88 min 2026-02
Head of Claude Code: What happens after coding is solved | Boris Cherny
概要
Claude Code负责人Boris Cherny讲述从终端原型到占GitHub 4% commit的增长故事，以及coding solved后的agent化方向
核心洞察
- Claude Code 从一个内部获得 2 个赞的终端 hack 成长为全球软件工程的基础设施：Semi Analysis 报告显示，GitHub 上 4% 的 commit 由 Claude Code 生成（私有仓库比例更高），预计年底达到 20%。Boris 自 2024 年 11 月起未手动编辑过一行代码，每天提交 10-30 个 PR，而 Anthropic 工程团队规模扩大约 4 倍的同时，人均生产力提升了 200%。
- "编程已基本被解决"，下一个前沿是 AI 自主发现要做什么：Claude 已经开始从用户反馈、bug 报告和遥测数据中主动提出修复建议和功能创意，Boris 认为编程本身已是"solved problem"，软件工程师的头衔将在年底开始被"builder"取代。
- Latent demand 是 Boris 眼中最重要的产品原则：从 Facebook Marketplace（40% 群组帖子是买卖）到 Claude Code 被非技术用户用来种番茄、分析基因组，再到数据科学家 Brendan 自学终端使用 Claude Code 做 SQL 分析，每一次"产品被滥用"都指向了下一个爆款——Co-work 正是这样诞生的。
- Co-work 由团队用 Claude Code 在 10 天内构建（含完整 VM 安全沙箱），发布即爆款：对比 Claude Code 早期的慢热，Co-work 上线后迅速被百万级用户采用；Anthropic 一位 PM 用 Lenny 发布的 50 个非技术用例作为 eval，48/50 通过后才决定发布。
- Anthropic 的安全架构分三层——机制可解释性、评估、真实世界部署——这是 Boris 选择留在 Anthropic 而非 Cursor 的根本原因：他加入 Cursor 两周后因缺少使命感而回归，认为"无论工作多 exciting，都不能替代 mission"。
加入 Cursor 两周后回归：Mission 不可替代
核心要点：Boris 经历了职业生涯中最快的一次换工作——加入 Cursor 两周后回到 Anthropic，因为意识到产品的兴奋感无法替代使命感。
Boris 是 Cursor 产品的忠实用户，也被团队打动——他至今仍认为 Cursor 团队"awesome"，在 AI 编程方向的判断力领先于很多人。但到了 Cursor 之后，他几乎立刻意识到自己真正缺少的是 Anthropic 的使命。他最初加入 Anthropic 就是被安全使命吸引的：在大厂工作后，他想去一家实验室"帮助塑造这个疯狂的东西的未来"。在 Anthropic，随便在走廊上拦一个人问"你为什么在这里"，答案永远是"safety"。
"Whatever the work might be, no matter how exciting, even if it's building a really cool product, it's just not really a substitute for that." —— Boris Cherny
Boris 说这是他"最快的一次换工作"（the fastest job change I've ever had），Lenny 也表示从未听过这个故事的完整版本。
Claude Code 起源：从"没人看好的终端 hack"到改变软件工程
核心要点：Claude Code 的诞生是务实选择与产品直觉的结合——选终端是因为只有一个人所以"最简单"，而"内部发布获 2 个赞"恰恰是一个重要的产品教训：早期要刻意 underresource。
Boris 加入 Anthropic 后，先花一个月做各种奇怪的原型（大部分没发布），再花一个月做后训练以理解模型——他认为"要做好上层工作，就必须理解下面一层"。之后他开始原型开发，最初叫 QuadCLI。
"我在听什么歌"的顿悟时刻：Boris 给模型一个 bash 工具，没有任何指令说明用途。他问模型"我在听什么歌"——模型自己想出了如何用 bash 工具来回答这个问题。Boris 自己都不确定模型能不能回答，但模型做到了。这个瞬间让他意识到模型存在 latent demand——它"想要"做的事情远超设计者的预想。
他把这个原型发布到内部，获得了两个赞。没人觉得终端产品能行——大家想到编程工具就想到 IDE 和复杂环境，没人认为这东西能基于终端。但终端形态其实是务实选择：头几个月只有 Boris 一个人，终端是最简单的构建方式。
"No one thought that this thing could be terminal-based. That wasn't really the intention, but for the first couple months it was just me, so it was just the easiest way to build." —— Boris Cherny
后来团队考虑过其他形态，但决定继续坚持终端——因为模型进步太快，他们觉得没有其他形态能跟上。2025 年 2 月外部发布后，Claude Code 并没有立刻成为爆款，早期用户需要时间理解这个"有点奇怪"的产品。真正的拐点来自 Opus 4——Anthropic 第一个 ASL-3 级模型发布后，增长曲线开始指数级上升，此后一直在加速。Ben Man 在很早期就催促 Boris 做 DAU 图表，Boris 还觉得太早了，但图表"几乎立刻就垂直上升了"。
100% AI 写代码：从预测到现实
核心要点：Boris 在 2025 年 5 月预测"年底可能不再需要 IDE"时，全场倒吸一口气——但他只是在"描线"（trace the line），而 Anthropic 的 DNA 就是指数思维。
Boris 自 2024 年 11 月起未手动编辑过一行代码，每天提交 10-30 个 PR，录制本期播客时同时运行着 5 个 agent。但这个过程是渐进的：2025 年 2 月 Claude Code 只写他 20% 的代码，5 月约 30%（他大部分代码仍用 Cursor 写），直到 11 月才跨过 100%。
- Anthropic 三位联合创始人是 scaling laws 论文的前三位作者，指数思维"深入 DNA"
- Spotify 最近宣布其最优秀的开发者自 12 月以来没有手写过一行代码
- Semi Analysis 数据只统计公开 commit，私有仓库比例"相当高于"4%
- 有些工程师甚至已经不看代码了——Boris 认为目前还需要人工检查正确性和安全性，Anthropic 也让 Claude 自动 review 100% 的 PR，但之后仍有人工复核层
"I have never enjoyed coding as much as I do today because I don't have to deal with all the minutia." —— Boris Cherny
新人用 Claude 修 memory leak 比 Boris 快——AGI-forward 思维方式的冲击
核心要点：模型进步太快，即使长期使用者也会被旧思维困住；新工程师反而因为没有"旧包袱"而更高效。
几个月前 Claude Code 出现内存泄漏。Boris 按传统方式处理：取 heap snapshot，打开专用 debugger，逐行分析 trace。团队里一位较新的工程师则直接对 Claude Code 说："Hey Claude, it seems like there's a leak. Can you figure it out?" Claude Code 做了和 Boris 完全相同的事——取 heap snapshot——然后自己写了一个即时分析工具（just-in-time program），用它分析了 snapshot，找到了问题，提交了 PR，整个过程比 Boris 手动操作还快。
Boris 由此总结：长期使用模型的人反而容易停留在"旧模型的心智"里（"it's not Sonnet 3.5 anymore"），需要不断将自己拉回当下。新人和新毕业生反而用更 AGI-forward 的方式工作。
团队原则：Underfunding、速度、无限 Token
核心要点：刻意少配人不是为了省钱，而是为了逼出 AI-native 的工作方式；给工程师无限 token 不是因为 Anthropic 卖 token，而是因为创新需要试错自由。
- 刻意少配人（underfund）：有时一个项目只放一个工程师。当资源紧张时，工程师被迫让 Claude 做更多工作，反而产出更好。Boris 对 CTO 们的建议是：不要一开始就优化成本，先给工程师尽可能多的 token
- 速度至上：如果一件事今天能做，就今天做。早期 Claude Code 只有 Boris 一个人，唯一的优势就是速度——这至今仍是团队原则
- 无限 token 作为福利：Anthropic 已有工程师月消耗数十万美元的 token。Boris 认为个人实验阶段 token 成本相对薪资很低，等想法验证成功再优化（比如用 Haiku 或 Sonnet 替代 Opus），不要过早省钱
- Lenny 调侃"当然你说这话，你在 Anthropic 工作"，Boris 回应说小规模实验的 token 成本确实远低于工程师薪资
"Don't try to optimize. Don't try to cost cut at the beginning. Start by just giving engineers as many tokens as possible." —— Boris Cherny
Latent Demand：从 Facebook Marketplace 到 Co-work 的产品发现法
核心要点：当用户"滥用"你的产品去做它本来不该做的事时，这就是最强的产品信号——Co-work 正是从"有人在终端里种番茄"这类现象中诞生的。
Facebook Marketplace 案例：Marketplace 团队创始经理 Fiona 发现，2016 年前后 Facebook 群组中 40% 的帖子是买卖东西——没人设计这个功能，用户自己 hack 出来的。结论显而易见：为买卖专门做个产品，一定会成功。Facebook Dating 也类似：60% 的个人主页浏览来自异性非好友——用户在"偷看"彼此。
Brendan 数据科学家终端故事：大约 2025 年 5 月，Boris 走进办公室，看到数据科学家 Brendan 的电脑上居然开着终端——Boris 震惊了："Brendan，你怎么会打开终端？"（终端是工程师的工具，很多工程师自己都不想用。）Brendan 不仅打开了终端，还自己下载了 Node.js 和 Claude Code，正在终端里做 SQL 分析。第二周，所有数据科学家都在做同样的事。
其他"滥用"案例：有人用 Claude Code 种番茄、分析自己的基因组、从损坏硬盘中恢复婚纱照、分析 MRI 影像。Boris 看到这些非技术用户"跳过重重障碍去用一个终端产品"，意识到应该为他们做一个专门的产品——这就是 Co-work 的起源。
Boris 还提出了 latent demand 的"第二维度"：不只看用户想做什么，还要看模型想做什么。Claude Code 的设计哲学是"产品就是模型本身"——给模型最少的脚手架、最少的工具，让它自己决定用什么工具、按什么顺序用。研究中叫"on distribution"，产品中叫 latent demand，是同一个概念。
Co-work：10 天构建，发布即爆款
核心要点：团队探索了好几个月各种方案，最终有人说"把 Claude Code 放进桌面 app 不就行了"——10 天用 Claude Code 自身完成全部实现，包括完整的 VM 安全沙箱。
Claude Code 外部发布后经历了慢热期，用了好几个月人们才理解这个产品是什么。Co-work 则完全不同——上线后立刻被百万级用户采用，增长远快于 Claude Code 早期。
Boris 把功劳归于团队（Felix、Sam、Jenny 等人），但核心推动力仍是 latent demand：团队看到人们在用 Claude Code 做非技术任务，花了几个月探索各种方向，最终有人提出最简单的方案——把 Claude Code 放进桌面应用。10 天内完成全部实现，包括一个完整的虚拟机安全系统以确保模型不会"跑偏"，所有代码由 Claude Code 编写。产品以"research preview"形态提前发布，因为一方面需要用户反馈来改进产品，另一方面需要在真实世界中研究安全性。
"我成了 eval"：Lenny 曾发过一个帖子列出 50 个非技术用例。Anthropic 一位 PM 用这个帖子作为 Co-work 的评估标准——当 Co-work 能完成其中 48 个时，他们才决定发布。Lenny 听到后大笑："我成了 eval？" Boris 说："这是反向突破。"（reverse breaking through）
Boris 自己每天用 Co-work 处理各种非编程任务：缴停车罚单、团队项目管理（在电子表格和 Slack 之间同步状态、每周一自动催未填进度的工程师）、回复邮件、取消订阅——Co-work 也帮同事在产假期间填写了繁琐的医疗表格。
印刷术类比：编程正在经历 500 年前的识字民主化
核心要点：中世纪不到 1% 的人会读写，印刷术发明后 200 年全球识字率升至 70%——编程正在经历同样的转变，Boris 认为这将催生一个"所有人都能编程"的世界，其影响像文艺复兴一样不可预测。
- 15 世纪中叶欧洲识字率不到 1%，只有抄写员掌握读写技能，受雇于自己都不识字的贵族
- 印刷术发明后 50 年，印刷材料总量超过此前 1000 年的总和；成本在 50 年内下降约 100 倍
- 识字率花了 200 年才升到 70%（需要教育体系、空闲时间——不能整天在农场干活）
- Boris 找到一份历史文献：一位 15 世纪的抄写员被问到对印刷术的感受，回答竟然很兴奋——"我不喜欢的是在书本之间抄来抄去，我喜欢的是画插图和装帧书籍，现在时间终于被释放出来了"。Boris 说自己作为工程师有完全相同的感受：编程中烦人的细节工作没有了，留下的是思考构建什么、与用户对话、与团队协作
- 但短期内会"非常具有破坏性"（very disruptive）且"对很多人来说很痛苦"——Boris 强调这需要全社会共同讨论
AI 产品构建三条建议：不要框住模型、Bitter Lesson、为 6 个月后的模型构建
核心要点：绝大多数 AI 产品的错误在于给模型加太多脚手架——scaffolding 带来的 10-20% 性能提升会被下一代模型直接抹掉。
- 不要把模型关在盒子里：很多人的直觉是给模型严格的工作流（必须先做步骤一、再做步骤二），用复杂的 orchestrator 控制。但几乎总是直接给模型工具 + 目标、让它自己决定执行顺序能拿到更好结果。一年前也许需要脚手架，现在不需要了
- Bitter Lesson：Rich Sutton 约 10 年前的博客文章——更通用的模型永远胜过更专用的模型。推论：不要用小模型、不要 fine-tune（除非有特殊原因），尽可能押注最通用的模型
- 为 6 个月后的模型构建：Claude Code 最初只写 Boris 20% 的代码，但从第一天起就赌"模型终将好到可以写所有代码"。这意味着头 6 个月产品市场匹配会很差，但模型能力到位时"你已经准备好了，产品会 click"。Opus 4 发布后 Claude Code 的增长印证了这一策略
Boris 分享了两个可以下注的方向：模型会越来越擅长使用工具和电脑；模型会越来越能长时间无人看管地运行——从 Sonnet 3.5 时代的 15-30 秒到 Opus 4.6 的 10-30 分钟，现在甚至可以运行数小时甚至数天。
安全三层架构：从神经元到真实世界
核心要点：Anthropic 在模型安全上建立了三层防线——机制可解释性、实验室评估、真实世界部署——Claude Code 在内部测试了 4-5 个月才外部发布。
- 第一层：机制可解释性（Mechanistic Interpretability）——由 Chris Olah 开创的领域。研究模型内部神经元的行为，已能追踪到特定概念对应的神经元（如"欺骗"相关的神经元是否被激活）。模型变大后出现"超位"（superposition）现象：单个神经元可能对应十几个概念，多个神经元共同激活时代表更复杂的概念。已有较强证据表明模型"不只是在预测下一个 token，而是在做更深层的事情"
- 第二层：Eval——把模型放在"培养皿"中，给它合成场景，观察它的行为是否对齐、是否安全
- 第三层：真实世界部署——前两层表现好的模型在真实世界中可能表现不同。Claude Code 在内部使用了 4-5 个月才对外发布，Co-work 也经历了类似流程
- Anthropic 开源了 agent 沙箱，兼容任何 agent 而非仅限 Claude Code——Boris 称之为"race to the top"策略
角色融合：PM、工程师、设计师的 50% 重叠
核心要点：Boris 预测年底"软件工程师"头衔将开始消失，被"builder"取代——Claude Code 团队已经在实践这一点：PM 写代码，设计师写代码，财务写代码，数据科学家写代码。
- Claude Code 团队每个人都写代码——PM、工程经理、设计师、财务、数据科学家
- 三个角色之间已有约 50% 的重叠；差异在于专长方向（Boris 偏重编码，PM 偏重协调/规划/预测）
- 最强的工程师往往跨学科：产品 + 基建混合型、有设计感的产品工程师、懂商业的工程师、爱和用户聊天的工程师
- Lenny 调查：70% 的工程师和 PM 表示使用 AI 后更享受工作，仅 10% 觉得变差；但设计师只有 55% 觉得更好、20% 觉得变差——Boris 对此也很好奇，想深入了解原因
- Boris 的建议：成为通才，跨越学科边界，不要只做工程——这比单纯掌握 AI 工具更重要
