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| Section | Weight | Objectives |
|---|---|---|
| AI Agents | 35% | - Agent behavior configuration
|
| Data Cloud & Grounding | 20% | - Data integration for AI agents
|
| Prompt Engineering | 20% | - Grounding techniques
|
| Testing, Deployment & Lifecycle | 15% | - Agent lifecycle management
|
| Governance & Observability | 10% | - AI governance
|
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NEW QUESTION # 272
An administrator is responsible for ensuring the security and reliability of Universal Containers' (UC) CRM data. UC needs enhanced data protection and up-to-date AI capabilities. UC also needs to include relevant information from a Salesforce record to be merged with the prompt.
Which feature in the Einstein Trust Layer best supports UC's need?
Answer: A
Explanation:
Dynamic grounding with secure data retrieval is a key feature in Salesforce's Einstein Trust Layer, which provides enhanced data protection and ensures that AI-generated outputs are both accurate and securely sourced. This feature allows relevant Salesforce data to be merged into the AI-generated responses, ensuring that the AI outputs are contextually aware and aligned with real-time CRM data.
Dynamic grounding means that AI models are dynamically retrieving relevant information from Salesforce records (such as customer records, case data, or custom object data) in a secure manner. This ensures that any sensitive data is protected during AI processing and that the AI model's outputs are trustworthy and reliable for business use.
The other options are less aligned with the requirement:
Data masking refers to obscuring sensitive data for privacy purposes and is not related to merging Salesforce records into prompts.
Zero-data retention policy ensures that AI processes do not store any user data after processing, but this does not address the need to merge Salesforce record information into a prompt.
NEW QUESTION # 273
Universal Containers wants to be able to detect with a high level confidence if content generated by a large language model (LLM) contains toxic language. Which action should an Al Specialist take in the Trust Layer to confirm toxicity is being appropriately managed?
Answer: C
Explanation:
To ensure that content generated by a large language model (LLM) is appropriately screened for toxic language, the Agentforce Specialist should create a Trust Layer audit report within Data Cloud. By using the toxicity detector type filter, the report can display toxic responses along with their respective toxicity scores, allowing Universal Containers to monitor and manage any toxic content generated with a high level of confidence.
NEW QUESTION # 274
What is true of Agentforce Testing Center?
Answer: C
Explanation:
The Agentforce Testing Center is a tool in Agentforce Studio for validating agent performance.
NEW QUESTION # 275
What should An Agentforce consider when using related list merge fields in a prompt template associated with an Account object in Prompt Builder?
Answer: B
Explanation:
When using related list merge fields in a prompt template associated with the Account object in Prompt Builder, the Activities related list is not supported due to it being a polymorphic field.
Polymorphic fields can reference multiple different types of objects, which makes them incompatible with some merge field operations in prompt generation.
NEW QUESTION # 276
An Agentforce Agent has been developed with multiple topics and Agent Actions that use flows and Apex. Which options are available for deploying these to production?
Answer: B
Explanation:
Why is "Deploy flows, Apex, and all agent-related items using either change sets or the Salesforce CLI/Metadata API" the correct answer?
When deploying an Agentforce Agent with multiple topics and Agent Actions that use flows and Apex, a complete deployment solution is required. Change sets and the Salesforce CLI/Metadata API support the deployment of flows, Apex code, and agent-related metadata.
Key Considerations for Agentforce Deployments:
Supports Deployment of All Required Components
Agentforce Agents include flows, Apex classes, topics, and agent actions.
Change sets and Salesforce CLI/Metadata API allow deployment of all these components together, ensuring a smooth transition to production.
Agentforce Metadata Can Be Deployed Using Standard Tools
Change Sets: Allows admins to move configurations, custom objects, and metadata between Salesforce environments.
Salesforce CLI/Metadata API: Enables scripted deployments, automating the transfer of Agentforce configurations.
Ensures a Complete Migration Without Manual Configuration
Deploying all components together reduces the risk of misconfiguration.
Automating deployments using the Metadata API ensures consistency across environments.
NEW QUESTION # 277
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