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| Section | Weight | Objectives |
|---|---|---|
| AI Agents | 35% | - Agent architecture and reasoning engine - Agent User security and permissions - Channel integration: digital experience, email, Slack - Topics and actions configuration - Agent types: Service, Sales, Employee - Deterministic controls: filters and variables |
| Multi-Agent Interoperability | 5% | - Model Context Protocol (MCP) - Agent-to-agent communication - Agent API usage scenarios |
| Data Cloud for Agentforce | 20% | - Improving response accuracy with data grounding - Retrievers and search types: keyword, vector, hybrid - Agentforce Data Library types - Unstructured data processing: chunking, indexing |
| Prompt Engineering | 20% | - Prompt management and user roles - Grounding techniques and best practices - Prompt Builder usage and use cases - Prompt template creation: field generation, flex types |
| Development Lifecycle | 15% | - Monitoring, adoption and optimization - Deployment: sandbox to production - Testing agents in Testing Center - Version control and maintenance |
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NEW QUESTION # 218
What is the main purpose of Prompt Builder?
Answer: C
Explanation:
Prompt Builder is designed to help organizations create and configure reusable prompts for large language models (LLMs). By integrating generative AI responses into workflows, Prompt Builder enables customization of AI prompts that interact with Salesforce data and automate complex processes. This tool is especially useful for creating tailored and consistent AI-generated content in various business contexts, including customer service and sales.
NEW QUESTION # 219
When creating a custom retriever in Einstein Studio, which step is considered essential?
Answer: A
Explanation:
In Salesforce's Einstein Studio (part of the Agentforce ecosystem), creating a custom retriever involves setting up a mechanism to fetch data for AI prompts or responses. The essential step is defining the foundation of the retriever: selecting the search index, specifying the data model object (DMO), and identifying the data space (Option A). These elements establish where and what the retriever searches:
Search Index: Determines the indexed dataset (e.g., a vector database in Data Cloud) the retriever queries.
Data Model Object (DMO): Specifies the object (e.g., Knowledge Articles, Custom Objects) containing the data to retrieve.
Data Space: Defines the scope or environment (e.g., a specific Data Cloud instance) for the data.
Filters are noted as optional in Option A, which is accurate-they enhance precision but aren't mandatory for the retriever to function. This step is foundational because without it, the retriever lacks a target dataset, rendering it unusable.
NEW QUESTION # 220
An Agentforce Specialist wants to troubleshoot their Agent's performance. Where should the Agentforce Specialist go to access all user interactions with the Agent, including Agent errors, incorrectly triggered actions, and incomplete plans?
Answer: B
Explanation:
The Agentforce Specialist needs a comprehensive view of user interactions, errors, and action issues for troubleshooting.
NEW QUESTION # 221
Universal Containers needs to create Data Cloud reports to understand agent behavior. Which data lake object (DLO) represents an overarching container capturing contiguous interactions with one or more Al agents?
Answer: A
Explanation:
Per the AgentForce Data Cloud Integration Guide, the AI Agent Session (AIAGENTSESSION) object represents an overarching container that tracks a continuous interaction between one or more AI agents and a user. The document describes: "AI Agent Session is the parent container for a contiguous set of AI Agent interactions. It captures metadata, start and end times, and the relationship to individual messages exchanged during the session."
NEW QUESTION # 222
Universal Containers implemented Agentforce for its users. One user complains that an Agent is not deleting activities from the past 7 days. What is the reason for this issue?
Answer: C
Explanation:
Universal Containers (UC) uses Agentforce, a specialized AI-driven assistant for Salesforce. A user reports that an Agent is unable to delete recent activities.
Why Agentforce Cannot Delete Records
Agentforce's Standard Actions: Agentforce typically has predefined or "standard" actions like Create, Update, or Summarize records. However, a standard Delete Record action is not part of the default set of Agentforce actions.
Implication: If Agentforce has no built-in delete functionality, it cannot remove activities-even if the user has permission to delete them in the Salesforce UI.
NEW QUESTION # 223
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