2025-08-24 08:00:00
The tech world is having another moment. This time, everyone's convinced that Claude Code represents some kind of breakthrough in AI-assisted development. Twitter feeds are flooded with screenshots of terminal sessions, developers claiming they've found their new "coding partner," and hot takes about the death of traditional IDEs. The hype is real.
Having spent the past month actually using Claude Code alongside Cursor and other AI coding tools, I'm starting to think we're seeing something more interesting than the revolution everyone claims. The reality is messier, more human, and ultimately more promising than the hot takes suggest.
Claude Code's most striking feature isn't its intelligence—it's that it deliberately strips away everything we've spent decades building into our development environments. No syntax highlighting. No autocomplete. No visual git diffs. Just you, a terminal, and an AI that can read files and run bash commands.
This feels almost backwards in 2025. We've spent thirty years perfecting IDEs, creating rich visual experiences for code, building sophisticated debugging tools. And now the most talked-about AI coding tool is... a command-line app that could have run on Unix systems from the 1980s.
Yet there's something powerful in this simplicity. By limiting the interface, Claude Code forces a different kind of interaction. You can't mindlessly click through tabs or get distracted by a thousand features. The conversation becomes the main interface, and the code becomes secondary. This isn't necessarily better, but it's definitely different.
The Claude Code success story follows a familiar Silicon Valley narrative: small team builds something simple that "just works" while big companies are busy adding features nobody wants. The blogs explain how they chose "simplicity over complexity" and let the AI do the heavy lifting.
This story is appealing, but it hides a more complex reality. Claude Code doesn't "just work" any more than a junior developer "just works." It needs constant supervision, frequent corrections, and a deep understanding of when to step in and when to let it run. The difference is that it packages this complexity in a way that feels natural—conversational rather than technical.
The real innovation isn't the terminal interface or even the AI prompts (though both are well done). It's that Anthropic figured out how to make failure feel less frustrating. When Cursor's agent gets stuck trying the same broken fix over and over, it feels like a software bug. When Claude Code gets confused and starts going the wrong direction, it feels more like a conversation that needs guidance.
The most visible part of the Claude Code moment isn't the technology—it's the performance around it. Social media is full of time-lapse videos of terminals scrolling, productivity influencers sharing their "agent workflows," and elaborate setups for letting Claude Code work overnight.
This performance serves a need that goes beyond showing off the technology. In an industry obsessed with efficiency and automation, there's something deeply satisfying about giving work to an AI and watching it grind through tasks while you sleep. It's the ultimate programmer dream: writing code that writes code.
But the performance also reveals our worries. When developers post videos of their agents working, they're not just showing off—they're proving they're still relevant in an increasingly automated world. Look, they seem to say, I'm not being replaced by AI—I'm managing AI.
The secret of Claude Code is that using it well requires a particular kind of skill that the industry hasn't fully recognized. It's not enough to know how to code—you need to develop an intuitive sense of when the AI is likely to succeed, when it's about to go wrong, and how to structure problems in ways that play to its strengths.
This is a skill that comes from hundreds of hours of practice, countless failed experiments, and developing a mental model of what the AI can and can't do. It's closer to working with a talented but unpredictable junior developer than using a tool—you learn to read its patterns, understand its blind spots, and develop strategies for keeping it focused.
The problem is that this expertise is invisible in the final result. When someone shares a video of Claude Code successfully refactoring a complex codebase, you don't see the hours of failed attempts, the carefully prepared context, or the interventions that kept the agent on track.
Claude Code's philosophy—"choose the simplest option"—has become a mantra in the AI tools space. Every product blog now includes some version of "we could have built a complex system, but instead we chose simplicity."
This is probably the right approach technically, but it's worth understanding what gets lost. Traditional IDEs are complex for good reasons—they help you understand large codebases, navigate unfamiliar code, and maintain context across multiple files and projects.
Claude Code's simplicity works brilliantly for certain tasks: implementing well-defined features, fixing bugs with clear steps, or making systematic changes across a codebase. But it struggles with the exploratory work that defines much of real development—understanding how an unfamiliar system works, debugging complex interactions, or making architectural decisions that require broad context.
The simplicity is both Claude Code's greatest strength and its biggest limitation. It provides a focused environment for AI collaboration, but at the cost of all the tools we've developed for understanding complex systems.
