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| Section | Weight | Objectives |
|---|---|---|
| AI Agents | 35% | - Agent architecture and reasoning engine - Agent types: Service, Sales, Employee - Agent User security and permissions - Deterministic controls: filters and variables - Topics and actions configuration - Channel integration: digital experience, email, Slack |
| Data Cloud for Agentforce | 20% | - Improving response accuracy with data grounding - Agentforce Data Library types - Retrievers and search types: keyword, vector, hybrid - Unstructured data processing: chunking, indexing |
| Development Lifecycle | 15% | - Testing agents in Testing Center - Version control and maintenance - Deployment: sandbox to production - Monitoring, adoption and optimization |
| Prompt Engineering | 20% | - Prompt Builder usage and use cases - Grounding techniques and best practices - Prompt template creation: field generation, flex types - Prompt management and user roles |
| Multi-Agent Interoperability | 5% | - Agent API usage scenarios - Agent-to-agent communication - Model Context Protocol (MCP) |
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NEW QUESTION # 236
After configuring and saving a Salesforce Agentforce Data Library (regardless of the data source), which components are automatically created and available in Data Cloud?
Answer: B
Explanation:
Why is "A data stream, a search index, and a retriever" the correct answer?
When a Salesforce Agentforce Data Library is configured and saved, it automatically creates three essential components in Data Cloud to facilitate AI-driven search and retrieval.
Key Components Created in Data Cloud:
Data Stream
This acts as the pipeline that brings data into Data Cloud.
It enables real-time data ingestion from sources such as Salesforce records, PDFs, or external databases.
Search Index
After ingestion, data is indexed for efficient search and retrieval.
This allows AI models to perform structured queries and retrieve relevant data faster.
Retriever
The retriever is an AI-powered search mechanism that uses the search index to fetch the most relevant data.
It ensures that AI-generated responses are grounded in structured, reliable data.
NEW QUESTION # 237
Which business requirement presents a good use case for leveraging Einstein Prompt Builder?
Answer: C
Explanation:
Einstein Prompt Builder is a Salesforce feature that helps generate text (summaries, email content, responses) using AI models.
The question presents three potential use cases, asking which one best fits the capabilities of Einstein Prompt Builder.
Einstein Prompt Builder Typical Use Cases
Text Generation & Summaries: Great for writing or summarizing content, like responding to an email or generating text for a record field.
NEW QUESTION # 238
Universal Containers plans to enhance the customer support team's productivity using AI. Which specific use case necessitates the use of Prompt Builder?
Answer: A
Explanation:
The use case that necessitates the use of Prompt Builder is creating a draft of a support bulletin post for new product patches. Prompt Builder allows the Agentforce Specialist to create and refine prompts that generate specific, relevant outputs, such as drafting support communication based on product information and patch details.
NEW QUESTION # 239
Northern Trail Outfitters (NTO) wants to configure Einstein Trust Layer in its production org but is unable to see the option on the Setup page. After provisioning Data Cloud, which step must an Al Specialist take to make this option available to NTO?
Answer: C
Explanation:
For Northern Trail Outfitters (NTO) to configure the Einstein Trust Layer, the Einstein Generative AI feature must be enabled. The Einstein Trust Layer is closely tied to generative AI capabilities, ensuring that AI-generated content complies with data privacy, security, and trust standards.
NEW QUESTION # 240
Universal Containers (UC) is looking to improve its sales team's productivity by providing real- time insights and recommendations during customer interactions. Why should UC consider using Agentforce Sales Agent?
Answer: C
Explanation:
Agentforce Sales Agent provides real-time insights and AI-powered recommendations, which are designed to streamline the sales process and help sales representatives focus on key tasks to increase conversion rates. It offers features like lead scoring, opportunity prioritization, and proactive recommendations, ensuring that sales teams can interact with customers efficiently and close deals faster.
NEW QUESTION # 241
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