"I think by the end of the year, everyone's going to be a product manager and everyone codes. The title software engineer is going to start to go away." —— Boris Cherny
个人故事：敖德萨、打孔卡、TI-83 作弊、日本味噌
敖德萨同乡
访谈中 Boris 提到自己出生在乌克兰，Lenny 随口问"哪个城市"，Boris 说"敖德萨"——Lenny 惊呼"我也是！"两人大笑。Boris 家 1995 年移民美国，Lenny 家更早（1988 年）。Boris 说"我每天都觉得自己很幸运能在这里长大"，Lenny 的家人则每逢任何好事都会举杯"to America!"——Boris 笑着说"我们也是同样的 toast，但还是用伏特加"。
爷爷是苏联第一代程序员
Boris 的外公是苏联最早一批程序员，用打孔卡编程。母亲小时候的记忆是：外公带回家一大摞打孔卡，她就在上面用蜡笔画画。外公没有活到软件时代的到来。Boris 由此类比：当年从打孔卡到软件的转变中，老一辈程序员也许不把软件"当作真正的编程"——每一代都经历同样的转变。
TI-83 作弊故事
Boris 自学编程的起点是为了在数学考试中作弊：把答案编程到 TI-83 Plus 图形计算器里。后来题目太难、无法预知考什么，他就写了一个代数求解器。再后来他发现可以用连接线把程序传给全班——全班都拿了 A，然后被老师抓了。Boris 说从一开始编程对他就是纯粹的工具："编程是用来做事的方式，不是目的本身。"
日本乡下与味噌
加入 Anthropic 之前，Boris 住在日本乡下——镇上唯一的工程师、唯一的英语使用者。每周骑车路过稻田去农贸市场，和邻居交换腌菜来建立友谊。他学会了做味噌：白味噌至少 3 个月，红味噌 2-4 年。"味噌教会我用长时间尺度思考"——这和工程世界完全不同。他也在那个时期读了大量科幻小说，开始思考 AI 的长期走向，最终决定必须"为这件事走向好的方向做点贡献"，于是加入 Anthropic。
被问到"AGI 之后你打算做什么"，Boris 说：做味噌。
Lightning Round：书、产品、座右铭、推特
- 推荐书：(1) Functional Programming in Scala——"我读过的最好的技术书"，Scala 本身不一定用得上，但函数式编程和类型思维塑造了他的编码方式；(2) Accelerando（Charles Stross）——科幻小说，节奏越来越快，从 liftoff 到"集体龙虾意识绕木星运行"，跨越几十年，"比任何书都更能捕捉当下这个时刻的本质"；(3) 流浪地球（刘慈欣短篇集）——比《三体》更喜欢短篇集，"中国科幻提供了和西方完全不同的视角"
- 最近最喜欢的产品：Co-work——"确实改变了我的生活"，Chrome 集成特别好用，帮他缴罚单、取消订阅、处理日常琐事
- 人生座右铭：Use common sense——他见过最多的失败是人们不动脑子地跟流程、跟惯性。最好的结果来自第一性原理思考
- 为什么开始用 Twitter：2025 年 12 月在欧洲旅行时太无聊，打开 Twitter 看到有人讨论 Claude Code 的 bug 就开始回复。他用 Claude Code 几分钟内就能修复用户报告的 bug——用户对这个速度感到震惊，这让他觉得 Twitter 值得继续。之前他主要用 Threads（因为他参与过 Threads 的早期开发）
附录：关键人/机构/产品/数据
：关键人/机构/产品/数据
| 项目 | 详情 |
|------|------|
| Boris Cherny | Anthropic Claude Code 负责人，前 Meta/Instagram 工程师，TypeScript 书作者 |
| Lenny Rachitsky | 播客主持人，同为乌克兰敖德萨出生 |
| Ben Man | Anthropic 联合创始人，早期催促 Boris 做 DAU 图表，提议"post-AGI 问题" |
| Chris Olah | Anthropic 机制可解释性领域开创者 |
| Fiona | Facebook Marketplace 团队创始经理 |
| Brendan | Anthropic 数据科学家，自学终端使用 Claude Code 做 SQL 分析 |
| Felix, Sam, Jenny | Co-work 核心构建团队成员 |
| Claude Code | Anthropic 编程 agent，GitHub 4% commit 占比，预计年底 20% |
| Co-work | Claude 桌面端非技术任务 agent，10 天构建，发布即爆款 |
| MCP | Anthropic 构建的协议（与 Claude Code 同一时期由同一团队产出） |
| Opus 4 / 4.6 | Anthropic ASL-3 级模型，Claude Code 增长拐点始于 Opus 4 发布 |
| Sonnet 3.5 | 早期模型基准，当时 agent 只能运行 15-30 秒 |
| Semi Analysis 报告 | GitHub 4% commit 来自 Claude Code，预测年底 20% |
| Anthropic 融资 | 最新一轮估值超 3500 亿美元 |
| Claude Code 收入 | 约 20 亿美元；Anthropic 整体约 150 亿美元 |
| 工程生产力 | Anthropic 人均 PR 产出提升 200%，团队规模约扩大 4 倍 |
| 工程师 token 消耗 | 部分 Anthropic 工程师月消耗数十万美元 token |
| Bitter Lesson | Rich Sutton 博客文章，核心论点：更通用的模型永远胜过更专用的模型 |
| Scaling Laws | Anthropic 三位联合创始人是该论文前三位作者 |
| Lenny 的 50 个用例 | 被 Anthropic PM 用作 Co-work 发布前的 eval 标准（48/50 通过） |
中文翻译 English Original
**Boris Cherny：** 我100%的代码都是用 Claude Code 写的。从去年11月起，我没有手动编辑过哪怕一行代码。每天我会提交10个、20个、30个拉取请求（pull request）。就在我们录这期节目的时候，我同时开着大概五个智能体（agent）在跑。
**Boris Cherny:** 100% of my code is written by Claude Code. I have not edited a single line by hand since November. Every day I ship 10, 20, 30 pull requests. So at the moment I have like five agents running while we're recording this.
**Lenny：** 是的。你会怀念写代码的日子吗？
**Lenny:** Yeah. Yeah. Do you miss writing code?
**Boris Cherny：** 我从来没有像今天这样享受编程，因为我再也不用处理那些琐碎的细节了。每位工程师的生产力提升了200%。
**Boris Cherny:** I have never enjoyed coding as much as I do today because I don't have to deal with all the minutia. Productivity per engineer has increased 200%.
**Lenny：** 一直有人问"我该不该学编程？"再过一两年，这个问题就不重要了。编程基本上已经被解决了。我能想象一个人人都会编程的世界，任何人随时都能构建软件。下一个软件开发的重大变革是什么？
**Lenny:** There's always this question, should I learn to code? In a year or two, it's not going to matter. Coding is largely solved. I imagine a world where everyone is able to program. Anyone can just build software anytime. What's the next big shift to how software is written?
**Boris Cherny：** Claude 正在开始自己提出想法。它会浏览用户反馈，查看 bug 报告，分析遥测数据（telemetry），然后提出 bug 修复和功能建议——越来越像一个同事。
**Boris Cherny:** Claude is starting to come up with ideas. It's looking through feedback. It's looking at bug reports. It's looking at telemetry for bug fixes and things to ship a little more like a co-worker or something like that.
**Lenny：** 很多听众是产品经理，他们估计正在冒冷汗。我觉得到今年年底，人人都会成为产品经理，人人都能写代码。"软件工程师"这个头衔会开始消失，取而代之的是"构建者"（builder）。这对很多人来说会是一个痛苦的过程。
**Lenny:** A lot of people listening to this are product managers and they're probably sweating. I think by the end of the year, everyone's going to be a product manager and everyone codes. The title software engineer is going to start to go away. It's just going to be replaced by builder and it's going to be painful for a lot of people.
**Lenny：** 今天的嘉宾是 Boris Cherny，Anthropic 公司 Claude Code 的负责人。很难描述 Claude Code 对这个世界产生了多大的影响。大约在这期节目播出的时候，正好是 Claude Code 发布一周年。在这短短的时间里，它彻底改变了软件工程师的工作方式，现在还开始改变科技行业其他岗位的工作方式——我们在节目中会详细讨论。
**Lenny:** Today my guest is Boris Cherny, head of Claude Code at Anthropic. It is hard to describe the impact that Claude Code has had on the world. Around the time this episode comes out will be the one-year anniversary of Claude Code. And in that short time, it has completely transformed the job of a software engineer and it is now starting to transform the jobs of many other functions in tech which we talk about.
**Lenny：** Claude Code 本身也是 Anthropic 过去一年整体增长的重要驱动力。他们刚刚以超过3500亿美元的估值完成了一轮融资。正如 Boris 提到的，Claude Code 自身的增长仍在加速。仅仅在过去一个月，他们的日活跃用户就翻了一倍。Boris 本人也是一个非常有趣、有思想、善于深度思考的人。在这次对话中，我们发现我们居然出生在乌克兰同一座城市。太有意思了，我之前完全不知道。非常感谢 Ben Man、Jenny Wen 和 Mike Krieger 为这次对话推荐了话题。别忘了去 lennisprodpass.com 看看，那里有专属于 Lenny 新闻通讯订阅者的超值优惠。让我们在精彩赞助商的广告之后正式开始。
**Lenny:** Claude Code itself is also a massive driver of Anthropic's overall growth over the past year. They just raised a round at over $350 billion. And as Boris mentions, the growth of Claude Code itself is still accelerating. Just in the past month, their daily active users has doubled. Boris is also just a really interesting, thoughtful, deep-thinking human. And during this conversation, we discover we were born in the same city in Ukraine. That is so funny. I had no idea. A huge thank you to Ben Man, Jenny Wen, and Mike Krieger for suggesting topics for this conversation. Don't forget to check out lennisprodpass.com for an incredible set of deals available exclusively to Lenny's newsletter subscribers. Let's get into it after a short word from our wonderful sponsors.
**Lenny：** 今天的节目由 DX 赞助——这是一个由顶尖研究人员设计的开发者智能平台。要在 AI 时代蓬勃发展，组织需要快速适应。但许多组织领导者难以回答这些紧迫的问题：哪些工具有效？它们是如何被使用的？什么真正在创造价值？DX 提供领导者所需的数据和洞察来应对这一转变。通过 DX，Dropbox、Booking.com、Adyen 和 Intercom 等公司深入了解了 AI 如何为开发者创造价值，以及 AI 对工程生产力的实际影响。了解更多请访问 DX 的网站 getdx.com/lenny。
**Lenny:** Today's episode is brought to you by DX, the developer intelligence platform designed by leading researchers. To thrive in the AI era, organizations need to adapt quickly. But many organization leaders struggle to answer pressing questions like which tools are working? How are they being used? What's actually driving value? DX provides the data and insights that leaders need to navigate this shift. With DX, companies like Dropbox, Booking.com, Adyen, and Intercom get a deep understanding of how AI is providing value to their developers and what impact AI is having on engineering productivity. To learn more, visit DX's website at getdx.com/lenny. That's getdx.com/lenny.
**Lenny：** 应用程序会以各种方式出问题——崩溃、卡顿、回退，还有那些只有真实用户出现后才会暴露的问题。Sentry 能捕获所有这些。它能告诉你发生了什么、在哪里、为什么——精确到引入错误的那次提交、提交代码的开发者，以及具体的代码行——全部在一个统一的视图中呈现。我确实试过那种开五个标签页外加一个 Slack 讨论串来调试的方式。Sentry 更好。它能展示请求的流转路径、什么在运行、什么变慢了、用户看到了什么。
**Lenny:** Applications break in all kinds of ways. Crashes, slowdowns, regressions, and the stuff that you only see once real users show up. Sentry catches it all. See what happened where, and why, down to the commit that introduced the error, the developer who shipped it, and the exact line of code all in one connected view. I've definitely tried the five tabs and Slack thread approach to debugging. This is better. Sentry shows you how the request moved, what ran, what slowed down, and what users saw.
