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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Prompt Engineering | 30% | - Agentforce AI Setup & Configuration
|
| Topic 2: Agent Force Concepts | 30% | - Einstein GPT Integration
|
| Topic 3: Reasoning Engine & AI Actions | - Workflow mastery
| |
| Topic 4: Einstein Trust Layer & Security | - Trust Layer & Security Features
|
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NEW QUESTION # 204
Universal Containers (UC) currently tracks Leads with a custom object. UC is preparing to implement the Sales Development Representative (SDR) Agent. Which consideration should UC keep in mind?
Answer: A
Explanation:
Universal Containers (UC) uses a custom object for Leads and plans to implement the Agentforce Sales Development Representative (SDR) Agent. The SDR Agent is a prebuilt, configurable AI agent designed to assist sales teams by qualifying leads and scheduling meetings. Let's evaluate the options based on its functionality and limitations.
NEW QUESTION # 205
When using a prompt template, what should an Agentforce Specialist consider with their grounding data and chosen model?
Answer: A
Explanation:
The most critical technical consideration when pairing a prompt template's grounding data with a chosen Large Language Model (LLM) is the relationship between the two. The correct action is to review the model limitation in Prompt Builder versus the grounding data size (C).
Every LLM has a fixed context window limit, typically expressed in tokens (the model's units for processing text). This token limit defines the maximum amount of input data (the prompt template text + all the dynamic grounding data) and output data the model can handle in a single request.
The grounding data, which is pulled dynamically from Salesforce records (e.g., related lists, long text fields, Flow outputs), varies significantly in size from one record to the next. If the combined size of the prompt and the dynamic data for a specific record exceeds the LLM's token limit, the generative AI request will fail with a "token limit exceeded" error. The Agentforce Specialist must proactively design the template to limit the amount of data retrieved (e.g., using Flow to summarize related lists or querying only essential fields) to ensure it stays within the chosen model's capacity.
NEW QUESTION # 206
An AgentForce Specialist wants to troubleshoot an agent that is hallucinating weblinks. The agent has an action that uses a prompt template, which is using a knowledge retriever, to generate the output text that the agent will use. Which process is appropriate to find the root cause of the hallucination behavior?
Answer: A
Explanation:
Comprehensive and Detailed Explanation From Exact Extract of AgentForce Documents:
According to the AgentForce Troubleshooting and Optimization Guide, hallucinations - instances where the agent fabricates details such as weblinks or data - often occur due to issues in prompt construction or retrieved content grounding. The recommended diagnostic process involves inspecting the prompt template instructions and reviewing the resolved prompt output, including the actual retrieved knowledge chunks.
By examining these areas, the AgentForce Specialist can determine whether the hallucinated content originates from ambiguous prompt phrasing, missing grounding variables, or irrelevant retrieval results. This approach ensures an evidence-based investigation directly linked to the agent's reasoning and generation steps.
NEW QUESTION # 207
Universal Containers has created an Employee Agent. Which step should an Agentforce Specialist take to connect the agent with a Slack channel?
Answer: C
Explanation:
According to the AgentForce for Slack Integration Guide, to connect an Employee Agent (or any internal AgentForce agent) with a Slack channel, the required setup step is to create a connection between Salesforce and the Slack workspace. The documentation specifies: "Before deploying an Employee Agent into Slack, you must establish a secure connection between your Salesforce org and the Slack workspace. This connection enables authentication, permission mapping, and message exchange between the Agent and Slack users." Once the connection is established, the administrator can configure the specific Slack channel where the agent will operate.
NEW QUESTION # 208
Universal Containers (UC) wants to deploy an Agentforce Service Agent to support customers via a web experience. UC uses a Digital Experience site and wants to enable messaging for logged- in users. The customer needs to pass the membership number to the agent for which a pre-chat variable is available. What is a required step to connect the agent to the Digital Experience site using Messaging for In-App and Web?
Answer: A
Explanation:
The required step to route any messaging session, including those from Messaging for In-App and Web (MIAW) on a Digital Experience site, to an Agentforce Service Agent is to Create an Omni-Channel flow that routes messages to the agent (B).
Messaging for In-App and Web utilizes Omni-Channel Routing to direct incoming work items (which are created as MessagingSession records) to the correct destination. When setting up the Messaging Channel for a Digital Experience site, the Routing Type must be configured to use a Flow. This Flow is an Omni-Channel Flow that explicitly contains a Route Work action element configured to route to the Agentforce Service Agent.
Crucially, this Omni-Channel Flow also handles the passing of the pre-chat variables (like the membership number). The pre-chat variables are mapped in the Messaging Channel settings to input variables in the Omni-Channel Flow. The Flow can then use this membership number to perform a record lookup, enrich the context of the conversation (e.g., by updating the related MessagingSession record), and then successfully route the session to the Agentforce Service Agent using the Route To: Bot action, which targets the specific Agentforce Agent.
NEW QUESTION # 209
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