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

通过模拟购车场景实测OpenAI Deep Research，展示其如何大幅提升调研效率、解放脑力进行更深层思考，以及重新定义问题边界的认知炼金能力。

A hands-on exploration of OpenAI Deep Research through a simulated car-buying scenario, demonstrating how AI elevates research efficiency and enables deeper strategic thinking about negotiation and decision-making.

不要从AutoGen、LangGraph等框架入手学习Agentic AI——它们会锁定你的世界观。在领域快速演变期，应该从第一性原理出发自己构建。

Don't start Agentic AI with frameworks like AutoGen or LangGraph—they lock you into a worldview. Build from first principles while the field is still evolving rapidly.

对比GPT-4o和o1评测DeepSeek r1，发现其在指令遵循和思维深度上不及第一梯队，但在中文表达和创意写作方面展现出独特优势。

A critical review of DeepSeek r1 comparing it to GPT-4o and o1, finding it lacking in instruction following and reasoning depth, but exceptional in Chinese language mastery and creative writing.

用医院的分诊系统作比喻，通俗解释DeepSeek v2和v3的混合专家架构原理，包括专家分工、路由机制、负载均衡挑战和跨节点通信问题。

Explains DeepSeek v2 and v3's Mixture of Experts architecture using a hospital analogy, covering expert specialization, routing, load balancing challenges, and cross-node communication.

以一次debug经历说明三个AI管理技巧：克制抢键盘的冲动、提供可视化上下文而非模糊抱怨、授之以渔而非授之以鱼——即从IC到Manager的思维蜕变。

Uses a debugging session to illustrate three key AI management skills: resisting the urge to take over, providing visual context instead of vague complaints, and teaching methodology rather than giving answers—the shift from IC to manager mindset.