**Lenny：** Seer 是 Sentry 的 AI 调试智能体，它会接手后续工作。它利用 Sentry 的所有上下文信息告诉你根本原因，建议修复方案，甚至直接为你开一个 PR。它还会审查你的 PR，标记任何破坏性变更并准备好修复方案。在 sentry.io/lenny 免费试用 Sentry 和 Seer，使用优惠码 Lenny 可获得100美元的 Sentry 积分。
**Lenny:** Seer, Sentry's AI debugging agent, takes it from there. It uses all of that Sentry context to tell you the root cause, suggest a fix, and even opens a PR for you. It also reviews your PR and flags any breaking changes with fixes ready to go. Try Sentry and Seer for free at sentry.io/lenny and use code Lenny for $100 in Sentry credits. That's s-n-t-r-y.io/lenny.
**Lenny：** Boris，非常感谢你来做客，欢迎来到播客节目。
**Lenny:** Boris, thank you so much for being here and welcome to the podcast.
**Boris Cherny：** 谢谢你邀请我。
**Boris Cherny:** Yeah, thanks for having me on.
**Lenny：** 我想先抛一个劲爆的问题。大约6个月前——不知道大家还记不记得——你其实离开了 Anthropic，加入了 Cursor，然后两周后又回到了 Anthropic。当时到底发生了什么？我觉得我从来没听过真实的故事。
**Lenny:** I want to start with a spicy question. About 6 months ago, I don't know if people even remember this, you actually left Anthropic. You joined Cursor and then two weeks later, you went back to Anthropic. What happened there? I don't think I've ever heard the actual story.
**Boris Cherny：** 这是我经历过的最快的一次跳槽。我加入 Cursor 是因为我非常喜欢他们的产品，而且我见了团队之后确实印象深刻。他们是一个很棒的团队，我现在仍然觉得他们很棒，他们在做非常酷的东西。可以说，他们比很多人更早看到了 AI 编程的发展方向。所以打造优秀产品这件事本身对我来说非常有吸引力。
**Boris Cherny:** It's the fastest job change that I've ever had. I joined Cursor because I'm a big fan of the product and honestly I met the team and I was just really impressed. They're an awesome team. I still think they're awesome and they're just building really cool stuff and kind of they saw where AI coding was going I think before a lot of people did. So the idea of building good product was just very exciting for me.
**Boris Cherny：** 但我到了之后很快意识到，我真正怀念 Anthropic 的是它的使命。这其实也是最初吸引我加入 Anthropic 的原因。在加入 Anthropic 之前，我在大型科技公司工作，后来有一天我想去一家实验室，以某种方式参与塑造我们正在构建的这个疯狂事物的未来。吸引我来 Anthropic 的就是使命——一切都围绕安全。你在 Anthropic 随便拉住一个人，问他们为什么在这里，答案永远是安全。
**Boris Cherny:** I think as soon as I got there, what I started to realize is what I really missed about Anthropic was the mission. And that's actually what originally drove me to Anthropic also because before I joined Anthropic, I was working in big tech and then at some point I wanted to work at a lab to just help shape the future of this crazy thing that we're building in some way. And the thing that drew me to Anthropic was the mission. It's all about safety. And when you talk to people at Anthropic, just like find someone in the hallway, if you ask them why they're here, the answer is always going to be safety.
**Boris Cherny：** 这种使命驱动的文化深深打动了我。我也认识到，对我个人而言，这是获得幸福感的必要条件。这就是我真正怀念的东西。我发现，无论工作本身多么令人兴奋，哪怕是在打造一个非常酷的产品，都无法真正替代这种使命感。所以对我来说，我很快就意识到自己缺少了这一点。
**Boris Cherny:** And so this kind of mission-drivenness just really really resonated with me. And I just know personally it's something I need in order to be happy. And that's just a thing that I really missed. And I found that, you know, whatever the work might be, no matter how exciting, even if it's building a really cool product, it's just not really a substitute for that. So for me it was actually pretty obvious that I was missing that pretty quick.
**Lenny：** 好的。那让我顺着这条线聊聊你回到 Anthropic 之后的工作。这期播客播出的时间大约是 Claude Code 发布一周年的日子。所以我想花一些时间回顾一下你所产生的影响。
**Lenny:** Okay. So let me follow the thread of just coming back to Anthropic and the work you've done there. This podcast is going to come out around the year anniversary of launching Claude Code. So I'm going to spend a little time just reflecting on the impact that you've had.
**Lenny：** 最近有一份 SemiAnalysis 的报告——我相信你看到了——显示 GitHub 上4%的提交（commit）现在是由 Claude Code 完成的。他们预测到今年年底，GitHub 上五分之一的代码提交将由 Claude Code 完成。他们的原话是"当我们一眨眼的功夫，AI 就吞噬了整个软件开发"。就在我们录制的这一天，Spotify 刚刚发布了一则头条新闻，说他们最优秀的开发者自去年12月以来就没有写过一行代码——全靠 AI。
**Lenny:** There's this report that recently came out that I'm sure you saw by SemiAnalysis that showed that 4% of all GitHub commits are authored by Claude Code now. And they predicted it'll be a fifth of all code commits on GitHub by the end of the year. The way they put it is while we blinked, AI consumed all software development. The day that we're recording this, Spotify just put out this headline that their best developers haven't written a line of code since December thanks to AI.
**Lenny：** 越来越多最顶尖的资深工程师——包括你——都在公开分享一个事实：你们不再亲自写代码了，所有代码都是 AI 生成的。很多人甚至不再看代码了——我们已经走到了这一步，这在很大程度上要归功于你启动的这个小项目，以及你的团队在过去一年中将它扩展壮大。我很想听你回顾一下这一年的感受，以及你的工作所产生的影响。
**Lenny:** More and more of the most advanced senior engineers, including you, are sharing the fact that you don't write code anymore, that it's all AI generated. And many aren't even looking at code anymore is how far we've gotten in large part thanks to this little project that you started and that your team has scaled over the past year. I'm curious just to hear your reflections on this past year and the impact that your work has had.
**Boris Cherny：** 这些数字简直太疯狂了。全世界4%的提交——这远超我的想象。而且正如你所说，这感觉才刚刚开始。这些还只是公开的提交。我们认为如果看私有仓库（private repository），这个比例会高出不少。我觉得最疯狂的还不是我们目前达到的数字，而是增长的速度。如果你看 Claude Code 在任何指标上的增长率，它还在持续加速——不只是在增长，而是增长得越来越快。
**Boris Cherny:** These numbers are just totally crazy, right? Like 4% of all commits in the world is just way more than I imagined and like you said, it still feels like the starting point. These are also just public commits. So we actually think if you look at private repositories, it's quite a bit higher than that. And I think the craziest thing for me isn't even the number that we're at right now, but the pace at which we're growing because if you look at Claude Code's growth rate kind of across any metric, it's continuing to accelerate. So it's not just going up, it's going up faster and faster.
**Boris Cherny：** 当我最初开始做 Claude Code 的时候，它只是一个小实验。我们在 Anthropic 内部大致知道我们想推出某种编程产品。长期以来，Anthropic 构建模型的方式遵循着我们对安全 AI 的心智模型：模型先是在编程上表现出色，然后在工具使用（tool use）上表现出色，然后在计算机使用（computer use）上表现出色。大致就是这个发展轨迹。
**Boris Cherny:** When I first started Claude Code, it was just going to be a like it was just supposed to be a little hack. We broadly knew at Anthropic that we wanted to ship some kind of coding product and for Anthropic for a long time we were building the models in this way that kind of fit our mental model of the way that we build safe AI where the model starts by being really good at coding then it gets really good at tool use then it gets really good at computer use. Roughly this is like the trajectory.
**Boris Cherny：** 我们在这方面投入了很长时间。我最初加入的团队叫 Anthropic Labs 团队——实际上 Mike Krieger 和 Ben Man 最近刚刚重新启动了这个团队的第二阶段。这个团队构建了一些非常酷的东西：我们做了 Claude Code，做了 MCP，做了桌面应用。你可以看到这个理念的萌芽——先是编程，然后是工具使用，然后是计算机使用。
**Boris Cherny:** We've been working on this for a long time and when you look at the team that I started on it was called the Anthropic Labs team and actually Mike Krieger and Ben Man they just kicked this team off again for kind of round two. The team built some pretty cool stuff so we built Claude Code, we built MCP, we built the desktop app. So you can kind of see the seeds of this idea -- it's coding then it's tool use then it's computer use.
**Boris Cherny：** 这对 Anthropic 很重要的原因还是回到安全。AI 正变得越来越强大、越来越有能力。过去一年发生的变化是，至少对工程师来说，AI 不只是写代码，不只是一个对话伙伴，它实际上在使用工具，在真实世界中采取行动。
**Boris Cherny:** And the reason this matters for Anthropic is because of safety. It's kind of again just back to that. AI is getting more and more powerful. It's getting more and more capable. The thing that's happened in the last year is that for at least for engineers, the AI doesn't just write the code. It's not just a conversation partner, but it actually uses tools. It acts in the world.
**Boris Cherny：** 我认为现在通过 co-work（协作模式），我们开始看到非技术人员也在经历这种转变。对于很多使用对话式 AI 的人来说，这可能是他们第一次使用一个能够实际行动的工具。它可以使用你的 Gmail、你的 Slack，为你做各种事情，而且做得相当好。未来只会更好。
**Boris Cherny:** And I think now with co-work, we're starting to see the transition for non-technical folks also. For a lot of people that use conversational AI, this might be the first time that they're using the thing that actually acts. It can actually use your Gmail, it can use your Slack, it can do all these things for you and it's quite good at it. And it's only going to get better from here.
**Boris Cherny：** 所以在 Anthropic 内部，长期以来一直有一种感觉：我们想要构建一些东西，但不清楚具体是什么。当我加入 Anthropic 后，我花了一个月的时间进行各种实验，构建了一堆奇怪的原型。大部分都没有发布，甚至离发布还差得很远。这只是在探索模型能力的边界。然后我又花了一个月做训练后处理（post-training），去理解研究那一面的东西。
**Boris Cherny:** So I think for Anthropic for a long time there was this feeling that we wanted to build something but it wasn't obvious what. And so when I joined Anthropic I spent one month kind of hacking and built a bunch of weird prototypes. Most of them didn't ship and weren't even close to shipping. It was just kind of understanding the boundaries of what the model can do. Then I spent a month doing post-training to understand kind of the research side of it.
**Boris Cherny：** 老实说，作为一名工程师，我一直认为要做好工作，你必须理解你所工作层级之下的那一层。在传统的工程工作中，如果你做产品，你需要了解基础设施、运行时、虚拟机、编程语言——你所构建的系统的底层。但如果你做 AI 开发，你真的必须在一定程度上理解模型本身才能做好工作。所以我绕了一段路去做这件事，然后回来开始做最终成为 Claude Code 的原型。
**Boris Cherny:** And I think honestly that's just for me as an engineer I find that to do good work you really have to understand the layer under the layer at which you work. And with traditional engineering work, if you're working on product, you want to understand the infrastructure, the runtime, the virtual machine, the language -- kind of whatever that is, the system that you're building on. But if you're working in AI, you just really have to understand the model to some degree to do good work. So I took a little detour to do that and then I came back and just started prototyping what eventually became Claude Code.
**Boris Cherny：** 最初的版本——我有一段录像，因为我录制了一个演示并发布了出去。当时它叫 Claude CLI。我展示了它如何使用几个工具。最让我震惊的是，我给了它一个 bash 工具，它就能用这个工具来写代码告诉我我正在听什么音乐——当我问它"我现在在听什么音乐？"的时候。
**Boris Cherny:** And the very first version of it, I have like a video recording of this because I recorded this demo and I posted it. It was called Claude CLI back then. And I just kind of showed off how it used a few tools and the shocking thing for me was that I gave it a bash tool and it just was able to use that to write code to tell me what music I'm listening to when I asked it like what music am I listening to?
**Boris Cherny：** 这是最疯狂的事情，因为我并没有指示模型说"用这个工具来做这件事"之类的。模型拿到了这个工具，然后自己想出了如何用它来回答我的问题——一个我甚至不确定它能不能回答的问题。"我在听什么音乐？"
**Boris Cherny:** And this is the craziest thing, right? Because it's like I didn't instruct the model to say use this tool for this or kind of do whatever. The model was given this tool and it figured out how to use it to answer this question that I had that I wasn't even sure if it could answer. What music am I listening to?
**Boris Cherny：** 于是我开始进一步尝试这个原型。我写了一篇帖子，在公司内部发布了这个消息——结果获得了两个赞。这就是当时的全部反响。因为公司内部的人想到编程工具，就会想到 IDE，想到各种相当复杂的开发环境。没人觉得这东西可以是基于终端（terminal）的。这种设计方式很奇怪。
**Boris Cherny:** And so I started prototyping this a little bit more. I made a post about it and I announced it internally and it got two likes. That was the extent of the reaction at the time because I think people internally, when you think of coding tools you think of IDE, you think about kind of all these pretty sophisticated environments. No one thought that this thing could be terminal based. That's sort of a weird way to design it.
**Boris Cherny：** 这其实不是有意为之。我一开始把它做成终端应用是因为最初几个月就我一个人，这是最简单的构建方式。对我来说这其实是一个很重要的产品经验——在一开始稍微少给一点资源。
**Boris Cherny:** And that wasn't really the intention but from the start I built it in a terminal because for the first couple months it was just me so it was just the easiest way to build. And for me this is actually a pretty important product lesson -- you want to under-resource things a little bit at the start.
**Boris Cherny：** 后来我们开始考虑是否应该做成其他形态，但最终决定继续用终端。最主要的原因是模型进化得太快了，我们觉得没有其他形态能跟上它的进化速度。老实说，这就是我一直在纠结"我们该做什么"的结果。过去一年，Claude Code 就是我脑子里想的全部事情。
**Boris Cherny:** Then we started thinking about what other form factors we should build and we actually decided to stick with the terminal for a while and the biggest reason was the model is improving so quickly. We felt that there wasn't really another form factor that could keep up with it. And honestly this was just me kind of struggling with what should we build. For the last year Claude Code has just been all I think about.
