy policies and regulations.
* Option A, enabling data masking for sandbox refreshes, is related to sandbox environments, which are separate from how AI interacts with production data.
* Option C, adding masking rules in the LLM setup, is not appropriate because data masking is managed through theEinstein Trust Layer, not the LLM configuration.
The Einstein Trust Layer allows for more granular control over what data is exposed to the AI model and ensures compliance with privacy regulations.
SalesforceAgentforce SpecialistReferences:For more information, refer to:https://help.salesforce.com/s
/articleView?id=sf.einstein_trust_layer_data_masking.htm
NEW QUESTION # 153
Universal Container's internal auditing team asks An Agentforce to verify that address information is properly masked in the prompt being generated.
How should theAgentforce Specialistverify the privacy of the masked data in the Einstein Trust Layer?
Answer: C
Explanation:
TheAI audit trailin Salesforce provides a detailed log of AI activities, including the data used, itshandling, and masking procedures applied in the Einstein Trust Layer. It allows theAgentforce Specialistto inspect and verify that sensitive data, such as addresses, is appropriately masked before being used in prompts or outputs.
* Enable data encryption on the address field: While encryption ensures data security at rest or in transit, it does not verify masking in AI operations.
* Review the platform event logs: Platform event logs capture system events but do not specifically focus on the handling or masking of sensitive data in AI processes.
* Inspect the AI audit trail: This is the most relevant option, as it provides visibility into how data is processed and masked in AI activities.
NEW QUESTION # 154
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