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| Section | Weight | Objectives |
|---|---|---|
| Governance & Observability | 10% | - AI governance
|
| Data Cloud & Grounding | 20% | - Data integration for AI agents
|
| Testing, Deployment & Lifecycle | 15% | - Agent lifecycle management
|
| AI Agents | 35% | - Agent setup and orchestration
|
| Prompt Engineering | 20% | - Prompt Builder usage
|
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NEW QUESTION # 40
What is An Agentforce able to do when the "Enrich event logs with conversation data" setting in Agent is enabled?
Answer: C
Explanation:
When the "Enrich event logs with conversation data" setting is enabled in Agent, it allows An Agentforce or admin to view session data, including both the user input and copilot responses from interactions over the past 7 days. This data is crucial for monitoring how the copilot is being used, analyzing its performance, and improving future interactions based on past inputs.
This setting enriches the event logs with detailed conversational data for better insights into the interaction history, helping Agentforce Specialists track AI behavior and user engagement.
NEW QUESTION # 41
Coral Cloud Resorts is uploading thousands of new HTML knowledge articles files for a resort launch. To ensure Agentforce retrieves accurate responses quickly, which chunking strategy should be used when creating a new index?
Answer: B
Explanation:
In AgentForce documentation on Knowledge Indexing and Chunking Strategies, Salesforce emphasizes that when uploading large volumes of structured content such as HTML or documentation files, the system should use section-aware chunking. The guide states: "Section- aware chunking preserves the logical boundaries of headings, paragraphs, and sub-sections in structured documents like HTML or PDF files, allowing the agent to retrieve contextually accurate and relevant responses quickly." This method ensures that the agent does not split content mid-section or lose contextual relationships between headings and body text. It enhances both retrieval speed and answer precision.
NEW QUESTION # 42
Universal Containers wants to allow its service agents to query the current fulfillment status of an order with natural language. There is an existing auto launched flow to query the information from Oracle ERP, which is the system of record for the order fulfillment process. How should An Agentforce apply the power of conversational AI to this use case?
Answer: C
Explanation:
To enable Universal Containers service agents to query the current fulfillment status of an order using natural language and leverage an existing auto-launched flow that queries Oracle ERP, the best solution is to create a custom copilot action that calls the flow. This action will allow Agent to interact with the flow and retrieve the required order fulfillment information seamlessly. Custom copilot actions can be tailored to call various backend systems or flows in response to user requests.
NEW QUESTION # 43
A Salesforce Agentforce Specialist is reviewing the feedback from a customer about the ineffectiveness of the prompt template. What should the Agentforce Specialist do to ensure the prompt template's effectiveness?
Answer: C
Explanation:
To address the ineffectiveness of a prompt template reported by a customer, the Salesforce Agentforce Specialist should use the Prompt Builder Scorecard (Option B). This tool is explicitly designed to evaluate and monitor prompt templates against key criteria such as relevance, accuracy, safety, and grounding. By leveraging the scorecard, the specialist can systematically identify weaknesses in the template and make data-driven refinements. While monitoring and refining based on user feedback (Option A) is a general best practice, the Prompt Builder Scorecard is Salesforce's recommended tool for structured evaluation, aligning with documented processes for maintaining prompt effectiveness. Changing the grounding object (Option C) without proper evaluation is reactive and does not address the root cause.
NEW QUESTION # 44
An Agentforce Service Agent, who has been successfully assisting customers with service requests in Salesforce, is now unable to help customers with issues related to a new product replacement process. The company recently implemented a custom Product Replacement object in Salesforce to track and manage these replacements. Which Agentforce Agent User change must be implemented to address this issue?
Answer: B
Explanation:
Why is "Permission Set Read Access" the correct answer?
If an Agentforce Service Agent is unable to assist customers with the new Product Replacement process, it is likely due to missing object permissions.
Key Considerations for Object Access in Agentforce:
Custom Objects Require Permission Set Access
The new Product Replacement object must be explicitly assigned to the agent's permission set.
Without Read access, the agent cannot view or interact with the object.
Ensuring Full Data Access for Agents
In Setup -> Permission Sets, the admin should:
Grant Read access to the Product Replacement object
Ensure that related fields (e.g., status, replacement reason) are also accessible Aligning AI and Agent Workflows If Einstein AI is used to suggest solutions, the agent must have visibility into the Product Replacement object for context-aware responses.
NEW QUESTION # 45
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