**Boris Cherny：** 深夜里我也在想这件事——模型在持续进步，我们该怎么办？我们怎么才能跟上？终端老实说是我当时唯一想到的答案。后来发布之后，它很快就火了。在 Anthropic 内部一炮而红，日活跃用户直线飙升。
**Boris Cherny:** And so just like late at night, this is just something I was thinking about like, okay, the model is continuing to improve. What do we do? How can we possibly keep up? And the terminal was honestly just the only idea that I had. And yeah, it ended up catching on after I released it pretty quickly. It became a hit at Anthropic and the daily active users just went vertical.
**Boris Cherny：** 实际上在发布之前很早的时候，Ben Man 就建议我做一个 DAU 图表。我当时觉得"现在还太早了吧，真的要做吗？"他说"做。"于是这个图表几乎立刻就呈垂直上升的态势。
**Boris Cherny:** And really early on, actually before I launched it, Ben Man nudged me to make a DAU chart and I was like, it's kind of early maybe, should we really do it right now? And he was like, "Yeah." And so the chart just went vertical pretty immediately.
**Boris Cherny：** 然后在二月份我们对外发布了。有一件事人们可能不太记得了：Claude Code 最初对外发布的时候并不是一炮而红的。它获得了一些用户，有很多早期采用者立刻就用上了，但实际上花了好几个月，大家才真正理解这个东西是什么。因为它太不一样了。
**Boris Cherny:** And then in February, we released it externally. Actually, something that people don't really remember is Claude Code was not initially a hit when we released it. It got a bunch of users. There was a lot of early adopters that got it immediately, but it actually took many months for everyone to really understand what this thing is. Just again, it's just so different.
**Boris Cherny：** 回想起来，Claude Code 之所以能成功，其中一个原因是"潜在需求"（latent demand）这个概念——我们把工具带到人们已经在的地方，让现有的工作流变得更容易一些。但也因为它是在终端里的，它有一种出人意料的感觉，有一种陌生感。所以你需要保持开放心态，需要学习如何使用它。
**Boris Cherny:** And when I think about it, kind of part of the reason Claude Code works is this idea of latent demand where we bring the tool to where people are and it makes existing workflows a little bit easier, but also because it's in a terminal. It's like a little surprising. It's a little alien in this way. So you have to be open-minded and you had to learn to use it.
**Boris Cherny：** 当然现在 Claude Code 已经可以在 iOS 和 Android 的 Claude 应用里使用了，在桌面应用里也有，在网页端也有，还有 IDE 扩展，在 Slack 和 GitHub 里也有。所有工程师所在的地方它都在，变得更加熟悉了。但起点并不是这样的。
**Boris Cherny:** And of course now Claude Code is available in the iOS and Android Claude app. It's available in the desktop app. It's available on the website. It's available as IDE extensions in Slack and GitHub. All these places where engineers are it's a little more familiar but that wasn't the starting point.
**Boris Cherny：** 总之，一开始大家都没想到这个东西会有用。随着团队的壮大、产品的成长、它变得越来越有用——从小型创业公司到最大的 FAANG 公司，全世界的人都开始使用它，并且开始提供反馈。
**Boris Cherny:** So yeah I mean at the beginning it was kind of a surprise that this thing was even useful. And as the team grew, as the product grew, as it started to become more and more useful to people -- just people around the world from small startups to the biggest FAANG companies started using it and they started giving feedback.
**Boris Cherny：** 回顾这一切，这是一段非常令人谦卑的经历。我们不断从用户那里学习。最令人兴奋的是，我们谁都不真正知道自己在做什么。我们只是在和所有人一起摸索，而最有价值的信号就是用户的反馈。这是最棒的。我被惊到了太多次。
**Boris Cherny:** And I think just reflecting back it's been such a humbling experience because we just keep learning from our users and just the most exciting thing is like none of us really know what we're doing. And we're just trying to figure out along with everyone else and the single best signal for that is just feedback from users. So that's just been the best. I've been surprised so many times.
**Lenny：** 在今天这个时代，变化可以发生得如此之快，这真是不可思议。你一年前发布了这个工具——虽然这不是人们第一次能用 AI 来编程——但在一年内，整个软件工程这个职业就发生了巨大变化。曾经各种预测说"AI 会写100%的代码"，大家都觉得"这太疯狂了，你在说什么"。现在——当然这正在发生，完全如他们所说。一切变化得太快了。
**Lenny:** It's incredible how fast something can change in today's world. You launched this a year ago and it wasn't the first time people could use AI to code but in a year the entire profession of software engineering has dramatically changed. Like there's all these predictions oh AI is going to be written 100% -- AI's code is going to be written by AI. Everyone's like no that's crazy what are you talking about. Now it's like of course it's happening exactly as they said. It's just -- things move so fast and change so fast now.
**Boris Cherny：** 是的，真的非常快。回想今年5月在 Code with Claude 大会上——那是 Anthropic 举办的第一个开发者大会。我做了一个简短的演讲，在演讲后的问答环节，大家问我对年底有什么预测。当时我的预测是：到今年年底，你可能不再需要 IDE 来编程了，我们将开始看到工程师不再需要 IDE。我记得全场发出了一声清晰的倒吸凉气。这个预测太疯狂了。
**Boris Cherny:** Yeah it's really fast. Back at Code with Claude back in May that was like our first developer conference that we did as Anthropic. I did a short talk and in the Q&A after the talk people were asking what are your predictions for the end of the year and my prediction back in May of 2025 was by the end of the year you might not need an IDE to code anymore and we're going to start to see engineers not doing this and I remember the room like audibly gasped. It was such a crazy prediction.
**Boris Cherny：** 但我认为在 Anthropic，我们思考事物的方式就是指数级的。这深深植入了公司的 DNA。看看我们的联合创始人——其中三位是扩展法则（scaling laws）论文的前三位作者。所以我们真的是用指数思维来思考问题的。如果你看当时 Claude 写代码的比例这条指数曲线，顺着延长线画下去，很明显年底之前就会突破100%——即使这完全不符合直觉。所以我只是顺着趋势线延伸了一下。在11月份，这件事在我身上成为了现实，此后一直如此。我们也开始在很多不同客户身上看到同样的趋势。
**Boris Cherny:** But I think at Anthropic this is just the way we think about things -- exponentials. And this is like very deep in the DNA. Like if you look at our co-founders, three of them were the first three authors on the scaling laws paper. So we really just think in exponentials and if you kind of look at the exponential of the percent of code that was written by Claude at that point if you just trace the line it's pretty obvious we're going to cross 100% by the end of the year even if it just does not match intuition at all. And so all I did was trace the line and yeah, in November that happened for me personally and that's been the case since and we're starting to see that for a lot of different customers too.
**Lenny：** 你刚才分享的关于这段旅程的内容非常有趣——这种先玩一玩、看看会发生什么的理念。这种情况在 Claude 的发展中反复出现——Peter 也是在摆弄中发现了一些东西。感觉这是 AI 领域许多最大创新的核心要素——人们就是坐在那里尝试各种东西，把模型推到比大多数人更远的地方。
**Lenny:** I thought it was really interesting what you just shared there about kind of the journey -- this idea of just playing around and seeing what happens. This comes up with Claude a lot just like Peter was playing around and just like a thing happened. And it feels like that's a central kind of ingredient to a lot of the biggest innovations in AI is people just sitting around trying stuff, pushing the models further than most other people.
**Boris Cherny：** 这就是创新的本质——你无法强迫创新。创新没有路线图。你只需要给人们空间。你可能需要的词是"安全感"——一种心理安全感（psychological safety），让大家知道失败是可以的，80%的想法不好也是可以的。同时你也需要一定程度的问责——如果一个想法不好，就及时止损，转向下一个想法，而不是继续投入更多。
**Boris Cherny:** I mean this is the thing about innovation right -- you can't force it. There's no road map for innovation. You just have to give people space. You have to give them maybe the word is like safety. So it's like psychological safety that it's okay to fail. It's okay if 80% of the ideas are bad. You also have to hold them accountable a bit. So if the idea is bad, you cut your losses, move on to the next idea instead of investing more.
**Boris Cherny：** 在 Claude Code 的早期，我完全不知道这个东西会有用。因为即使在2月份对外发布的时候，它也只写了大概20%的代码，不会更多。到5月份也只写了大概30%。大部分代码我还是用 Cursor 写的。直到11月才突破100%。花了不少时间。但即使从最早期开始，我就觉得自己抓住了什么。每天晚上、每个周末我都在改这个东西。幸好我妻子非常支持我。就是那种感觉——抓住了什么，但还不清楚具体是什么。有时候你找到一根线头，你就必须一直拉下去。
**Boris Cherny:** In the early days of Claude Code, I had no idea that this thing would be useful at all. Because even in February when we released it, it was writing maybe I don't know like 20% of my code, not more. And even in May, it was writing maybe 30%. I was still using Cursor for most of my code. And it only crossed 100% in November. So it took a while. But even from the earliest day, it just felt like I was on to something. And I was just spending every night, every weekend hacking on this. And luckily my wife was very supportive. But it just felt like it was on to something. It wasn't obvious what. And sometimes you find a thread, you just have to pull on it.
**Lenny：** 那么目前的状态是，你100%的代码都由 Claude Code 编写？
**Lenny:** So at this point, 100% of your code is written by Claude Code. Is that the current state of your coding?
**Boris Cherny：** 是的。我100%的代码都由 Claude Code 编写。我的代码产出量相当高。这一点在我之前在 Instagram 工作的时候就是如此——我是生产力最高的几位工程师之一。在 Anthropic 这里仍然是这样。
**Boris Cherny:** Yeah. So 100% of my code is written by Claude Code. I am a fairly prolific coder. And this has been the case even when I worked back at Instagram. I was like one of the top few most productive engineers. And that's actually still the case here at Anthropic.
**Lenny：** 即使作为团队负责人也是？
**Lenny:** Wow. Even as head of the team.
**Boris Cherny：** 是的。我仍然写很多代码。每天我大概提交10个、20个、30个拉取请求。
**Boris Cherny:** Yeah. Yeah. I still do a lot of coding. And so every day I ship like 10, 20, 30 pull requests something like that.
**Lenny：** 每天？
**Lenny:** Every day.
**Boris Cherny：** 每天。是的。
**Boris Cherny:** Every day. Yeah.
**Lenny：** 天哪。
**Lenny:** Good god.
**Boris Cherny：** 100%由 Claude Code 编写。从11月起我没有手动编辑过一行代码。但我确实还会看代码。我不认为我们已经到了可以完全放手的阶段，尤其是当有很多人在运行程序的时候。你必须确保代码是正确的，确保它是安全的。
**Boris Cherny:** 100% written by Claude Code. I have not edited a single line by hand since November. And yeah, that's been it. I do look at the code. So I don't think we're kind of at the point yet where you can be totally hands-off, especially when there's a lot of people running the program. You have to make sure that it's correct. You have to make sure it's safe and so on.
**Boris Cherny：** 我们还让 Claude 进行自动代码审查。在 Anthropic，Claude 审查100%的拉取请求。之后仍然有一层人工审查，但你确实还是需要一些检查点。你仍然需要有人看代码——除非是纯原型代码，不会在任何地方运行，只是个原型。
**Boris Cherny:** And then we also have Claude doing automatic code review for everything. So here at Anthropic, Claude reviews 100% of pull requests. There's still a layer of human review after it, but you kind of still do want some of these checkpoints. You still want a human looking at the code. Unless it's like pure prototype code that it's not going to run anywhere, it's just a prototype.
**Lenny：** 下一个前沿是什么？现在你100%的代码都由 AI 编写了。这显然是软件工程的大方向。这在之前感觉像是一个疯狂的里程碑。现在它就只是"当然，这就是世界的现状"。你的团队已经在探索的、或者你认为未来会走向的下一个软件开发的重大变革是什么？
**Lenny:** What's kind of the next frontier? So at this point 100% of your code is being written by AI. This is clearly where everyone is going in software engineering. That felt like a crazy milestone. Now it's just like of course this is the world now. What's the next big shift to how software is written that either your team's already operating in or you think will head towards?
**Boris Cherny：** 我认为正在发生的一件事是 Claude 开始自己提出想法。Claude 会浏览用户反馈、查看 bug 报告、分析遥测数据，然后开始提出 bug 修复和功能发布的建议。
**Boris Cherny:** I think something that's happening right now is Claude is starting to come up with ideas. So Claude is looking through feedback. It's looking at bug reports. It's looking at telemetry and things like this and it's starting to come up with ideas for bug fixes and things to ship.
**Boris Cherny：** 所以它正在变得越来越像一个同事。第二件事是我们开始从纯编程向外扩展。我认为在这一点上可以说，编程基本上已经被解决了。至少对我所做的那种编程来说，这已经是一个解决了的问题，因为 Claude 能做到。
**Boris Cherny:** So it's just starting to get a little more like a co-worker or something like that. I think the second thing is we're starting to branch out of coding a little bit. So I think at this point it's safe to say that coding is largely solved. At least for the kind of programming that I do, it's just a solved problem because Claude can do it.
**Boris Cherny：** 现在我们开始思考"下一步是什么？超越编程的是什么？"有很多与编程相邻的领域。但也包括通用任务。我现在每天都用 co-work 来做各种与编程完全无关的事情，而且是自动完成的。比如前几天我要交一张停车罚单，我就让 co-work 去处理了。
**Boris Cherny:** And so now we're starting to think about okay like what's next? What's beyond this? There's a lot of things that are kind of adjacent to coding. And I think this is going to be coming. But also just general tasks. I use co-work every day now to do all sorts of things that are just not related to coding at all and just to do it automatically. Like for example, I had to pay a parking ticket the other day. I just had co-work do it.
