ai-app-performance-optimization

To build successful AI applications, move beyond the "ideal crisis" of chasing every new research paper or model update. Real performance gains come from traditional product engineering applied to AI: data quality, workflow optimization, and user-centric evaluation.

The Optimization Pivot Differentiate between activities that offer marginal gains (The Hype) and those that drive exponential product quality (The Reality).

Optimize Data for Retrieval (RAG) If using Retrieval-Augmented Generation (RAG), the biggest lever for quality is not the retrieval algorithm, but how the data is prepared.

将焦点从人工智能炒作（最新模型、矢量数据库、代理框架）转移到真正提高产品质量的高杠杆活动。当人工智能功能表现不佳、团队陷入“研究循环”或规划新人工智能应用的路线图时，请使用此功能。 来源：samarv/shanon。