[‘胶水工作’的实际作用并没有那么大，因为人本身并不能持续地创造下去，对一个==大团队==，保持低效率的运行并不是一件坏事]( Glue work considered harmful
https://www.seangoedecke.com/glue-work-considered-harmful/)

坚毅是比智商更重要的天赋

有好些年都过得不太容易，但我没有放弃。我就是一直往前走，一直敦促自己。最重要的是好奇心，它让数学成了我生命里不可或缺的一部分 —张益唐（好奇心的重要性）

最近有一项研究，科学家让参与者完全依靠 AI 来写论文，结果83％的人在写完后不久，无法引用自己论文中的任何内容。即使稍后让这些人重新独立写作论文，他们也会表现出大脑神经活动减少和无法完全投入思考，总是习惯性寻求 AI 的帮助。研究人员创造出了”认知债务”这个词来描述这种现象：AI 确实带来了便利，但代价是牺牲我们的思考能力。机器借给你脑力，你需要付出利息—-你自身的思维能力。我的建议是，明智地使用 AI，不要让它帮你解数学方程式，而要让它查看你的答案，来解释你可能错在哪里。你的原则是坚持独立思考，在这个基础上再加入 AI。思考可能会让你觉得很累、不舒服，但它是你大脑的训练场，不适感让你的思考变得更强大

当领导者优先考虑扩大自身职权和影响力，而非培养团队时，就会形成吸引同类利己主义领导者的真空。结果不可避免：形成层层政治割据，这些割据不重视成果层面的胜利，也不关心他们的员工最好的问题就是那些人人回避、直到无法忽视的问题

The unexamined life is not worth living（未经审视的人生不值得度过）

The quick thinker handles in-the-moment action well, but is so wrapped up in the “now” that it’s difficult for them to get too deep on a topic. The slow thinker meditates on ideas for a while, carefully chooses (almost always the correct) path, and steadies the course. Prick and pull at this one for a quick thought, and it comes out flatter than you could imagine思维敏捷者擅长即时应对，但过于沉浸”当下”使其难以深入思考议题。思维缜密者会长时间酝酿观点，谨慎选择（几乎总是正确的）路径并稳扎稳打。若试图催促后者快速输出想法，得到的反馈会比想象中更为平淡。

It also takes me longer to understand things and it takes me longer to get to delivery than many of my peers. However, I have consistently noticed that the quickness comes at the price of a shallow understanding, and the delivery is also often lacking in those who move fast. For me, I have to really grok the thing I’m focussing on. I have to internalise it somehow and build a mental model. Once I’ve done that I am actually faster and more productive than the ones who leap on things quicker.

专注和深度思考比敏捷更重要

That doesn’t mean “nothing to see here, move on.” It means that AI isn’t the bow-wave of “impending superintelligence.” Nor is it going to deliver “humanlike intelligence.” It’s a grab-bag of useful (sometimes very useful) tools that can sometimes make workers’ lives better, when workers get to decide how and when they’re used. 这并非意味着“此处无事发生，请继续前行”。而是指人工智能并非“即将到来的超级智能”的浪潮前兆，也无法实现“类人智能”。这是一系列实用（有时非常实用）的工具，当工人能够决定如何使用及何时使用它们时，这些工具有时能让工人的生活变得更好。

Discouraging people from trying is a good filter for these fields, since the only people who will ignore such advice is people who really deeply love it or are really driven. Those are the people most likely to ascend to the top 20%. Nobody gets that good at something they aren’t driven to do.劝阻人们尝试是这些领域的一个良好筛选机制，因为只有那些真正深爱此事或极具内驱力的人才会无视这类建议。这些人最有可能跻身前 20%——若缺乏内在驱动力，无人能在某个领域达到如此卓越的境界