**Boris Cherny：** 我团队所有的项目管理工作都是 co-work 在做——在电子表格之间同步数据、在 Slack 上发消息、发邮件等等。所以我认为下一个前沿大概就是这个方向。我不认为是编程本身，因为编程基本上已经解决了。在接下来几个月里，我认为我们会看到编程在整个行业中对每一种代码库、每一种技术栈都变得越来越容易解决。
**Boris Cherny:** All of my project management for the team -- co-work does all of it. It's like syncing stuff between spreadsheets and messaging people on Slack and email and all this kind of stuff. So I think the frontier is something like this and I don't think it's coding because I think coding is pretty much solved and over the next few months I think what we're going to see is just across the industry it's going to become increasingly solved for every kind of codebase, every tech stack that people work on.
**Lenny：** 帮助你想出该做什么——这个想法非常有意思。很多听众是产品经理，他们可能正在冒冷汗。你是怎么用 Claude 来做这件事的？你只是跟它对话吗？你有没有想出什么巧妙的方法来帮助你用它来发现该做什么？
**Lenny:** This idea of helping you come up with what to work on is so interesting. A lot of people listening to this are product managers and they're probably sweating. How do you use Claude for this? Do you just talk to it? Is there anything clever you've come up with to help you use it to come up with what to build?
**Boris Cherny：** 老实说，最简单的方法就是打开 Claude Code 或 co-work，然后让它去看一个 Slack 频道。对我们来说，有一个频道专门收集 Claude Code 的内部反馈。从2024年内部发布以来，那里就一直是反馈的消防水管——持续不断。这是最棒的。
**Boris Cherny:** Honestly, the simplest thing is like open Claude Code or co-work and point it at a Slack thread. For us, we have this channel that's all the internal feedback about Claude Code. Since we first released it, even in like 2024 internally, it's just been this fire hose of feedback. And it's the best.
**Boris Cherny：** 在早期，我的做法是每当有人发反馈，我就立刻冲进去尽可能快地修复每一个问题——一分钟内、五分钟内。这种极快的反馈循环鼓励人们提供越来越多的反馈。这非常重要，因为它让人们觉得被倾听了。通常你用一个产品提了反馈，它就消失在某个黑洞里，然后你就不会再提反馈了。如果你让人们感到被倾听，他们就愿意贡献、愿意帮助产品变得更好。
**Boris Cherny:** And in the early days, what I would do is anytime that someone sends feedback, I would just go in and I would fix every single thing as fast as I possibly could. So like within a minute, within 5 minutes or whatever. And this just really fast feedback cycle, it encourages people to give more and more feedback. It's just so important because it makes them feel heard. Usually when you use a product, you give feedback, it just goes into a black hole somewhere and then you don't give feedback again. So if you make people feel heard, then they want to contribute and they want to help make the thing better.
**Boris Cherny：** 现在我做着同样的事情，但大部分工作其实是 Claude 在做。我把它指向那个频道，它会说："好的，这里有几件我可以做的事情，我已经提了几个 PR，你要看看吗？"我说："好的。"
**Boris Cherny:** And so now I kind of do the same thing, but Claude honestly does a lot of the work. So I point it at the channel and it's like, "Okay, here's a few things that I can do. I just put up a couple PRs. Want to take a look at that one?" I'm like, "Yeah."
**Lenny：** 你有没有注意到它在这方面变得好很多了？因为这某种程度上是圣杯对吧？现在的状态是"好了，构建的问题解决了。"代码审查成了下一个瓶颈——这么多 PR，谁来审查？再下一个大问题就是"好了，现在我们还需要人类来决定做什么、如何排优先级。"你说的就是 Claude Code 正在开始帮你做这件事。它有没有在最近的版本比如 Opus 4.6 中有很大提升？进展轨迹是怎样的？
**Lenny:** Have you noticed that it is getting much better at this? Because this is kind of the holy grail, right? Now it's like, "Cool, building solved." Code review became kind of the next bottleneck. All these PRs, who's going to review them all? The next big open question is just like, okay, now we need to -- now humans are necessary for figuring out what to build, what to prioritize. And you're saying that that's where Claude Code is starting to help you. Has it gotten a lot better with like say Opus 4.6 or what's been the trajectory there?
**Boris Cherny：** 是的，改善非常大。一部分是我们针对编程做的专项训练。当然，这是世界上最好的编程模型，而且还在不断变好。4.6 简直不可思议。但实际上，我们在编程之外所做的训练也能很好地迁移过来。存在一种迁移效应（transfer）——你教模型做 X，它在 Y 上也会变好。
**Boris Cherny:** Yeah. Yeah, it's improved a lot. I think some of it is kind of like training that we do specific to coding. So obviously best coding model in the world and it's getting better and better. Like 4.6 is just incredible. But also actually a lot of the training that we do outside of coding translates pretty well too. So there is this kind of like transfer where you teach the model to do X and it kind of gets better at Y.
**Boris Cherny：** 而且增益简直是疯狂的。在 Anthropic，自从引入 Claude Code 以来的这一年里——我不知道确切数字——我们的工程团队大概扩大了四倍，但每位工程师的生产力提升了200%。
**Boris Cherny:** Yeah and the gains have just been insane. Like at Anthropic over the last year since we introduced Claude Code we probably -- I don't know the exact number -- we probably like 4x the engineering team or something like this but productivity per engineer has increased 200%.
**Boris Cherny：** 按拉取请求来衡量的话——这个数字对任何真正在这个领域工作、做开发者生产力的人来说都是疯狂的。在我之前的职业生涯中，我在 Meta 工作，我的职责之一是整个公司的代码质量——所有代码库都是我负责的：Facebook、Instagram、WhatsApp 所有这些。其中很大一部分是关于生产力的，因为如果你提高代码质量，工程师就会更高效。当时的情况是，几百名工程师投入一年的工作，你可能会看到几个百分点的生产力提升。
**Boris Cherny:** In terms of pull requests -- and this number is just crazy for anyone that actually works in the space and works on dev productivity because back in a previous life I was at Meta and one of my responsibilities was code quality for the company. So this is like all of our code bases -- that was my responsibility. Like Facebook, Instagram, WhatsApp all this stuff. And a lot of that was about productivity because if you make the code higher quality then engineers are more productive. And things that we saw is in a year with hundreds of engineers working on it you would see a gain of like a few percentage points of productivity something like this.
**Boris Cherny：** 所以现在看到几百个百分点的提升，这简直是不可思议。
**Boris Cherny:** And so nowadays seeing these gains of just hundreds of percentage points it's just absolutely insane.
**Lenny：** 同样不可思议的是这一切变得多么正常。我们听到这些数字——"AI 当然在做这些事情"。这是前所未有的变化量级，正在发生在软件开发、产品构建、整个科技世界中。我们太容易习以为常了。但重要的是要认识到——这是疯狂的。我时不时需要提醒自己。
**Lenny:** What's also insane is just how normalized this has all been. Like we hear these numbers -- like of course AI is doing this to us. It's just so unprecedented the amount of change that is happening to software development, to building products, to just the world of tech. It's just like so easy to get used to it. But it's important to recognize this is crazy. This is something like I have to remind myself once in a while.
**Boris Cherny：** 这也有一些副作用。因为模型变化太快了。其实有很多我们可以谈论的副作用，但我觉得从个人层面来说，其中一个是模型变化太频繁，我有时会被困在旧的思维方式中。我甚至发现团队里的新人，甚至刚毕业的新员工，在使用 AI 的方式上比我更"AGI 优先"。
**Boris Cherny:** There's sort of like a downside of this because the model changes so fast. There's actually many kind of downsides that we could talk about but I think one of them on a personal level is the model changes so often that I sometimes get stuck in this old way of thinking about it and I even find that new people on the team or even new grads that join do stuff in a more kind of AGI-forward way than I do.
**Boris Cherny：** 比如几个月前我遇到了一个内存泄漏（memory leak）的问题——Claude Code 的内存使用量不断上升，最终会崩溃。这是一个非常常见的工程问题，每个工程师都调试过无数次。
**Boris Cherny:** So like sometimes for example I had this case a couple months ago where there was a memory leak. So what this is -- Claude Code's memory usage is going up and at some point it crashes. This is a very common kind of engineering problem that every engineer has debugged a thousand times.
**Boris Cherny：** 传统的做法是你拿一个堆快照（heap snapshot），放到专门的调试器里，用各种专门的工具来分析到底发生了什么。我就是这么做的——我在翻看这些跟踪记录，试图弄明白是怎么回事。
**Boris Cherny:** And traditionally the way that you do it is you take a heap snapshot, you put it into a special debugger, you kind of figure out what's going on, use these special tools to see what's happening. And I was doing this and I was kind of looking through these traces and trying to figure out what was going on.
**Boris Cherny：** 而那个新加入团队的工程师直接让 Claude Code 来做——"嘿 Claude，好像有内存泄漏，你能查一下吗？"Claude Code 做了和我一模一样的事情：它拿了堆快照，为自己编写了一个分析工具——一种即时生成的程序。然后它找到了问题并提交了一个 PR，比我更快。
**Boris Cherny:** And the engineer that was newer on the team just had Claude Code do it and was like, "Hey Claude, it seems like there's a leak. Can you figure it out?" And so Claude Code did exactly the same thing that I was doing. It took the heap snapshot. It wrote a little tool for itself so it could analyze it itself. It was sort of like a just-in-time program. And it found the issue and put up a pull request faster than I could.
**Boris Cherny：** 所以对于我们这些长期使用模型的人来说，你仍然需要把自己拉回到当下，不要停留在旧模型的思维里。现在已经不是 Sonnet 3.5 了。新模型完全完全不一样了。这种心态转换非常关键。
**Boris Cherny:** So it's something where for those of us that have been using the model for a long time, you still have to kind of transport yourself to the current moment and not get stuck back in an old model because it's not Sonnet 3.5 anymore. The new models are just completely completely different. And just this mindset shift is very different.
**Lenny：** 我听说你有一些非常具体的原则，已经为团队明确写了出来。每当有人加入，你会带他们过一遍。我记得其中一条是——"什么比做一件事更好？让 Claude 来做。"你刚才描述的内存泄漏的例子就是这条原则的完美体现——你几乎忘了"让我先看看 Claude 能不能解决这个问题"。
**Lenny:** I hear you have these very specific principles that you've codified for your team that when people join you kind of walk them through them. I believe one of them is what's better than doing something -- having Claude do it. And it feels like that's exactly what you describe with this memory leak is just like you almost forgot that principle of like okay let me see if Claude can solve this for me.
**Boris Cherny：** 还有一个有趣的现象——当你有意少配一点资源的时候，人们就会被迫去"Claude 化"（Claudify）自己的工作。这是我们反复看到的。有些项目我们就安排一个工程师，而他们之所以能够快速交付，是因为他们真的想快速交付。这是一种发自内心的内在动力——就是想把事情做好。
**Boris Cherny:** There's this interesting thing that happens also when you underfund everything a little bit because then people are kind of forced to Claudify and this is something that we see. So for work where sometimes we just put like one engineer on a project and the way that they're able to ship really quickly because they want to ship quickly. This is like an intrinsic motivation that comes from within -- just wanting to do a good job.
**Boris Cherny：** 如果你有一个好想法，你就是想赶紧把它推出去。没有人需要强迫你，这来自你自己。如果你有 Claude，你就可以用它来自动化很多工作。这是我们反复看到的模式。
**Boris Cherny:** If you have a good idea you just really want to get it out there. No one has to force you to do that. That comes from you. And so if you have Claude, you can just use that to automate a lot of work. And that's kind of what we see over and over.
**Boris Cherny：** 所以我觉得这是其中一条原则——有意少配资源。另一条原则是鼓励大家加快速度。如果你今天就能做一件事，那你就应该今天就做。这是我们在团队中非常非常强调的。早期这一点尤其重要，因为当时只有我一个人，我们唯一的优势就是速度。这是我们在这个竞争异常激烈的编程工具市场中生存的唯一方式。
**Boris Cherny:** So I think that's kind of like one principle -- underfunding things a little bit. I think another principle is just encouraging people to go faster. So if you can do something today, you should just do it today. And this is something we really really encourage on the team. Early on it was really important because it was just me and so our only advantage was speed. That's the only way that we could ship a product that would compete in this very crowded coding market.
**Boris Cherny：** 到了今天，这仍然是我们团队的核心原则。如果你想更快，一个很好的方法就是让 Claude 做更多的事情。所以这自然就鼓励了这种做法。
**Boris Cherny:** But nowadays, it's still very much a principle we have on the team. And if you want to go faster, a really good way to do that is to just have Claude do more stuff. So it just very much encourages that.
**Lenny：** "有意少配资源"这个想法非常有趣。一般的感觉是 AI 会让你不需要那么多员工、不需要那么多工程师。所以这不仅仅是"你可以更高效"。你说的是——如果你有意少配资源，效果反而会更好。不只是 AI 能让你更快，而是如果参与的人更少，你反而能从 AI 工具中获得更多。
**Lenny:** This idea of underfunding, it's so interesting because in general there's this feeling like AI is going to allow you to not have as many employees, not have as many engineers. And so it's not only you can be more productive. What you're saying is that you will actually do better if you underfund. It's not just that AI can make you faster. It's you will get more out of the AI tooling if you have fewer people working on something.
**Boris Cherny：** 是的。如果你雇佣优秀的工程师，他们会想办法搞定的。尤其是如果你赋能他们去做。
**Boris Cherny:** Yeah. If you hire great engineers, they'll figure out how to do it. And especially if you empower them to do it.
**Boris Cherny：** 这是我经常和 CTO 们以及各种公司讨论的话题。我的一般建议是——不要一上来就试图优化、试图削减成本。先给工程师尽可能多的 token（调用额度）。现在你开始看到一些公司——比如在 Anthropic，每个人都可以使用大量的 token。我们开始看到这成为一些公司的福利，比如"加入我们，你会获得无限 token"。
**Boris Cherny:** This is something I actually talk a lot about with CTOs and kind of all sorts of companies. My advice generally is don't try to optimize. Don't try to cost cut at the beginning. Start by just giving engineers as many tokens as possible. And now you're starting to see companies -- like at Anthropic we have everyone can use a lot of tokens. We're starting to see this come up as like a perk at some companies. Like if you join you get unlimited tokens.