The conventional wisdom is that Claude Code is competing with Cursor and other AI coding assistants. But I think the real competition is more fundamental: it's competing with the entire approach of modern software development.
Claude Code represents a bet that the future of programming looks more like natural language conversation and less like manipulating code in sophisticated visual environments. It's proposing that we can collapse the distance between intent and implementation to the point where traditional programming workflows become less necessary.
This isn't necessarily better—it's different and makes different trade-offs. But if the bet works, the implications go far beyond just how we interact with AI assistants. It suggests a future where programming becomes more accessible, where the barrier to creating software drops significantly, and where the line between "technical" and "non-technical" people becomes less clear.
Strip away the hype and performance theater, and Claude Code represents something more modest but more lasting: a different interface for human-AI collaboration in software development.
The terminal interface isn't revolutionary because it's simpler—it's interesting because it changes the rhythm of interaction. The conversation becomes more central, the code becomes more secondary, and the developer's role shifts from direct control to guided collaboration.
This isn't necessarily better than traditional development workflows, but it's different enough to reveal assumptions we didn't know we were making about how programming should work. It suggests possibilities for new kinds of tools, new ways of thinking about the relationship between human intent and machine capability, and new approaches to translating ideas into working software.
The real value of Claude Code might not be the specific tool itself, but the questions it raises about everything else. If this different way of working is possible, what other assumptions about software development are worth questioning? If natural language can work for complex technical tasks, what other interfaces might we be missing? If simplicity can compete with sophistication, what complexity in our current tools is actually unnecessary?
