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| Section | Weight | Objectives |
|---|---|---|
| Prompt Engineering | 30% | - User Roles and Management
|
| Agentforce and Sales Cloud | 10% | - Sales Cloud Features
|
| Agentforce Concepts | 30% | - Agent Architecture
|
| Agentforce and Service Cloud | 10% | - Channel Connection
|
| Agentforce and Data Cloud | 20% | - Data Library
|
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NEW QUESTION # 335
Cloud Kicks has long, complex legal agreements. An Agentforce agent must be able to retrieve specific clauses that are often nested within larger sections. The standard chunking method is failing to capture the full context of these clauses.
Which chunking strategy should an administrator use to preserve the structure of the documents?
Answer: C
Explanation:
The correct answer is B. When legal clauses are nested inside larger sections, overly small chunks can split the clause from surrounding definitions, exceptions, or conditions. That makes the retrieved passage technically relevant but contextually incomplete. A larger chunk size keeps more surrounding legal text together, improving the chance that the retriever returns the clause with its dependencies intact. Option A would usually make the problem worse because it increases fragmentation. Option C is not the best fix because keyword matching can find terms, but it does not preserve the legal structure around those terms. In Data 360 search indexes, chunking strategy and maximum token settings directly affect how much text is included in each retrievable chunk, so tuning chunk size is the right corrective lever.
NEW QUESTION # 336
In Model Playground, which hyperparameters of an existing
Salesforce-enabled foundational model can An Agentforce change?
Answer: A
Explanation:
InModel Playground, An Agentforce working with a Salesforce-enabled foundational model has control over specific hyperparameters that can directly affect the behavior of the generative model:
* Temperature: Controls the randomness of predictions. A higher temperature leads to more diverse outputs, while a lower temperature makes the model's responses more focused and deterministic.
* Frequency Penalty: Reduces the likelihood of the model repeating the same phrases or outputs frequently.
* Presence Penalty: Encourages the model to introduce new topics in its responses, rather than sticking with familiar, previously mentioned content.
These hyperparameters are adjustable to fine-tune the model's responses, ensuring that it meets the desired behavior and use case requirements. Salesforce documentation confirms that these three are the key tunable hyperparameters in the Model Playground.
For more details, refer toSalesforce AI Model Playgroundguidance from Salesforce's official documentation on foundational model adjustments.
NEW QUESTION # 337
An Agentforce Specialist is tasked with analyzing Agent interactions, looking into user inputs, requests, and queries to identify patterns and trends. What functionality allows the Agentforce Specialist to achieve this?
Answer: C
Explanation:
The task requires analyzing user inputs, requests, and queries to identify patterns and trends in Agentforce interactions. Let's assess the options based on Agentforce's analytics capabilities.
* Option A: Agent Event Logs dashboard.Agent Event Logs capture detailed technical events (e.g., API calls, errors, or system-level actions) related to agent operations. While useful for troubleshooting or monitoring system performance, they are not designed to analyze user inputs or conversational trends. This option does not meet the requirement and is incorrect.
* Option B: AI Audit and Feedback Data dashboard.There's no specific "AI Audit and Feedback Data dashboard" in Agentforce documentation. Feedback mechanisms exist (e.g., user feedback on responses), and audit trails may track changes, but no single dashboard combines these for analyzing user queries and trends. This option appears to be a misnomer and is incorrect.
* Option C: User Utterances dashboard.The User Utterances dashboard in Agentforce Analytics is specifically designed to analyze user inputs, requests, and queries. It aggregates and visualizes what users are asking the agent, identifying patterns (e.g., common topics) and trends (e.g., rising query types). Specialists can use this to refine agent instructions or topics, making it the perfect tool for this task. This is the correct answer per Salesforce documentation.
Why Option C is Correct:
The User Utterances dashboard is tailored for conversational analysis, offering insights into user interactions that align with the specialist's goal of identifying patterns and trends. It's a documented feature of Agentforce Analytics for post-deployment optimization.
References:
Salesforce Agentforce Documentation: Agent Analytics > User Utterances Dashboard - Describes its use for analyzing user queries.
Trailhead: Monitor and Optimize Agentforce Agents - Highlights the dashboard's role in trend identification.
Salesforce Help: Agentforce Dashboards - Confirms User Utterances as a key tool for interaction analysis.
NEW QUESTION # 338
Universal Containers (UC) is using standard Service AI Grounding. UC created a custom rich text field to be used with Service AI Grounding.
What should UC consider when using standard Service AI Grounding?
Answer: C
Explanation:
Service AI Grounding retrieves data from Salesforce objects to ground AI-generated responses. Key considerations:
Field Types: Standard Service AI Grounding supports String and Text Area fields. Custom rich text fields (e.
g., RichTextArea) are not supported, making Option B correct.
Objects: While Service AI Grounding primarily uses Case and Knowledge objects (Option A), the limitation here is the field type, not the object.
Visibility: Service AI Grounding respects user permissions and sharing settings unless overridden (Option C is incorrect).
References:
Salesforce Help: Service AI Grounding Requirements
Explicitly states support for "Text Area and String fields" only.
NEW QUESTION # 339
Universal Containers (UC) is implementing Agentforce Service Agent on Email, UC made an email template and now needs to connect it to a Service Agent.
What should an Agentforce Specialist recommend?
Answer: A
Explanation:
According to the AgentForce for Service Configuration Guide, when implementing Service Agents on Email, administrators must create an Email Configuration to connect the agent with the appropriate email channel and templates. The documentation specifies: "To enable Service Agents to handle emails, create an Email Configuration that links the agent to the email address, template, and routing parameters. This configuration allows the Service Agent to read, interpret, and respond using the defined template." Option B (creating an Omni-Channel flow) applies to routing live messages or chats, not configuring email agents.
Option C is incorrect because Service Agents do not automatically connect to email templates - a manual configuration is required.
Thus, Option A is correct as it aligns with Salesforce's documented process for connecting email templates to AgentForce Service Agents.
References (AgentForce Documents / Study Guide):
* AgentForce for Service Setup Guide: "Creating Email Configurations for Service Agents"
* Salesforce Service Cloud Email Configuration Overview
* AgentForce Study Guide: "Deploying Service Agents on Email Channels"
NEW QUESTION # 340
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