**Boris Cherny：** 这是我非常鼓励的做法。因为它让人们可以自由尝试那些原本觉得太疯狂的想法。如果某个想法可行，你再去想如何扩展它，那才是优化和削减成本的时候——比如看看能不能用 Haiku 或 Sonnet 代替 Opus。但在一开始，你就是要往上面砸大量 token，看看想法是否可行，给工程师这样的自由。
**Boris Cherny:** This is a thing I very much encourage because it makes people free to try these ideas that would have been too crazy and then if there's an idea that works then you can figure out how to scale it and that's the point to kind of optimize and to cost cut. Figure out like maybe you can do it with Haiku or with Sonnet instead of Opus or whatever. But at the beginning you just want to throw a lot of tokens at it and see if the idea works and give engineers the freedom to do that.
**Lenny：** 所以你的建议是对使用模型的成本要大方一些。听到这话的人可能会想"当然了，他在 Anthropic 工作，当然希望我们用尽可能多的 token"。但你真正想说的是——最有趣、最创新的想法会来自于那些把模型使用推到极致、探索可能性边界的人。
**Lenny:** So the advice here is just be loose with your tokens with the cost on using these models. People hearing this may be like of course he works at Anthropic. He wants us to use as many tokens as possible. But what you're saying here is the most interesting innovative ideas will come out of someone just kind of taking it to the max and seeing what's possible.
**Boris Cherny：** 是的。而且现实是，在小规模使用时你不会收到一张巨额账单。如果只是一个工程师在实验，token 成本相对于他们的工资或者运营业务的其他成本来说仍然是相当低的。所以这实际上不是一笔很大的开支。当项目扩展起来的时候——比如他们做了一个很棒的东西，然后它需要大量的 token，成本变得很高——那才是你需要优化的时候。但不要太早做优化。
**Boris Cherny:** Yeah. And I think the reality is like at small scale you're not going to get like a giant bill or anything like this. Like if it's an individual engineer experimenting, the token cost is still probably relatively low relative to their salary or other costs of running the business. So it's actually not a huge cost. As the thing scales up -- so let's say they build something awesome and then it takes a huge amount of tokens and then the cost becomes pretty big. That's the point at which you want to optimize it. But don't do that too early.
**Lenny：** 你有没有见过公司的 token 成本超过工资的情况？你觉得这会成为趋势吗？
**Lenny:** Have you seen companies where their token cost is higher than their salary? Is that a trend you think we're going to find and see?
**Boris Cherny：** 嗯，在 Anthropic，我们开始看到一些工程师每月的 token 消耗达到数十万美元。所以我们确实在看到这种趋势的苗头。有一些公司也在出现类似的情况。
**Boris Cherny:** You know, at Anthropic, we're starting to see some engineers that are spending, you know, like hundreds of thousands a month in tokens. So we're starting to see this a little bit. There's some companies that we're starting to see similar things. Yeah.
**Lenny：** 回到编程的话题，你会怀念写代码吗？作为一名软件工程师，你会因为写代码这件事不再存在而感到遗憾吗？
**Lenny:** Going back to coding, do you miss writing code? Is this something you're kind of sad about that this is no longer a thing you will do as a software engineer?
**Boris Cherny：** 对我来说挺有意思的。我学工程一直是很务实的——我学编程是为了能做出东西。我是自学的。大学学的经济学，不是计算机科学，但我很早就自学了编程——中学时期就开始了。从一开始就非常务实。其实我学编程的第一个目的是为了在数学考试中作弊。我们有那种图形计算器，我就把答案编程进去——
**Boris Cherny:** It's funny for me. When I learned engineering, for me it was very practical. I learned engineering so I could build stuff and for me I was self-taught. I studied economics in school, but I didn't study CS, but I taught myself engineering kind of early on. I was programming in like middle school and from the very beginning it was very practical. So I actually learned to code so that I can cheat on a math test. That was like the first thing. We had these graphing calculators and I just programmed the answer into --
**Lenny：** TI-83。
**Lenny:** TI-83.
**Boris Cherny：** TI-83 Plus。没错。
**Boris Cherny:** TI-83 Plus. Yeah. Yeah. Exactly.
**Lenny：** Plus。对。
**Lenny:** Plus. Yeah.
**Boris Cherny：** 我把答案编进去了。然后第二年的数学考试太难了，我没办法把所有答案都编进去，因为我不知道题目是什么。所以我不得不写一个小求解器——一个能解代数题之类问题的程序。然后我发现可以用一根数据线把这个程序传给全班同学，然后全班都考了A。不过后来我们被抓了，老师让我们不许再这么做。
**Boris Cherny:** So I programmed the answers in and then the next math test whatever the next year that it was just too hard. I couldn't program all the answers in because I didn't know what the questions were. And so I had to write a little solver so that it was a program that would just solve these algebra questions or whatever. And then I figured out you can get a little cable, you can give the program to the rest of the class and then the whole class gets A's. But then we all got caught and the teacher told us to knock it off.
**Boris Cherny：** 但从一开始，对我来说编程就一直是非常务实的——编程是构建东西的手段，不是目的本身。有一段时间我确实掉进了编程之美的兔子洞。我写了一本关于 TypeScript 的书，还创办了当时世界上最大的 TypeScript 聚会，因为我爱上了这门语言本身。我深深沉浸在函数式编程（functional programming）这些东西里。
**Boris Cherny:** But from the very beginning it's always just been very practical for me where programming is a way to build a thing. It's not the end in itself. At some point I personally fell into the rabbit hole of the beauty of programming. So I wrote a book about TypeScript. I started the -- actually at the time it was the world's biggest TypeScript meetup just because I fell in love with the language itself. And I kind of got in deep into functional programming and all this stuff.
**Boris Cherny：** 我觉得很多程序员会被这些东西分散注意力。对我来说——编程确实有它的美，尤其是函数式编程。类型系统（type system）有一种美感。解决一个复杂数学问题时那种兴奋感，和你把类型平衡好、程序写得很漂亮时的感觉很像。但这真的不是最终目的。
**Boris Cherny:** I think a lot of coders they get distracted by this. For me, it was always sort of -- there is a beauty to programming and especially to functional programming. There's a beauty to type systems. There's a certain kind of buzz that you get when you solve a really complicated math problem. It's kind of similar when you kind of balance the types or the program is just really beautiful. But it's really not the end of it.
**Boris Cherny：** 对我来说编程就是一个工具，一种做事的方式。话虽如此，不是每个人都这么想。比如团队里有一位工程师 Lena，她周末仍然会手写 C++，因为她就是很享受手写 C++ 的过程。每个人都不一样。我觉得即使这个领域在变、即使一切都在变，总有空间去做这些事，总有空间去欣赏这门手艺，如果你想的话。
**Boris Cherny:** I think for me coding is very much a tool and it's a way to do things. That said not everyone feels this way. So for example there's one engineer on the team Lena who was still writing C++ on the weekends by hand because for her she just really enjoys writing C++ by hand. And so everyone is different and I think even as this field changes, even as everything changes, there's always space to do this, there's always space to enjoy the art and to do things by hand if you want.
**Lenny：** 你会担心自己作为工程师的技能退化吗？这是你担心的事情，还是你觉得"这就是趋势"？
**Lenny:** Do you worry about your skills atrophying as an engineer? Is that something you worry about or is it just like, you know, this is just the way it's going to go?
**Boris Cherny：** 我觉得这就是自然演进的过程。我个人不太担心。对我来说编程是一个连续的进化过程。回顾历史，软件其实是相对较新的事物。今天我们写程序的方式——运行在虚拟机上的软件——大概从1960年代开始，也就60年左右。在那之前是打孔卡（punch card），更早是开关，再早是硬件，最早就是纸和笔——一屋子的人在纸上做数学运算。
**Boris Cherny:** I think it's just the way that it happens. I don't worry about it too much personally. I think for me programming is on a continuum and way back in the day software actually is relatively new, right? If you look at the way programs are written today using software that's running on a virtual machine or something, this has been the way that we've been writing programs since probably the 1960s. So it's been like 60 years or something like that. Before that it was punch cards. Before that it was switches. Before that it was hardware. And before that it was just literally pen and paper. It was a room full of people that were doing math on paper.
**Boris Cherny：** 编程一直都在这样变化。从某种意义上说，你仍然想理解底层的那一层，因为它能让你成为更好的工程师。我觉得在未来一年左右这仍然会是这样。但我认为很快它就不再重要了——它就会变成像汇编代码（assembly code）运行在程序员之下那样的存在。
**Boris Cherny:** And so programming has always changed in this way. In some ways, you still want to understand the layer under the layer because it helps you be a better engineer. And I think this will be the case maybe for the next year or so. But I think pretty soon it just won't really matter. It's just going to be kind of like the assembly code running under the programmer or something like this.
**Boris Cherny：** 从情感层面上讲，我觉得我一直都在学新东西。作为程序员，这种感觉其实并不陌生，因为总有新框架、新语言出现。这是我们这个领域早已习惯的事情。但与此同时，不是每个人都这样。对一些人来说，他们可能会有更强烈的失落感、怀旧感或者技能退化的担忧。
**Boris Cherny:** At an emotional level, I feel like I've always had to learn new things. And as a programmer, it's actually not -- it doesn't feel that new because there's always new frameworks, there's always new languages. It's just something that we're quite comfortable with in the field. But at the same time, this isn't true for everyone. And I think for some people, they're going to feel a greater sense of, I don't know, maybe like loss or nostalgia or atrophy or something like this.
**Lenny：** 不知道你有没有看到，Elon 说过"为什么 AI 不直接写二进制——直接写二进制代码？所有这些编程抽象层最终有什么意义？"
**Lenny:** I don't know if you saw this, but Elon was saying that why isn't the AI just writing binary -- straight to binary? Because what's the point of all this programming abstraction in the end?
**Boris Cherny：** 是的，这是个好问题。如果你想的话，AI 完全可以做到。
**Boris Cherny:** Yeah, it's a good question. I mean, it totally can do that if you wanted to.
**Lenny：** 天哪。所以，我从你的话中听出——关于"我该不该学编程"这个一直存在的问题——你的观点是再过一两年，真的不需要了。
**Lenny:** Oh, man. So, what I'm hearing here is in terms -- there's always this question, should I learn to code? Should people in school learn to code? What I heard from you is your take is in like a year or two, you don't really need to.
**Boris Cherny：** 我的观点是，对于今天正在使用 Claude Code、使用智能体来编程的人来说，你仍然需要理解底层。但一两年后，这就不重要了。
**Boris Cherny:** My take is I think for people that are using Claude Code that are using agents to code today you still have to understand the layer under. But yeah in a year or two it's not going to matter.
**Boris Cherny：** 我一直在思考什么是合适的历史类比，因为我们需要把这件事放到历史中去定位，找到我们经历过的类似转型。什么是正确的心智模型？我认为最接近的是印刷术。
**Boris Cherny:** I was thinking about what is the right historical analog for this because somehow we have to situate this thing in history and figure out when have we gone through similar transitions. What's the right kind of mental model for this? I think the thing that's come closest for me is the printing press.
**Boris Cherny：** 看看15世纪中期的欧洲，当时的识字率其实非常低，不到人口的1%。是抄写员（scribe）在做所有的书写和阅读工作。他们受雇于领主和国王——而这些领主和国王自己往往不识字。所以这是一个极小比例的人群在做这件事。
**Boris Cherny:** And so if you look at Europe in the mid-1400s literacy was actually very low. It was sub 1% of the population. It was scribes that did all the writing. They were the ones that did all the reading. They were employed by lords and kings that often were not literate themselves. And so it was the job of this very tiny percent of the population to do this.
**Boris Cherny：** 后来古腾堡（Gutenberg）和印刷术出现了。有一个疯狂的统计数据：在印刷术发明后的50年里，产生的印刷材料比之前一千年的总和还多。印刷材料的数量急剧上升，成本大幅下降——在随后的50年里下降了大约100倍。
**Boris Cherny:** And at some point Gutenberg and the printing press came along and there was this crazy stat that in the 50 years after the printing press was built there was more printed material created than in the thousand years before. And so the volume of printed material just went way up. The cost went way down. It went down something like 100x over the next 50 years.
**Boris Cherny：** 至于识字率，它其实花了很长时间才提上去，因为学习读写是很难的。需要教育体系，需要空闲时间，需要不用整天在田里干活才能有时间接受教育。但在随后的200年里，全球识字率上升到了大约70%。
**Boris Cherny:** And if you look at literacy, it actually took a while because learning to read and write is quite hard. It takes an education system. It takes free time. It takes not having to work on a farm all day so that you actually have time for education and things like this. But over the next 200 years, it went up to like 70% globally.
**Boris Cherny：** 所以我觉得我们可能会看到类似的转型。有一份很有趣的历史文献，里面有一段对15世纪某位抄写员的采访——问他对印刷术怎么看。他其实非常兴奋，因为他说"我不喜欢做的事情是在书本之间抄写。我喜欢做的是在书里画插图和做装帧。我很高兴现在我的时间被释放出来了。"
**Boris Cherny:** So I think this is the kind of thing that we might see -- a similar kind of transition. And there was actually this interesting historical document where there was an interview with some scribe in the 1400s about how do you feel about the printing press? And they were actually very excited because they were like actually the thing that I don't like doing is copying between books. The thing that I do like doing is drawing the art in books and then doing the book binding. And I'm really glad that now my time is freed up.