These are the questions worth exploring as the hype settles and we start to understand what this technology actually means for how we build software. The answers won't be as dramatic as the predictions suggest, but they'll probably be more interesting than the skeptics assume.
Progress, as always, happens quietly while everyone's arguing about the revolution.
2025-08-10 15:49:55
从 2019 年到现在，《捕蛇者说》 也走过了六个年头。我喜欢和有意思的人聊天，因此每次录制都让我非常享受。从热度上看，知识管理系列是无可争议的巅峰，也是我们唯一出圈的一次；有几期是则我个人很喜欢的，比如《Ep 08. 如何成为一名开源老司机》、《Ep 27. 聊聊焦虑》。
为什么专门写一篇博客？因为最近和 Hawstein 录的《Ep 56. 对话 Hawstein：从独立开发，到追寻人生的意义》，是六年来我最喜欢的一期。
六年前播客刚起步时，我还是一个入行不久的职场菜鸟，满心只想着怎么在业界站稳脚跟。六年后，工作于我已变成倦怠的日常，而对于人生的思考则在过去几年占据了我的脑海。《捕蛇者说》是一档以嘉宾访谈为主，围绕「编程、程序员、Python」展开的播客，我不打算改变它。然而，固定的形式和内容也成了一种限制，以至于我得去别的播客串台才能聊那些技术之外的想法和兴趣。结果就是，我脑中积压的想法越来越多，却无处表达。这听起来不可思议，但却是事实——我光是想写成文章的主题都积攒了一大堆，更何况那些零碎的思考。
所幸，Hawstein 的做客终于让我有了释放的渠道。之前在 Twitter 上约他上节目，一是感觉他表达欲望强烈，再有就是他回信里涉及的那些话题我也恰好都很感兴趣。不同以往，这次我们完全没有列提纲。然而我一点都不担心，因为我知道录出来的效果一定好——最后果然如此，甚至比我期待的更好。这里真的要感谢 Hawstein。可能这就是互相成就吧。
当然，本期因为没那么「技术」，几位老听众反馈说听不下去。这点我非常理解，并且在准备节目时就有心理准备。不过也有几位听众给予了非常积极的评价，还是令人开心的。不论怎样，我聊了我想聊的内容，也相信它给一些听众带去了启发和思考，已经无法奢求更多了。
本期的文字稿可以在这里找到。
2025-07-16 14:51:00
今年是我开始认真对待投资的一年。几个月的实践下来，不谈具体操作，我意识到自己的整体思路有一些问题。因此用这篇文章总结一下。
我主要的问题是太过追求找到高 beta 的标的，却忽视了那些领头羊公司。比如，我今年从未投资过 Nvidia 和 Palantir，甚至从未把它们放进观察列表。很不可思议吧。即便我知道这波反弹它们肯定会涨，但却始终不肯看它们一眼。几个月下来，它们涨得并不比那些动辄一天 10% 20% 的小票少，波动却小得多。我花很多时间看各种小票，最后反而因为判断错误没有很好地利用资金，经常直接就止损了。
往后，我打算这样分配资金：
60% 投入 3 - 4 家高确定性、高成长的领头羊公司，持仓数月 - 数年：
30% 投入 1 - 2 家短期内的热点题材，持仓数周：
10% 投入当前炒作的 1 支妖股，持仓数天（当前没有就不买）：
至于为什么不买标普500和纳斯达克100，因为 401k 里已经买了，所以主动投资就没必要重复。
这样分配的好处有几点：
当然，短期内美股已经太高，我目前不会上太大仓位。等之后有机会就开始实践。
2025-06-29 08:38:21
之后可能会在博客里写一些投资相关的文章。先从这篇开始，我想列举几个初入投资容易犯的错误，其中的坑我也踩过。
正如游戏里不会让你一上来就挑战最终 boss，初入投资最好不要挑战高难度市场。这里不得不提的就是A股，一个典型的地狱难度市场，具体可参考《为什么A股是价值投资者的坟墓？》。
我当然不是说投A股一定亏钱，或者投美股一定赚钱（少部分人在A股赚钱或许更容易）。关键在于，如果处在一个不正常的市场，你将无法通过反馈机制纠正错误并逐渐成长（关于「反馈」，我未来还会写文章）。比如，我看到不少人抱着赚钱致富的心态进入A股，很快便遭受打击退出了市场，并从此认定「投资都是骗钱的玩意，不投资就是最好的投资」。选错市场，会让人对投资这件事本身失去信心，而这是最可怕的一点。
这可能是新手最常犯的错误，包括我自己。
除了极少数天赋异禀的选手，基本上人们刚开始投资时都会亏钱，不论身处哪个市场。其中原理也很简单：大部分人开始投资，都是因为市场或者某个标的已经热到不能再热了。当身边的人都在赚钱却只有你被落下，你能不急吗？当年的牛顿就是这样：
结果呢？你入市的时候已经是牛市末期。很快，这支股票或者市场就崩盘了。
既然开始时亏钱是自然规律，与其违抗它，不如想办法减小损失。后面会说怎么做。
提到「投资交易」，有人会说不就是低买高卖吗？然而这种过度简化是有害的，因为它忽略了投资交易有的不同风格，且它们之间的差异极大，甚至完全相反。比如，我们最常听到的「价值投资」流派，要求投资者花费大量时间去彻底搞懂一家公司，而超短线日内交易往往不在乎基本面。你可以做多或者做空，左侧交易或者右侧交易，买入或者卖出各种期权；你可以买大盘、行业 ETF、个股，甚至加密货币，等等等等，不一而足。
