In the AgentForce Flex Prompt Design Guide, the recommended best practice for Flex prompt templates is to ensure that the large language model (LLM) is provided with clear contextual information and a defined role (e.g., sales rep, support agent, concierge). Flex prompts are intentionally open-ended and adaptable, enabling them to handle dynamic and conversational use cases, provided they are guided with sufficient context and role clarity.
By setting a role and including detailed contextual cues, the LLM can tailor tone, content, and reasoning appropriately while maintaining response accuracy.
Option B describes a data-grounded Record Summary use case, not a Flex prompt. Option C, involving retrievers, is for grounding responses to external or indexed data — but Flex prompts typically handle free-form or reasoning-driven tasks, not retrieval-based ones.
Thus, following AgentForce’s official design standards, the correct best practice is Option A – Provide contextual information and assign a role to the LLM for optimal performance and consistency.
[Reference: AgentForce Flex Prompt Development Guide — “Designing Context-Rich and Role-Aware Flex Prompts.”, , , ]
