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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Data Cloud for Agentforce | 20% | - Improving response accuracy with data grounding - Retrievers and search types: keyword, vector, hybrid - Unstructured data processing: chunking, indexing - Agentforce Data Library types |
| Topic 2: 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 |
| Topic 3: Development Lifecycle | 15% | - Monitoring, adoption and optimization - Testing agents in Testing Center - Version control and maintenance - Deployment: sandbox to production |
| Topic 4: Multi-Agent Interoperability | 5% | - Agent-to-agent communication - Agent API usage scenarios - Model Context Protocol (MCP) |
| Topic 5: AI Agents | 35% | - Agent types: Service, Sales, Employee - Topics and actions configuration - Channel integration: digital experience, email, Slack - Deterministic controls: filters and variables - Agent User security and permissions - Agent architecture and reasoning engine |
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NEW QUESTION # 142
Universal Container's internal auditing team asks An Agentforce to verify that address information is properly masked in the prompt being generated. How should the Agentforce Specialist verify the privacy of the masked data in the Einstein Trust Layer?
Answer: A
Explanation:
The AI audit trail in Salesforce provides a detailed log of AI activities, including the data used, its handling, and masking procedures applied in the Einstein Trust Layer. It allows the Agentforce Specialist to inspect and verify that sensitive data, such as addresses, is appropriately masked before being used in prompts or outputs.
Enable data encryption on the address field: While encryption ensures data security at rest or in transit, it does not verify masking in AI operations.
Review the platform event logs: Platform event logs capture system events but do not specifically focus on the handling or masking of sensitive data in AI processes.
Inspect the AI audit trail: This is the most relevant option, as it provides visibility into how data is processed and masked in AI activities.
NEW QUESTION # 143
A Universal Containers administrator is setting up Einstein Data Libraries. After creating a new library, the administrator notices that only the file upload option is available; there is no option to configure the library using a Salesforce Knowledge base. What is the most likely cause of this Issue?
Answer: C
Explanation:
Why is "Salesforce Knowledge is not enabled" the correct answer?
If an administrator only sees the file upload option in Einstein Data Libraries and cannot configure a Salesforce Knowledge base, the most likely reason is that Salesforce Knowledge is not enabled in the organization.
Key Considerations for Einstein Data Libraries:
Salesforce Knowledge Integration is Optional
Einstein Data Libraries can pull knowledge data only if Salesforce Knowledge is enabled.
If Knowledge is not activated, the system will default to file uploads as the only available option.
How to Fix This Issue?
The administrator should enable Salesforce Knowledge in Setup Knowledge Settings.
Once enabled, the option to configure Knowledge-based Data Libraries will become available.
NEW QUESTION # 144
Universal Containers' administrator has developed a new agent in a sandbox environment and now wants to deploy it to production. What should the administrator do to deploy an agent?
Answer: B
Explanation:
As per the AgentForce Deployment and Lifecycle Management Guide, AgentForce agents, including their topics, actions, and prompt templates, can be deployed from sandbox to production using Salesforce change sets.
Administrators should create an outbound change set in the sandbox environment that includes all relevant components (Agent definition, prompt templates, topic configurations, flows, and permissions) and then upload it to production for validation and deployment. This process ensures consistency, auditability, and proper dependency tracking between environments.
NEW QUESTION # 145
An Agentforce is creating a custom action in Agent. Which option is available for the Agentforce Specialist to choose for the custom copilot action?
Answer: B
Explanation:
When creating a custom action in Agent, one of the available options is to use Flows. Flows are a powerful automation tool in Salesforce, allowing the Agentforce Specialist to define custom logic and actions within the Copilot system. This makes it easy to extend Copilot's functionality without needing custom code.
While Apex triggers and SOQL are important Salesforce tools, Flows are the recommended method for creating custom actions within Agent because they are declarative and highly adaptable.
NEW QUESTION # 146
An Agentforce wants to use the related lists from an account in a custom prompt template. What should the Agentforce Specialist consider when configuring the prompt template?
Answer: A
Explanation:
When configuring a custom prompt template to use related lists, the Agentforce Specialist must be aware of the maximum number of related list merge fields that can be included. Salesforce enforces limits to ensure prompt templates perform efficiently and do not overload the system with too much data. As a best practice, it's important to monitor and optimize the number of merge fields used.
NEW QUESTION # 147
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