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| Section | Weight | Objectives |
|---|---|---|
| Development Lifecycle | 15% | - Testing agents in Testing Center - Deployment: sandbox to production - Version control and maintenance - Monitoring, adoption and optimization |
| Data Cloud for Agentforce | 20% | - Agentforce Data Library types - Unstructured data processing: chunking, indexing - Improving response accuracy with data grounding - Retrievers and search types: keyword, vector, hybrid |
| Prompt Engineering | 20% | - Prompt Builder usage and use cases - Grounding techniques and best practices - Prompt management and user roles - Prompt template creation: field generation, flex types |
| Multi-Agent Interoperability | 5% | - Agent-to-agent communication - Model Context Protocol (MCP) - Agent API usage scenarios |
| AI Agents | 35% | - Agent User security and permissions - Agent architecture and reasoning engine - Deterministic controls: filters and variables - Channel integration: digital experience, email, Slack - Agent types: Service, Sales, Employee - Topics and actions configuration |
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NEW QUESTION # 138
A Salesforce Administrator wants to generate personalized, targeted emails that incorporate customer interaction data. The admin wants to leverage large language models (LLMs) to write the emails, and wants to reuse templates for different products and customers. Which solution approach should the admin leverage?
Answer: A
Explanation:
To generate personalized emails using LLMs while reusing templates:
Sales Email Prompt Template Type (Option C): Designed specifically for generating dynamic email content by combining LLMs with structured templates. It allows admins to define placeholders (e.g., customer name, product details) and reuse templates across scenarios.
NEW QUESTION # 139
When is the Agent-to-Agent (A2A4) protocol an appropriate communication choice?
Answer: B
Explanation:
The Agent-to-Agent (A2A) protocol in AgentForce is specifically designed to facilitate collaboration and coordination between multiple agents. It allows distinct agents - such as Service, Sales, or Employee Agents - to exchange structured messages, delegate tasks, and share context securely within the Salesforce ecosystem.
AgentForce documentation describes A2A as a collaborative communication framework, enabling agents to "handoff, request, and respond" to each other in complex workflows. This is useful when different agents specialize in separate domains (e.g., one handles billing inquiries, another manages account upgrades).
NEW QUESTION # 140
Universal Containers wants to implement a customer verification process where sensitive account information can only be accessed after the customer passes identity verification. The agent must enforce this security rule deterministically without allowing the large language model (LLM) to bypass the verification requirement. What should an Agentforce Specialist recommend as the best solution?
Answer: B
Explanation:
The AgentForce Security and Deterministic Logic Guide specifies that sensitive actions must be gated through conditional filters linked to verification variables, not through natural language. It states: "For any process requiring secure, deterministic access, create a custom variable (e.g., IsCustomerVerified) that stores the verification status as a Boolean. Apply a filter expression to all protected actions (e.g., IsCustomerVerified = true). This ensures the LLM cannot bypass or alter access logic." This configuration ensures security and determinism because the execution of sensitive actions is programmatically enforced, not dependent on the LLM's understanding.
NEW QUESTION # 141
Universal Containers (UC) wants to improve the productivity of its sales team with generative AI technology. However, UC is concerned that public AI virtual assistants lack adequate company data to general useful responses. Which solution should UC consider?
Answer: A
Explanation:
Universal Containers (UC) wants to harness generative AI to boost sales productivity. They are wary of public AI virtual assistants (like generic chatbots) that lack sufficient UC-specific data to generate useful business responses.
NEW QUESTION # 142
Universal Containers needs to bring individual customer warranties from an external system into Data Cloud. They want Agentforce to return warranty-related responses only for accounts whose warranty status is active. Which search approach should the Agentforce Specialist configure to ensure warranty-related information is retrieved correctly?
Answer: A
Explanation:
The AgentForce Retrieval Configuration Guide outlines that when external data must be filtered by specific criteria-such as WarrantyStatus = Active-the correct approach is to use Hybrid Search with pre-filtering logic defined in a custom retriever. The documentation specifies: "Hybrid search allows combining keyword precision and semantic context. When used with a custom retriever, administrators can pre-filter data on metadata fields (e.g., WarrantyStatus) to ensure that only eligible records are returned."
NEW QUESTION # 143
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