Short writing on research systems, AI agents, and technical work.
从中美社会共享的优绩主义想象出发，讨论成功、聪明与人生意义如何被捆绑，又如何在上升停滞和 AI 到来后重新松动。
Starting from the meritocratic ideals shared by China and the United States, this essay examines how success, intelligence, and meaning became intertwined—and how stalled mobility and AI are pulling them apart.
回顾从 2023 年开始使用 LLM 时坚持的四个原则：不微调、不用 RAG、不做 constrained decoding、不把 temperature 设为 0，以及它们如何逐渐汇成我的 agent 方法论。
A look back at four principles I followed when I began working with LLMs in 2023—no fine-tuning, no RAG, no constrained decoding, and no temperature 0—and how they grew into my approach to agents.
（内容为戏仿作品）
围绕 P 与 NP 问题，本文提出一种基于 benchmark saturation 的“经验性证明”叙事：用大规模 3-SAT 基准、模型准确率和 scaling law 外推来宣称数学结论。
(Parody work)
A paper-style narrative around P versus NP that proposes an empirical proof via benchmark saturation, using a large 3-SAT benchmark, model accuracy, and scaling-law extrapolation to announce a mathematical conclusion.
从工作中的“对齐”经验出发，讨论人在 AI agent 时代的主体性：人和 agent 的区别不只是能力，而是信念、历史、责任，以及是否需要为自己的判断辩护。
A reflection on subjectivity in the age of AI agents: humans differ from agents not only by capability, but by belief, history, responsibility, and the need to stand behind their own judgments.