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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Data Cloud for Agentforce | 20% | - Agentforce Data Library types - Improving response accuracy with data grounding - Retrievers and search types: keyword, vector, hybrid - Unstructured data processing: chunking, indexing |
| Topic 2: Prompt Engineering | 20% | - Prompt management and user roles - Prompt Builder usage and use cases - Prompt template creation: field generation, flex types - Grounding techniques and best practices |
| Topic 3: Development Lifecycle | 15% | - Deployment: sandbox to production - Testing agents in Testing Center - Monitoring, adoption and optimization - Version control and maintenance |
| Topic 4: Multi-Agent Interoperability | 5% | - Agent API usage scenarios - Model Context Protocol (MCP) - Agent-to-agent communication |
| Topic 5: AI Agents | 35% | - Topics and actions configuration - Agent types: Service, Sales, Employee - Agent architecture and reasoning engine - Channel integration: digital experience, email, Slack - Agent User security and permissions - Deterministic controls: filters and variables |
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NEW QUESTION # 242
An Agentforce implements Einstein Sales Emails for a sales team. The team wants to send personalized follow-up emails to leads based on their interactions and data stored in Salesforce.
The Agentforce Specialist needs to configure the system to use the most accurate and up-to-date information for email generation. Which grounding technique should the Agentforce Specialist use?
Answer: B
Explanation:
For Einstein Sales Emails to generate personalized follow-up emails, it is crucial to ground the email content with the most up-to-date and accurate information. Grounding refers to connecting the AI model with real-time data. The most appropriate technique in this case is Ground with Record Merge Fields. This method ensures that the content in the emails pulls dynamic and accurate data directly from Salesforce records, such as lead or contact information, ensuring the follow-up is relevant and customized based on the specific record.
Record Merge Fields ensure the generated emails are highly personalized using data like lead name, company, or other Salesforce fields directly from the records.
Apex Merge Fields are typically more suited for advanced, custom logic-driven scenarios but are not the most straightforward for this use case.
Automatic grounding using Draft with Einstein is a different feature where Einstein automatically drafts the email, but it does not specifically ground the content with record-specific data like Record Merge Fields.
NEW QUESTION # 243
Amid their busy schedules, sales reps at Universal Containers dedicate time to follow up with prospects and existing clients via email regarding renewals or new deals. They spend many hours throughout the week reviewing past communications and details about their customers before performing their outreach. Which standard Copilot action helps sales reps draft personalized emails to prospects by generating text based on previous successful communications?
Answer: C
Explanation:
For sales reps who need to draft personalized emails based on previous communications, the Agentforce Specialist should recommend the Agent Action: Draft or Revise Sales Email. This action uses AI to generate or revise email content, leveraging past successful communications to create personalized and relevant outreach to prospects or clients.
Find Similar Opportunities is used for opportunity matching, not email drafting.
Summarize Record provides a summary of customer data but does not directly help with drafting emails.
NEW QUESTION # 244
Cloud Kicks (CK) is launching a new partner portal on Experience Cloud, CK wants to provide partners with an agent that can answer questions about product specifications from the knowledge base and allow them to submit a new Lead for a potential customer they've identified.
The agent must be accessible only to authenticated partner users on the portal. Which agent type is required to meet this scenario?
Answer: C
Explanation:
The required agent type is the Service Agent (C). The core function described-answering questions from the knowledge base-is the primary task of a Service Agent, which is designed for self-service support and knowledge article retrieval. Although the requirement also includes the ability to submit a new Lead, Service Agent models are highly configurable to include custom actions, such as a "Create Lead" action, using Agentforce Builder. Furthermore, the Service Agent type is intended to be deployed to external-facing Experience Cloud sites to provide support to external authenticated users, such as partners.
NEW QUESTION # 245
An administrator wants to check the response of the Flex prompt template they've built, but the preview button is greyed out. What is the reason for this?
Answer: A
Explanation:
When the preview button is greyed out in a Flex prompt template, it is often because the records related to the prompt have not been selected. Flex prompt templates pull data dynamically from Salesforce records, and if there are no records specified for the prompt, it can't be previewed since there is no content to generate based on the template.
NEW QUESTION # 246
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: C
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.
NEW QUESTION # 247
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