写作方法2022every.to编辑精选
James Clear 如何撰写他的下一本书（2021）
How James Clear is writing his next book (2021)
导读
这篇讲的是 James Clear 如何为下一本书做长期准备：他让一个核心概念长期占据头脑，持续收集素材，再设法把多年零散的笔记整理成有结构的一本书。评论区进一步聊到他的写法为什么有效：观点不算新，但更实用，并且用真实故事来支撑每一章。对写作者来说，这篇值得读的地方在于「素材如何积累、结构如何生成」，而不是「如何成为畅销书」。
可以直接用的写作要点
- 01
先确定一个能长期盘踞脑后的核心概念，把它当作过滤器，让日常经历和阅读都自动为它收集素材。
- 02
不要等素材攒完再想结构：可以按「哪个概念必须先讲清楚」给旧笔记排序，排列顺序就会自然显出章节骨架。
- 03
讲方法时用真实人物和案例把观点支撑起来，而不是罗列理论和研究，可读性来自故事。
- 04
用一个贴切的具体类比（如英国自行车队的边际收益）代替抽象论证，哪怕读者不认同，也会先停下来重新想一遍。
HN 评论精选
观点不新也能写好，差别在于实用性，以及用真实故事支撑每一章。
这本书出版已经四年，真快。刚出时我读了，觉得改变人生；后来读别的习惯类书才发现观点大同小异，只是他写得比学术书更实用。我又去读19世纪末20世纪初的老自助书，发现格式也很像（比如 Orson Swett Marden）：围绕真实生活里的成功故事来组织章节，用故事把观点讲得有说服力。他是很好的写作者，希望「第一畅销书作者」这个身份不会妨碍他继续写书，也希望他跳出「习惯那个人」的人设，他还有更多好素材可写。
thenerdhead查看英文原文
It's crazy to think it has already been 4 years since he released this book. I read it when it first came out and thought it was life-changing. Then I started to read other habit books and realized the ideas are the same, just his writing was more practical than academics. I then started to read old self-help from the 1800s/1900s and realized the format was pretty similar(think Orson Swett Marden) of chapters related around real-life stories of success to drive the points home. I'm excited to see what he comes up with next. He's a great writer. I hope the dilemma of being a #1 NYT best seller doesn't prevent him from continuing to author books regardless of how good they are. In other words, I hope he breaks out of the "habits guy" persona as he has much more great material to write books about.
把旧素材当零件，按「概念必须先于哪个概念」排序，让长期积累变成有结构的长文。
我写了个很粗糙的 Python 脚本：（1）找出星号之间的词或短语，作为待定义的术语；（2）找出依赖关系，即哪些词应该先被定义；（3）生成段落之间的关系图，再做最小生成树和拓扑排序。计划是拿五年左右、对新读者几乎读不懂的博客素材，产出一份排序合理的文本。
prionassembly查看英文原文
I wrote a Python script (it's so shoddy and easy to recreate I won't even share) that will (1) look for definitions as words/expressions between asterisks (2) look for dependencies (words that should be defined beforehand) and (3) produce paragraph-paragraph graph -> minimum spanning tree -> toposort. The plan is to take five-ish years of blog material that's nearly unreadable to people who haven't followed it from the beginning and produce ordered text.
足够大的核心概念会反过来筛选你的观察，写作就是持续为它采集素材。
「当一个大概念盘踞在你脑后，它就成了过滤器，你经历的一切都要从它上面过」——这话太对了，有时甚至觉得是概念占有了你，而不是你占有了概念。它接收你的人生经验，好让自己进入现实世界；它定义了你对信号与噪音的判断，不停在现实中采样可能帮助它成形的模式。有时因为先天倾向，概念的一部分已经固定在脑中，你永远体验不到没有它驱动的生活。它编排你的梦，用比你最清晰的记忆还真实的景象冲击你，塑造你的性格。自认为是「概念整合者」的人，别让概念虐待你：它们不属于我们的世界，也不在乎人类经验的全貌。
Lwepz查看英文原文
>When you have a big concept in the back of your mind, it becomes a filter that everything you experience runs through This is so true, to the point where sometimes you feel possessed by the concept and not the other way around. The concept harvests your human experience to make its way into the real world. It defines your notion of signal and noise, it restlessly samples patterns in the real world that might help its incarnation. Sometimes due to predisposition, part of the concept is hardware implemented which means you never really get to experience what it's like to live without this concept driving your life. The concept carefully arranges your dreams, strikes you with overwhelming visions that feel more real that your clearest memories and skilfully crafts your personality. For those who feel as though they are concept integrators, do not allow concepts to mistreat you. They don't belong to our world, they don't care about the totality of human experience, they operate on timescales far greater than that of our precious lives and our civilisation as a whole is still far too primitive to bear their throughput.
一个贴切的具体类比能让人停下来重新思考，即使对方不认同。
他的一篇文章曾在一场关于代码库的争论中帮了我。公司分两派：一派认为该选更快的写法（比如用 for 循环代替 forEach 链式调用），另一派认为这只是微观优化。代码库巨大，应用慢到快不能用。我用了《原子习惯》里 Dave Brailsford 与英国自行车队的类比：边际收益不断累积，能在宏观层面带来巨大变化。一个没优化的函数也许影响不大，但百万行的代码库里成千上万个就一定有影响。同事说不确定自行车队的类比能否迁移到编程，但我看得出他至少停下来想了想。当然慢的原因很多，肯定有更大的问题，但我仍认为尽量选更高效的写法有帮助。
rcarr查看英文原文
One of his articles helped me in a debate about a codebase once. There were two camps at the company. One camp believed that we should be looking to optimise the code we wrote by choosing faster options such as for loops over slower chain functions such as forEach (application was written in Typescript, I don't know if this is the case for all languages). The other camp classified these kinds of changes as micro optimisations. I belonged to the former. The code base was huge and the application was slow bordering on unusable. I used the Dave Brailsford British Cycling analogy from Atomic Habits that the aggregation of marginal gains can result in big changes on the macro level. Or put in other words, one non-optimised function might not make much of a difference but lots of them in a massive code base with millions of lines most certainly does. My co-worker's response was that he was not sure that the analogy from cycling transferred over to coding but I could tell that it was at least giving him pause for thought. In reality, there were many reasons for how slow that codebase was. There were most certainly bigger fish, but I still believe that choosing more optimal language options where possible would have helped.
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