An engineering notebook on AI, systems, and everyday experiments.

以航海为喻，指出当AI成为蒸汽机后，技术人应从划桨手进化为领航员或轮机长——前者决定方向，后者驾驭引擎。关键不是与机器竞争，而是选择新的角色定位。

Uses the ship metaphor to argue that as AI becomes the engine, tech professionals must evolve from paddlers to Navigators (defining direction) or Chief Engineers (optimizing execution). The key is choosing your role, not competing with machines.

用"笨数据+笨方法+笨模型=精知识"的方法论，将千万字小说转化为可交互查询的知识图谱，介绍线性扫描、语义检索和知识飞轮迭代的技术细节。

Describes building an interactive knowledge graph from a massive Chinese fantasy novel using AI, with a methodology of "dumb data + dumb methods + dumb models = refined knowledge" through iterative refinement.

闭环学习强调持续反馈与调整而非一次成功，持续校准方向的能力比初始瞄准的精度更为重要。

Closed-loop learning emphasizes continuous feedback and adjustment over one-shot perfection—the ability to calibrate direction matters more than initial aim.

对比尊界S800与迈巴赫的品牌策略：清单式技术对标vs体验驱动型叙事，科技参数堆砌vs从容克制的品牌调性，探讨技术豪华与故事豪华的不同路径。

Comparing Zunjie S800's tech-focused marketing with Maybach's experience-driven branding - checklist-driven features vs. cultivated prestige, and what this reveals about different paths to defining luxury.

分析为什么模型越来越强但用户感受不到：App设计滞后于模型能力。对比Claude、Gemini和ChatGPT的产品体验，发现OpenAI是唯一同等重视产品设计和模型能力的公司。

Analyzes why users don't feel AI getting smarter despite model advances: apps lag behind capabilities. Compares Claude, Gemini, and ChatGPT products, finding OpenAI the only company equally prioritizing product design and model capability.