**Boris Cherny：** 有趣的是，作为工程师，我感到了一种相似的共鸣。我也是这种感觉——我不再需要做编程中那些繁琐的工作了，因为编程一直以来就有它的繁琐之处——处理 git、使用各种工具——那不是有趣的部分。有趣的部分是弄清楚该做什么、提出构想、与用户交流、思考大型系统、思考未来、与团队中的其他人协作。而现在我可以把更多时间花在这些事情上。
**Boris Cherny:** And it's interesting -- as an engineer I sort of felt a parallel with this. It's like this is sort of how I feel where I don't have to do the tedious work anymore of coding because this has always been sort of the detail of it. It's always been the tedious part of it and kind of messing with git and using all these different tools. That was not the fun part. The fun part is figuring out what to build and coming up with this. It's talking to users. It's thinking about these big systems. It's thinking about the future. It's collaborating with other people on the team. And that's what I get to do more of now.
**Lenny：** 更了不起的是，你正在构建的工具让任何人都可以做到这一点。没有技术背景的人也可以做你描述的事情。我自己一直在做各种小项目，每次卡住了就说"帮我弄清楚这个"，然后就能继续了。
**Lenny:** And what's amazing is that the tool you're building allows anybody to do this. People that have no technical experience can do exactly what you're describing. Like I've been doing a bunch of random little projects and anytime you get stuck just like help me figure this out and you get unblocked.
**Lenny：** 我曾经做过工程师——职业生涯早期做了10年——我记得花了大量时间在库、依赖项上，然后就是"天哪我该怎么办"，然后去 Stack Overflow 上查。现在就只需要说"帮我弄清楚这个"，然后它一步一步地告诉你——一、二、三、四——搞定了。
**Lenny:** Like I used to -- I was an engineer early in my career for 10 years and I just remember spending so much time on like libraries and dependencies and things and just like oh my god what do I do and then looking on Stack Overflow and now it's just like help me figure this out and here's step by step one two three four okay we got this.
**Boris Cherny：** 没错。我今天早些时候和一个工程师聊天，他在用 Go 写一个服务，已经大概一个月了，服务搭起来了，运行得还不错。然后我问"你写 Go 的感觉怎么样？"他说"你知道吗，我其实还是不太会 Go，但是......"（笑）我觉得我们会越来越多地看到这种情况。如果你知道代码是正确的、高效的，那你其实不需要了解所有的细节。
**Boris Cherny:** Yeah, exactly, exactly. I was talking to an engineer earlier today, they're like, they're writing some service in Go and, you know, it's been like a month already and they built up the service, like it's working quite well. And then I was like, "Okay, so like, how do you feel writing it?" He was like, "You know, like, I still don't really know Go, but..." [laughter] And I think we're going to start to see more and more of this. It's like, if you know that it works correctly and efficiently, then you don't actually have to know all the details.
**Lenny：** 显然，软件工程师的职业已经发生了巨大变化。过去一两年里这已经变成了一份全新的工作。你觉得下一个受 AI 影响最大的角色会是什么？是在科技行业内部——比如产品经理、设计师——还是科技行业之外？你觉得 AI 接下来会走向哪里？
**Lenny:** Clearly, the life of a software engineer has changed dramatically. It's like a whole new job now as of the past year or two. What do you think is the next role that will be most impacted by AI within either within tech, like, you know, product managers, designers, or even outside tech? Just like, what do you think, where do you think AI is going next?
**Boris Cherny：** 我觉得会是很多与工程相邻的角色。比如产品经理、设计、数据科学。它会扩展到几乎任何可以在电脑上完成的工作，因为模型会越来越擅长这些。co-work 这个产品是实现这一目标的第一种方式，但它只是第一个。我认为它是第一次把智能体式的 AI 带给那些之前没有真正用过的人，人们正在第一次感受到它的力量。
**Boris Cherny:** I think it's going to be a lot of the roles that are adjacent to engineering. So yeah, it could be like product managers, it could be design, could be data science. It is going to expand to pretty much any kind of work that you can do on a computer because the models are just going to get better and better at this. And, you know, like, this co-work product is kind of the first way to get at this, but it's just the first one. And it's the thing that I think brings AI, agentic AI, to people that haven't really used it before, and people are starting just to get a sense of it for the first time.
**Boris Cherny：** 回想一年前的工程领域，没有人真正知道什么是智能体，也没有人真正用过。但现在，这就是我们的工作方式。再看看今天的非技术性工作——或者说半技术性的，比如产品工作和数据科学——人们使用的 AI 都是对话式的，就像聊天机器人，但没有人真正用过智能体。
**Boris Cherny:** When I think back to engineering a year ago, no one really knew what an agent was. No one really used it. But nowadays, it's just the way that, you know, we do our work. And then when I look at non-technical work today, so, you know, like, or maybe semi-technical like product work and, you know, like data science and things like this, when you look at the kinds of AI that people are using, it's always these like conversational AI, it's like a chatbot or whatever, but no one really has used an agent before.
**Boris Cherny：** "智能体"这个词到处被滥用，已经失去了意义。但智能体其实有一个非常具体的技术含义——它是一个能够使用工具的 AI，是一个能使用工具的大语言模型（LLM）。它不只是对话，它能实际行动，能与你的系统交互。这意味着它可以使用你的 Google Docs、发邮件、在你的电脑上运行命令。所以我认为任何涉及使用电脑工具的工作都会是下一个被改变的。
**Boris Cherny:** And this word "agent" just gets thrown around all the time and it's just so misused, it's like lost all meaning. But agent actually has a very specific technical meaning, which is it's an AI, it's an LLM that's able to use tools. So it doesn't just talk, it can actually act, and it can interact with your system. And, you know, this means like it can use your Google Docs and it can send email. It can run commands on your computer and do all this kind of stuff. So I think like any kind of job where you use computer tools in this way, I think this is going to be next.
**Boris Cherny：** 这是我们作为社会需要共同面对的问题，作为行业也是。对我来说，这也是在 Anthropic 做这项工作感觉非常重要和紧迫的原因之一，因为我认为我们对此非常非常认真。我们现在有经济学家、有政策专家、有社会影响研究人员。我们希望广泛讨论这些问题，让社会共同决定该怎么做——因为这不应该由我们来决定。
**Boris Cherny:** This is something we have to kind of figure out as a society. This is something we have to figure out as an industry. And I think for me also this is one of the reasons it feels very important and urgent to do this work at Anthropic, because I think we take this very, very seriously. And so now, you know, we have economists, we have policy folks, we have social impact folks. This is something we just want to talk about a lot so as a society we can kind of figure out what to do, because it shouldn't be up to us.
**Lenny：** 你暗示的那个大问题就是就业和失业之类的。有一个叫杰文斯悖论（Jevons paradox）的概念——当我们能做更多的时候，我们反而会雇更多人，所以事情并没有看起来那么可怕。到目前为止，随着 AI 成为工程工作的重要组成部分，你实际看到了什么？你们是比没有 AI 的情况下招了更多人吗？对就业问题有什么看法？
**Lenny:** So the big question which you're kind of alluding to is jobs and job loss and things like that. There's this concept of Jevons paradox of just as we can do more, we hire more, and it's not actually as scary as it looks. What have you experienced so far, I guess, with AI becoming a big part of the engineering job? Just, are you hiring more than if you didn't have AI, and just thoughts on jobs?
**Boris Cherny：** 是的，就我们团队而言，我们正在招人。Claude Code 团队在招人。如果你感兴趣，可以去 Anthropic 的招聘页面看看。就我个人而言，这一切只是让我更享受工作了。我从来没有像今天这样享受编程，因为我不用再处理那些琐碎的事情。所以对我个人来说，这一切都非常令人兴奋。我们从很多客户那里听到同样的话——他们喜欢这个工具，喜欢 Claude Code，因为它让编程重新变得愉悦了。
**Boris Cherny:** Yeah, I mean, for our team we're hiring. So the Claude Code team is hiring. If you're interested, just check out the jobs page on Anthropic. Personally, it's, you know, all this stuff has just made me enjoy my work more. I have never enjoyed coding as much as I do today because I don't have to deal with all the minutiae. So, for me personally, it's been quite exciting. This is something that we hear from a lot of customers where they love the tool, they love Claude Code because it just makes coding delightful again. And that's just so fun for them.
**Boris Cherny：** 但很难知道未来会走向哪里。我还是得借助历史类比。我觉得印刷术就是一个非常好的类比。当时发生的是，一项被锁定在少数人手中的技术——识字——变成了所有人都能使用的。它本质上是民主化的。如果不是这样，文艺复兴就不可能发生。因为文艺复兴的很大一部分是关于知识的传播、关于人们用来交流的文字记录——毕竟当时没有电话、没有互联网。
**Boris Cherny:** But it's hard to know where this thing is going to go. And I again, I just like, I have to reach for these historical analogies. And I think the printing press is just such a good one because what happened is this technology that was locked away to a small set of people -- like knowing how to read and write -- became accessible to everyone. It was just inherently democratizing. Everyone started to be able to do this. And if that wasn't the case, then something like the Renaissance just could never have happened because a lot of the Renaissance, it was about knowledge spreading. It was about written records that people used to communicate. You know, because there were no phones or anything like this. There was no internet at the time.
**Boris Cherny：** 所以关键在于——这会带来什么新的可能？这是我非常乐观的版本，也是最令我兴奋的部分。简直无法想象。如果没有印刷术的发明，我们今天就不可能在这里对话。我们的麦克风不会存在，我们周围的一切都不会存在。如果没有印刷术，就不可能协调如此大规模的人群。所以我想象的是，几年后，每个人都能编程。那会解锁什么？任何人随时都能构建软件。我完全不知道答案。就像15世纪的人无法预测后来发生的一切一样。
**Boris Cherny:** So, it's about like, what does this enable next? And I think that's the very optimistic version of it for me. And that's the part that I'm really excited about. It's just unimaginable, you know, like we couldn't be talking today if the printing press hadn't been invented. Like our microphones wouldn't exist. None of the things around us would exist. It just wouldn't be possible to coordinate such a large group of people if that wasn't the case. And so I imagine a world, you know, a few years in the future where everyone is able to program. And what does that unlock? Anyone can just build software anytime. And I have no idea. It's just the same way that, you know, in the 1400s, no one could have predicted this. I think it's the same way.
**Boris Cherny：** 但我确实认为在此期间，这会带来很大的颠覆，对很多人来说会是痛苦的。作为一个社会，这是我们必须进行的对话，必须共同面对的问题。
**Boris Cherny:** But I do think in the meantime, it's going to be very disruptive and it's going to be painful for a lot of people. And again, as a society, this is a conversation that we have to have and this is a thing that we have to figure out together.
**Lenny：** 对于那些想要成功、想在我们即将进入的这场疯狂变革中生存下来的人，你有什么建议？是去玩 AI 工具、精通最新的东西吗？还有什么建议可以帮助人们保持领先？
**Lenny:** So, for folks hearing this that want to succeed and, you know, make it in this crazy turmoil we're entering, any advice? Is it, you know, play with AI tools, get really proficient at the latest stuff? Is there anything else that you recommend to help people stay ahead?
**Boris Cherny：** 是的，基本上就是这样。去实验、去了解这些工具、不要害怕它们。大胆尝试，走在最前沿。第二条建议可能是——比以往更加注重做一个通才（generalist）。比如在学校里，很多学计算机的人只学了编程，没怎么学其他的。也许学了一点系统架构之类的。
**Boris Cherny:** Yeah, I think that's pretty much it. Experiment with the tools, get to know them, don't be scared of them. Just, you know, dive in, try them, be on the bleeding edge, be on the frontier. Maybe the second piece of advice is try to be a generalist more than you have in the past. For example, in school, a lot of people that study CS, they learn to code and they don't really learn much else. Maybe they learn a little bit of systems architecture or something like this.
**Boris Cherny：** 但我每天一起工作的那些最有效率的工程师，以及最优秀的产品经理，他们都是跨学科的。在 Claude Code 团队里，每个人都写代码。我们的产品经理写代码，工程经理写代码，设计师写代码，财务的同事写代码，数据科学家写代码——团队里每个人都写代码。
**Boris Cherny:** But some of the most effective engineers that I work with every day and some of the most effective, you know, like product managers and so on, they cross over disciplines. So on the Claude Code team, everyone codes. You know, our product manager codes, our engineering manager codes, our designer codes, our finance guy codes, our data scientist codes. Like everyone on the team codes.
**Boris Cherny：** 具体到个别工程师，人们经常跨越不同学科。一些最强的工程师既做产品又做基础设施，或者是有出色设计感的产品工程师——他们也能做设计，或者是对商业有很好理解的工程师——能用商业洞察来决定下一步该做什么，或者是喜欢和用户交流的工程师——能真正理解用户想要什么来决定方向。
**Boris Cherny:** And then if I look at particular engineers, people often cross different disciplines. So some of the strongest engineers are hybrid product and infrastructure engineers, or product engineers with really great design sense and they're able to do design also, or an engineer that has a really good sense of the business and can use that to figure out what to do next, or an engineer that also loves talking to users and can just really channel what users want to figure out what's next.
**Boris Cherny：** 所以我认为未来几年会获得最大回报的人，不仅仅是 AI 原生（AI native）的、善于使用这些工具的，同时也是充满好奇心的通才，跨越多个学科，能思考更宏观的问题而不仅仅是工程部分。
**Boris Cherny:** So I think a lot of the people that will be rewarded the most over the next few years, they won't just be AI native and they don't just know how to use these tools really well, but also they're curious and they're generalists and they cross over multiple disciplines and can think about the broader problem they're solving rather than just the engineering part of it.
**Lenny：** 你觉得这三个独立的学科——工程、设计、产品管理——作为思考团队的方式还有用吗？虽然他们现在也写代码、也参与决定做什么，但你觉得这三个角色长期来看还会存在吗？
**Lenny:** Do you find these three separate disciplines still useful as a way to think about the team? They're, you know, engineering, design, product management. Do you find like those, even though they are now coding and contributing to thinking about what to build, do you feel like those are three roles that will persist long term, at least at this point?