在任意一个时间点，所有选项对投资者来说都是开放的。选项多固然好，却也让投资者陷入了选择困难症。同时，社交媒体上一会是这个人买A的期权翻了十倍，一会是这个人投资B五天翻倍。这些选项和声音会让新手们无比迷茫和焦虑，于是开始浏览大量的消息，生怕错过什么投资机会。看到好消息便马上买入，听闻负面消息便马上做空，要么就是跟单各种大V和「老师」。长此以往，不论赚钱与否，他们生活都将被市场裹挟，惶惶不可终日。
我很喜欢 Dawei 在《Ep 53. AI 能否帮我们做出更好的投资决策？ - 捕蛇者说》里的观点：「如果投资不能让我们的生活变得更好，那它就没有意义」。我认为，不让自己被市场裹挟的核心在于确立自己的交易风格。每种交易模式都有优缺点，但相同点在于都可以赚钱。这就和编程语言一样，你既不可能，也没有必要精通所有的编程语言。反之，你的上限取决于你最擅长的那种交易模式（编程语言）。人的时间是有限的，必须要减小决策的解空间。这样不仅可以提高决策效率，更可以专注于精进特定的交易模式。
这个问题没有标准答案，但我想给点框架性的建议。
Step 1. 假设你手头有 10w 块钱想投资。你要做的第一件事，就是把这部分钱除以十，也就是拿出一万去投资，把剩下的九万放在银行里。这样即便你亏了一半，也就是五千块而已，并不伤筋动骨。
Step 2. 花费三到六个月，随心所欲且尽可能多地尝试各种投资方法。这里的关注点不在于每种方法是否能赚钱，而在于仔细体察自己对于每种操作的感受，如有需要可以记录下来。举几个例子：
这样，你将建立一个量表，去量化自己对每一种投资方式的适应程度。而适应程度，决定了你未来应该采取的投资方式。只有当投资方式符合自己性格的时候，你才真正有可能把它执行好。相信我，没有人在实践之前真正了解自己。你自以为的了解，多半是幻觉。
Step 3. 当你找到了自己最舒服的 1-2 种投资模式，把它们固定下来，在往后的若干年里不再考虑其它的投资方式。同时，找到讲解这种特定投资模式的书，研读它们。就这样开始吧。重复地练习加上前人的经验，一定会让你进步飞快。
我自己也是新手，还在学习的路上，本文也算是阶段性总结，希望对你有帮助。限于篇幅，很多地方只能点到为止，之后想到了再展开写。
2025-03-17 08:47:14
不少动漫里都有主角团去海边这种老掉牙的桥段，而漫画家常借人物之口说出此行的目的是“创造美好回忆”。这里有意思的点在于，相对于参与海边之行和学园祭带来的快乐，漫画家们强调的却是“回忆”，这种在事后看才有价值的东西。由于中日间的文化差异，中国人对“创造回忆”这个概念并不熟悉。也有可能是“玫瑰色”的日本高中生活实在是太过美好，反衬出成为社畜之后的苦逼；而在中国，即便进入社会再怎么苦，恐怕都比不上高中时期。
我自认为非常幸运，可以在学生时期留下了一些美好的片段。进入社会之后，在我内心充满失落、煎熬和焦虑的时刻，我发现能带给我最大慰藉和力量的总是那些过往的美好回忆。这让我逐渐意识到回忆的力量，也开始理解为什么漫画里总强调“创造回忆”而不是“创造体验”——体验转瞬即逝，而回忆则随着时间的陈酿愈发珍贵。我相信一个人美好的回忆（尤其是青少年时期）越多，他的精神内核也就越稳定。令人遗憾的是，不幸的家庭和青少年经历同样将伴随人的一生，它不仅让人无法从过往汲取力量，更会带来持久的伤痛。
《DIE WITH ZERO》这本书提倡在死前花完你所有的钱。为了解释花钱的目的，作者自创了一个概念叫『记忆股息（Memory Dividend）』。这个概念让我醍醐灌顶，因为它准确而优美地阐述了我之前脑中模糊的感觉。下面我将会做个简单介绍。
首先，作者提到你可以把人生体验数值化。简单来说，就是给自己从体验中感受到的快乐打分。这样积累下来，就会有一个每年的分数。每个人对同一件事的感受大不相同，因此这个分数是完全主观的。
然后便可以引入『记忆股息』概念。股息是给股东定期派发的分红，即便股价不变，股息也能帮你积累财富。作者认为记忆带来的满足感亦是如此——已经获得的快乐记忆，将随着时间推移持续带给你满足感。经过的时间越久，这些积累起来的满足感也就越大。因此可以知道，即便是同样的体验，越早获得收益也就越大。
作者还提到你应该选择自己要去经历的体验，这点我也非常赞同。以我个人为例，“创造”带来的快乐无与伦比，而买奢侈品则微乎其微，因此我会希望最大化创造的体验。然而另一方面，我们虽看似有选择的自由，却往往沿着某种规划好的轨道，依靠惯性在生活。我们都说“身不由己”，现在先攒钱，等退休了再享受。然而根据记忆股息理论，等退休了再去获得美好回忆，即便可以做到，留给你积累股息的时间也已所剩不多。说到底，在人生的最后，你拥有的只有回忆，是它决定了你对这一生是否满意。
有句话叫『人生就是所有体验的总和』，记忆股息也无非是这句话的另一种表述。我听过一个有趣的理论：为什么世间诞生了生命和意识，因为造物主（根据你的信仰它可以是不同的东西，也可以就是宇宙本身）希望以不同的身份去经历和体验一切事物。我喜欢这个理论，不是因为它有多科学，而是因为它很浪漫。以及，万一真是如此呢？
最后再推荐一期播客《你一生的财富 - 知行小酒馆》。我想，体验也应该被纳入人生的财富列表，甚至应该排行首位——因为健康、金钱、社交等等，说到底不都是为了获得更好的人生体验吗？
