LLM的默认输出是consensus：正确但平庸。Deep Research其实是Wide Research。我们找到了一种系统性方法，用个人认知上下文把LLM从consensus里强行扯出来。一年实验，有控制变量证据。
Why AI Only Gives You Correct Nonsense, and How to Push It Out of Its Comfort Zone
An LLM's default output is consensus: correct but mediocre. Deep Research is really Wide Research. We found a systematic way to pull LLMs out of consensus using personal cognitive context. One year of experimentation, with controlled evidence.
用好AI的第一步：停止和AI聊天
会用AI和用好AI之间差的是10倍。这个差距的根源在于工作方式，而非模型。本文通过一个完整的工作流例子和上中下三策的框架，解释为什么应该从ChatGPT切换到Cursor这类Agentic工具。
Step One to Using AI Well: Stop Chatting with AI
The gap between using AI and using AI well is 10x. That gap comes from how you work, not which model you use. This post walks through a complete workflow example and a Three Tiers framework to explain why you should switch from ChatGPT to agentic tools like Cursor.
以一个简单任务为例看AI落地的关键决策
用两分钟指挥AI给300篇文章添加SEO summary的实战案例，拆解五个关键决策：选对执行环境、先建测试再干活、让agent自己处理corner case、divide and conquer、结果导向的prompt写法。