📄 中文摘要
许多待办事项并不是因为团队缺乏创意而失败，而是因为优先级排序停止了功能评分。RICE（覆盖面、影响力、信心、努力）是一个良好的起点，它迫使团队量化假设并客观比较工作。然而，在 AI 驱动的产品中，仅仅评分功能是不够的，因为设计的是学习系统而不仅仅是功能。AI 产品领导力框架在此发挥作用，优先级的定义也随之改变，必须评估是否能改善数据飞轮、增强模型性能和创造专有智能。
从 RICE 到 AI 系统：现代产品领导力的构建者指南
📄 English Summary
From RICE to AI Systems: A Builder's Guide to Modern Product Leadership
Most backlogs fail not due to a lack of ideas, but because prioritization halts feature scoring. RICE (Reach, Impact, Confidence, Effort) serves as a solid starting point, compelling teams to quantify assumptions and compare work objectively. However, in AI-driven products, merely scoring features is insufficient, as the focus shifts from shipping functionality to designing learning systems. This is where the AI Product Leadership Framework comes into play, redefining what 'priority' means. Evaluation must consider whether the feature improves data flywheels, strengthens model performance over time, and creates proprietary intelligence.