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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Development Lifecycle | 15% | - Monitoring, adoption and optimization - Deployment: sandbox to production - Version control and maintenance - Testing agents in Testing Center |
| Topic 2: AI Agents | 35% | - Agent architecture and reasoning engine - Deterministic controls: filters and variables - Channel integration: digital experience, email, Slack - Topics and actions configuration - Agent types: Service, Sales, Employee - Agent User security and permissions |
| Topic 3: Data Cloud for Agentforce | 20% | - Unstructured data processing: chunking, indexing - Improving response accuracy with data grounding - Agentforce Data Library types - Retrievers and search types: keyword, vector, hybrid |
| Topic 4: Prompt Engineering | 20% | - Grounding techniques and best practices - Prompt template creation: field generation, flex types - Prompt Builder usage and use cases - Prompt management and user roles |
| Topic 5: Multi-Agent Interoperability | 5% | - Agent-to-agent communication - Model Context Protocol (MCP) - Agent API usage scenarios |
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NEW QUESTION # 233
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 Agent action helps sales reps draft personalized emails to prospects by generating text based on previous successful communications?
Answer: C
Explanation:
UC's sales reps need an AI action to draft personalized emails based on past successful communications, reducing manual review time.
NEW QUESTION # 234
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: B
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 # 235
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: C
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 # 236
Universal Containers wants to use an existing prompt template inside Flow as part of automation.
Answer: A
NEW QUESTION # 237
An administrator at Universal Containers has successfully deployed a new agent from a sandbox to production using a change set. The agent uses a prompt template that invokes a Salesforce flow to perform a complex calculation. In production, when users interact with the agent, it fails with an error message every time the flow is supposed to run. The flow was included in the change set and is present in production. What is the most likely cause of this issue?
Answer: B
Explanation:
Per the AgentForce Deployment and Flow Integration Guide, when deploying flows via change sets, the flows arrive in the production org in "inactive" status by default. The administrator must manually activate the flow post-deployment before it can be executed by agents or users.
This explains why the agent encounters an error when attempting to run the flow--the system recognizes the flow but cannot invoke it because it remains inactive.
NEW QUESTION # 238
......
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