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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Data Cloud for Agentforce | 20% | - Retrievers and search types: keyword, vector, hybrid - Agentforce Data Library types - Improving response accuracy with data grounding - Unstructured data processing: chunking, indexing |
| Topic 2: Multi-Agent Interoperability | 5% | - Model Context Protocol (MCP) - Agent-to-agent communication - Agent API usage scenarios |
| Topic 3: AI Agents | 35% | - Agent architecture and reasoning engine - Topics and actions configuration - Deterministic controls: filters and variables - Agent User security and permissions - Channel integration: digital experience, email, Slack - Agent types: Service, Sales, Employee |
| Topic 4: Development Lifecycle | 15% | - Version control and maintenance - Deployment: sandbox to production - Monitoring, adoption and optimization - Testing agents in Testing Center |
| Topic 5: Prompt Engineering | 20% | - Prompt Builder usage and use cases - Prompt management and user roles - Prompt template creation: field generation, flex types - Grounding techniques and best practices |
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NEW QUESTION # 185
Universal Containers (UC) wants to empower its marketing team with Al capabilities that help employees quickly find campaign data, generate creative content, and manage project tasks. The solution should also allow marketers to receive personalized support, surface relevant information, and complete work directly in Salesforce. Which Al solution should UC implement?
Answer: A
Explanation:
According to the AgentForce Solutions Overview and Employee Agent documentation, the Employee Agent is designed to empower internal teams, such as marketing, sales, HR, and operations, by providing AI-driven assistance within Salesforce. The guide explains: "Employee Agents help internal users find information, automate tasks, generate content, and manage projects directly in Salesforce. They surface personalized insights, support productivity, and leverage enterprise knowledge sources." In the given scenario, the marketing team requires capabilities for content creation, data lookup, and task management-all within Salesforce. This exactly matches the described functionality of an Employee Agent.
NEW QUESTION # 186
Universal Containers (UC) has configured a data library and wants to restrict indexing of knowledge articles to articles which are only publicly available in their knowledge base, UC also wants the agent to link sources that the large language model (LLM) grounded its response on.
Which settings should help UC with this?
Answer: A
Explanation:
According to the AgentForce Data Library Configuration Guide, administrators can restrict indexing and retrieval of Knowledge articles to publicly available ones and enable source visibility for LLM-grounded responses. The documentation states:
"Within the data library settings, under Knowledge Settings, enable `Use Public Knowledge Articles' to ensure only publicly visible content is indexed. To display citations, enable `Show Sources' so the agent links the specific articles or data records used to ground its response."
NEW QUESTION # 187
When a customer chat is initiated, which functionality in Salesforce provides generative AI replies or draft emails based on recommended Knowledge articles?
Answer: C
Explanation:
When a customer chat is initiated, Einstein Service Replies provides generative AI replies or draft emails based on recommended Knowledge articles. This feature uses the information from the Salesforce Knowledge base to generate responses that are relevant to the customer's query, improving the efficiency and accuracy of customer support interactions.
NEW QUESTION # 188
Universal Containers wants to leverage the Record Snapshots grounding feature in a prompt template. What preparations are required?
Answer: B
Explanation:
Record Snapshots in Salesforce Prompt Builder leverage the data visible on the user's page layout for an object to ground the prompt. This means that the fields and related lists that are configured on the page layout directly influence the data included in the snapshot.
NEW QUESTION # 189
Universal Containers is indexing millions of product manuals where users may ask both structured queries (model numbers) and natural language questions (for example, "How do I reset my device?"). Which retrieval approach should the company use?
Answer: B
Explanation:
According to the AgentForce Retrieval Optimization Guide, when users ask both structured (exact) and unstructured (natural language) questions, the best practice is to use hybrid search.
The documentation states:
"Hybrid search combines the precision of keyword retrieval for structured terms, such as IDs or model numbers, with the semantic flexibility of vector search for natural language queries. This approach ensures both deterministic accuracy and contextual understanding."
NEW QUESTION # 190
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