Computing Life

观察到当代码成本趋近于零时，为一次性决策构建专用工具反而是最优策略。提出AI Native的本质是在信息获取成本坍塌后采用全新策略——从直觉驱动转向高分辨率的数据驱动决策。

Observes that when code cost approaches zero, building disposable tools for one-off decisions becomes optimal. Argues AI Native means adopting new strategies enabled by collapsed information costs—shifting from intuition-driven to high-resolution, data-driven decisions.

AI"偷懒"的本质是LLM输出长度限制导致的注意力分散。Wide Research通过多轻量模型并行处理子任务、主LLM汇总的方式解决，分享为Codex构建该能力的设计思路。

Why AI slacks off on large tasks: LLM output length limitations cause attention drift. Wide Research solves this by parallelizing with lightweight models, then aggregating results with a primary LLM.

记录在API因合规问题被拒后，使用视觉大模型从截图提取财务数据，实现十年手动记账流程的自动化。展示了本地模型、交叉验证和人机协作工作流如何安全处理敏感金融数据。