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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Data Cloud for Agentforce | 20% | - Retrievers and search types: keyword, vector, hybrid - Agentforce Data Library types - Unstructured data processing: chunking, indexing - Improving response accuracy with data grounding |
| Topic 2: AI Agents | 35% | - Agent types: Service, Sales, Employee - Agent architecture and reasoning engine - Channel integration: digital experience, email, Slack - Topics and actions configuration - Agent User security and permissions - Deterministic controls: filters and variables |
| Topic 3: Prompt Engineering | 20% | - Prompt management and user roles - Prompt template creation: field generation, flex types - Grounding techniques and best practices - Prompt Builder usage and use cases |
| Topic 4: Development Lifecycle | 15% | - Monitoring, adoption and optimization - Testing agents in Testing Center - Version control and maintenance - Deployment: sandbox to production |
| Topic 5: Multi-Agent Interoperability | 5% | - Agent-to-agent communication - Agent API usage scenarios - Model Context Protocol (MCP) |
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NEW QUESTION # 276
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 # 277
Coral Cloud Resorts (CCR) uses Agentforce to assist customers with booking and service issues.
CCR wants to implement a triage process 50 that:
- High severity requests must be escalated to a human service rep.
- Lower severity requests should result in creating a support case for
the guest.
The requirement is to achieve the highest reliability and determinism in the response from the agent.
Which approach should an Agentforce Specialist recommend?
Answer: B
Explanation:
The AgentForce Conditional Logic and Triage Design Guide recommends using custom variables and deterministic filters for reliable decision-making in AI agents. The document explains: "For deterministic triage flows, create a variable (e.g., severityLevel) populated by an action or rule.
Then, apply filters so that specific actions execute only when the variable matches defined criteria. This approach guarantees predictable and auditable outcomes." In this case, severityLevel controls whether to escalate to a human rep or create a support case, ensuring no ambiguity in execution.
NEW QUESTION # 278
After configuring and saving a Salesforce Agentforce Data Library (regardless of the data source), which components are automatically created and available in Data Cloud?
Answer: A
Explanation:
Why is "A data stream, a search index, and a retriever" the correct answer?
When a Salesforce Agentforce Data Library is configured and saved, it automatically creates three essential components in Data Cloud to facilitate AI-driven search and retrieval.
Key Components Created in Data Cloud:
Data Stream
This acts as the pipeline that brings data into Data Cloud.
It enables real-time data ingestion from sources such as Salesforce records, PDFs, or external databases.
Search Index
After ingestion, data is indexed for efficient search and retrieval.
This allows AI models to perform structured queries and retrieve relevant data faster.
Retriever
The retriever is an AI-powered search mechanism that uses the search index to fetch the most relevant data.
It ensures that AI-generated responses are grounded in structured, reliable data.
NEW QUESTION # 279
Universal Containers (UC) is implementing Einstein Generative AI to improve customer insights and interactions. UC needs audit and feedback data to be accessible for reporting purposes.
What is a consideration for this requirement?
Answer: B
Explanation:
When implementing Einstein Generative AI for improved customer insights and interactions, the Data Cloud is a key consideration for storing and managing large-scale audit and feedback data.
The Salesforce Data Cloud (formerly known as Customer 360 Audiences) is designed to handle and unify massive datasets from various sources, making it ideal for storing data required for AI- powered insights and reporting. By provisioning Data Cloud, organizations like Universal Containers (UC) can gain real-time access to customer data, making it a central repository for unified reporting across various systems.
Audit and feedback data generated by Einstein Generative AI needs to be stored in a scalable and accessible environment, and the Data Cloud provides this capability, ensuring that data can be easily accessed for reporting, analytics, and further model improvement.
Custom objects or Salesforce Big Objects are not designed for the scale or the specific type of real- time, unified data processing required in such AI-driven interactions. Big Objects are more suited for archival data, whereas Data Cloud ensures more robust processing, segmentation, and analysis capabilities.
NEW QUESTION # 280
Universal Containers (UC) is setting up a new Agentforce Service Agent. The company has sensitive medical product research stored internally and wants to ensure the agent cannot access it. What should UC da?
Answer: C
Explanation:
The AgentForce Security and Access Control Best Practices Guide emphasizes the principle of least privilege, which means granting each agent only the permissions strictly necessary to perform its defined tasks.
To prevent unauthorized access to sensitive data such as medical research, administrators should exclude permissions for the Medical Product object and related records from the AgentForce Service Agent's permission set group. This approach ensures that even if the reasoning engine processes a related query, it cannot retrieve or expose data it lacks access to.
NEW QUESTION # 281
......
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