**Boris Cherny：** 短期内还会存在，但我们开始看到的一件事是，这些角色之间可能有50%的重叠——很多人其实在做同样的事情，只是一些人有专长。比如我写更多代码，而我们的项目负责人则做更多的协调、规划、预测之类的工作。
**Boris Cherny:** I think in the short term it'll persist, but one thing that we're starting to see is there's maybe a 50% overlap in these roles where a lot of people are actually just doing the same thing and some people have specialties. For example, I code a little bit more versus our RPM does a little bit more, you know, coordination or planning or, you know, forecasting or things like this.
**Lenny：** 利益相关方对齐（stakeholder alignment）。
**Lenny:** Stakeholder alignment.
**Boris Cherny：** 利益相关方对齐。没错。我确实认为到年底我们会开始看到这些角色的界限变得更加模糊。在一些地方，"软件工程师"这个头衔会开始消失，取而代之的是"构建者"，或者也许是人人都成为产品经理、人人都会写代码。
**Boris Cherny:** Stakeholder alignment. Exactly. I do think that there's a future where I think by the end of the year what we're going to start to see is these start to get even murkier, where I think in some places the title "software engineer" is going to start to go away and it's just going to be replaced by "builder," or maybe it's just everyone's going to be a product manager and everyone codes, or something like this.
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**Lenny：** 你刚才提到你更享受编程了。我实际上在 Twitter 上做了一个小型非正式调查——不知道你有没有看到——我做了三个不同的投票。我问工程师，自从使用 AI 工具以来，你更享受还是更不享受工作了？然后我分别对产品经理和设计师做了同样的调查。工程师和产品经理中，70%的人说他们更享受工作了，大约10%说他们更不享受。有趣的是，设计师只有55%说更享受，20%说更不享受。我觉得这非常有意思。
**Lenny:** You talked about how you're enjoying coding more. I actually did this little informal survey on Twitter. I don't know if you saw this, where I just asked -- I did three different polls. I asked engineers, are you enjoying your job more or less since adopting AI tools? And then I did a separate one for PMs and one for designers. And both engineers and PMs, 70% of people said they are enjoying their job more and about 10% said they're enjoying their job less. Designers, interestingly, only 55% said they are enjoying their job more and 20% said they're enjoying their job less. Thought that was really interesting.
**Boris Cherny：** 超级有意思。我很想和这些人聊聊——无论是"更享受"还是"更不享受"那组——去了解他们的想法。你有跟他们中的人进一步交流过吗？
**Boris Cherny:** That's super interesting. I'd love to talk to these people, you know, both in the "more" bucket and the "less" bucket just to understand. Did you get to follow up with any of them?
**Lenny：** 有一些人回复了。我们实际上正在做一个更深入的后续调查，会在节目笔记中链接。但很多——你知道，让工作更有趣和更无趣的因素各不相同。那些设计师——那些说更不享受的人——其实没怎么分享原因。所以我也很好奇到底发生了什么。
**Lenny:** A few people replied and we're actually doing a follow-up poll that we'll link to in the show notes of going deeper into some of the stuff. But a lot of -- there's like, you know, the factors that make it more fun and less fun. The designers, they didn't share a lot actually of just like the people that were actually asked, just like, why are you enjoying your job less? And I didn't hear a lot. So, I'm curious what's going on there.
**Boris Cherny：** 是的。在 Anthropic 我也看到了一些这方面的情况。我觉得我们这里每个人都比较技术型。这是我们在招聘时就会筛选的——即使是非技术岗位也要经过很多技术面试。我们的设计师大部分都会写代码。所以据我所见，对他们来说这是好事——因为他们不用再去麻烦工程师了，可以自己去改代码。甚至一些之前不写代码的设计师也开始写代码了，对他们来说这很棒，因为他们可以自己解决阻塞了。但我确实很想多听听不同人的体验，因为我猜不是每个人的感受都一样。
**Boris Cherny:** Yeah, I'm seeing this a little bit at Anthropic. I think everyone is fairly technical. This is something that we screen for, you know, when people join. We have -- there's a lot of technical interviews that people go through even for non-technical functions. And, you know, our designers largely code. So I think for them, this is something that they have enjoyed from what I've seen, because now instead of bugging engineers, they can just like go in and code. And even some designers that didn't code before have just started to do it and for them it's great because they can unblock themselves. But I'd be really interested just to hear more people's experiences because I bet it's not uniform like that.
**Lenny：** 是的。如果你正在听这期节目，如果你觉得工作变得更不有趣了、更不享受了，请留言告诉我们。因为 Boris 说的、以及我从大多数人那里听到的是——70%的产品经理和工程师更喜欢自己的工作了。如果你不在那个群体里，可能有些值得关注的事情正在发生。
**Lenny:** Yeah. So maybe if you're listening to this, leave a comment if you're finding your jobs less fun and enjoying your job less, because what you're saying and what I'm hearing from most people, 70% of PMs and engineers are loving their job more. That's like, if you're not in that bucket, something's going on.
**Boris Cherny：** 是的。我们也看到大家使用不同的工具。比如我们的设计师就更多地使用 Claude 桌面应用来写代码。你只需下载桌面应用，里面有一个 Code 标签页，就在 Co-work 旁边，实际上底层跑的就是完全相同的 Claude Code——同样的智能体（agent），一模一样。这个功能已经上线好几个月了。这样你不需要打开一堆终端，却依然能获得 Claude Code 的全部能力。最大的好处是你可以同时并行运行任意多个 Claude 会话，我们内部管这叫"多 Claude 并行"（multi-Clauding）。
**Boris Cherny:** Yeah. Yeah. We do see that people use also different tools. So for example, our designers, they use the Claude desktop app a lot more to do their coding. So you just download the desktop app. There's a code tab. It's right next to co-work and it's actually the same exact Claude Code. So it's like the same agent and everything. We've had this for, you know, for many, many months. And so you can use this to code in a way that you don't have to open a bunch of terminals, but you still get the power of Claude Code. And the biggest thing is you can just run as many, you know, Claude sessions in parallel as you want. We, you know, we call this multi-Clauding.
**Boris Cherny：** 我觉得这种方式对非工程师来说更加自然。归根结底，这还是"把产品带到用户所在的地方"。你不想强迫用户改变工作流，不想让他们费力去学一个新东西。如果你能让人们正在做的事情变得更轻松一点，那就是一个更好的产品，人们也会更享受使用它。这就是"潜在需求"（latent demand）原则，我认为这是产品领域最重要的一条原则。
**Boris Cherny:** So this is a little more native, I think, for folks that are not engineers. And really, this is back to bringing the product to where the people are. You don't want to make people use a different workflow. You don't want to make them go out of their way to learn a new thing. It's whatever people are doing, if you can make that a little bit easier, then that's just going to be a much better product that people enjoy more. And this is just this principle of latent demand, which I think is just the single most important principle in product.
**Lenny：** 你能展开聊聊吗？我本来就想问这个。解释一下这个原则是什么，以及当你释放这种潜在需求时会发生什么。
**Lenny:** Can you talk about that actually, because I was going to go there. Explain what this principle is and what happens when you unlock this latent demand.
**Boris Cherny：** 潜在需求（latent demand）的意思是：如果你做的产品能够被人们"黑"进去、被用一种并非设计初衷的方式来使用，去做他们真正想做的事情，那么这就能帮助你作为产品构建者了解产品接下来该往哪里走。
**Boris Cherny:** Latent demand is this idea that if you build a product in a way that can be hacked or can be kind of misused by people in a way it wasn't really designed for, to do kind of something that they want to do, then this helps you as the product builder learn where to take the product next.
**Boris Cherny：** 举个例子——Facebook Marketplace。它的负责人 Fiona 其实是 Marketplace 团队的创始经理，她经常讲这个故事。Facebook Marketplace 的诞生源于一个观察：大概在 2016 年左右，Facebook 群组里 40% 的帖子都是在买卖东西。这太疯狂了——人们在"滥用" Facebook 群组来做交易。这里的"滥用"不是安全意义上的，而是说没有人为此设计过这个产品，但用户自己想办法用起来了，因为它实在太方便了。所以很明显，如果你专门做一个更好的买卖产品，人们一定会喜欢。Marketplace 会成功几乎是显而易见的。第一步是做了买卖专用群组，第二步就是 Marketplace。
**Boris Cherny:** So an example of this is Facebook Marketplace. So the manager for the team, Fiona, she was actually the founding manager for the Marketplace team and she talks about this a lot. Facebook Marketplace started based on the observation, back in, this must have been like 2016 or something like this, that 40% of posts in Facebook groups are buying and selling stuff. So this is crazy. It's like people are abusing the Facebook groups product to buy and sell. And it's not abuse in kind of like a security sense. It's abuse in that no one designed the product for this, but they're kind of figuring it out because it's just so useful for this. And so it was pretty obvious if you build a better product to let people buy and sell, they're going to like it. And it was just very obvious that Marketplace would be a hit from this. And so the first thing was buy-and-sell groups, so kind of special purpose groups to let people do that. And the second product was Marketplace.
**Boris Cherny：** Facebook Dating 的起源也很类似。当时的观察是：如果你看用户查看个人资料的行为，60% 的资料浏览来自互不是好友且性别相反的人。这就是一种典型的约会场景，只不过大家只是在"偷看"彼此的资料。所以如果你能为此做一个产品，或许就能行得通。
**Boris Cherny:** Facebook Dating I think started in a pretty similar place. And I think the observation was, if you look at people looking -- if you look at profile views, so people looking at each other's profiles on Facebook, 60% of profile views were people that are not friends with each other that are opposite gender. And so this is this kind of like, you know, traditional kind of dating setup, but, you know, people are just like creeping on each other. So maybe if you can build a product for this, it might work.
**Boris Cherny：** 潜在需求这个概念真的非常强大。举个例子，Co-work 也是这么来的。在过去大约六个月里，我们发现很多使用 Claude Code 的人根本不是在写代码。有人在 Twitter 上说他用 Claude Code 来种番茄。有人用它分析自己的基因组。有人用它从损坏的硬盘里恢复照片——那是婚礼照片。还有人用它来分析核磁共振影像。各种各样完全不是技术性的用例。很明显，人们在费尽心思通过终端来做这些事情，也许我们应该为他们专门做一个产品。
**Boris Cherny:** And so this idea of latent demand I think is just so powerful. And for example, this is also where co-work came from. We saw that for the last 6 months or so, a lot of people using Claude Code were not using it to code. There was someone on Twitter that was using it to grow tomato plants. There was someone else using it to analyze their genome. Someone was using it to recover photos from a corrupted hard drive -- it was like wedding photos. There was someone that was using it for -- I think like, they were using it to analyze an MRI. So there's just all these different use cases that are not technical at all. And it was just really obvious, like, people are jumping through hoops to use a terminal to do this thing. Maybe we should just build a product for them.
**Boris Cherny：** 其实我们很早就注意到这一点了，大概是去年五月。我记得有一天走进办公室，看到我们的数据科学家 Brendan 电脑上开着 Claude Code，就一个终端窗口。我当时震惊了，我说："Brendan，你在干嘛？你居然会打开终端了？"要知道，这是一个非常工程化的产品。很多工程师都不愿意用终端——那是最底层的工作方式，完全深入到计算机的最基础层面。
**Boris Cherny:** And we saw this actually pretty early, back in maybe May of last year. I remember walking into the office and our data scientist Brendan had Claude Code on his computer. He just had a terminal up and I was like, I was shocked. I was like, "Brendan, what are you doing? Like, you figured out how to open the terminal," which is, you know, it's a very engineering product. Even a lot of engineers don't want to use a terminal. It's just like the lowest level way to do your work. Just really, really in the weeds of the computer.
**Boris Cherny：** 然而他搞定了终端的使用，下载了 Node.js，安装了 Claude Code，然后就在终端里做 SQL 分析。太不可思议了。接下来一周，所有的数据科学家都在这么干。当你看到人们以这种方式"滥用"产品——用一种它没被设计过的方式来做对他们有用的事——这就是一个极其强烈的信号，说明你应该为此做一个专门的产品，人们一定会喜欢它。
**Boris Cherny:** And so he figured out how to use the terminal. He downloaded Node.js. He downloaded Claude Code and he was doing SQL analysis in a terminal and it was crazy. And then the next week all the data scientists were doing the same thing. So when you see people abusing the product in this way, using it in a way that it wasn't designed, in order to do something that is useful for them, it's just such a strong indicator that you should just build a product and people are going to like that. Something that's special purpose for that.
**Boris Cherny：** 我觉得现在潜在需求还多了一个有趣的维度。传统的理解是：观察人们在做什么，让那件事变得更容易，赋能给他们。而我最近六个月看到的现代理解稍有不同，那就是：观察模型正在尝试做什么，然后让那件事变得更容易。
**Boris Cherny:** I think now there's also this kind of interesting second dimension to latent demand. This is sort of the traditional framing: look at what people are doing, make that a little bit easier, empower them. The modern framing that I've been seeing in the last 6 months is a little bit different, and it's: look at what the model is trying to do and make that a little bit easier.
**Boris Cherny：** 我们刚开始做 Claude Code 的时候，很多人设计 LLM 产品的方式是把模型塞进一个框框里，然后说："这是我要做的应用，这是我想完成的事，模型，你负责其中这一个组件，这是你跟工具和 API 交互的方式。"
**Boris Cherny:** And so when we first started building Claude Code, I think a lot of the way that people approached designing things with LLMs is they kind of put the model in a box and they were like, here's this application that I want to build, here's the thing that I wanted to do, model, you're going to do this one component of it, here's the way that you're going to interact with these tools and APIs and whatever.
**Boris Cherny：** 而 Claude Code 的做法恰恰相反。我们说：产品就是模型本身。我们要让模型充分发挥，只在外面加最少的脚手架（scaffolding），给它最精简的一组工具，让它自己决定用哪些工具、以什么顺序运行。这在很大程度上就是基于模型自身的潜在需求。在研究领域，我们把这叫做"在分布上"（on distribution）——你要去看模型想做什么。用产品术语来说，潜在需求就是完全相同的概念，只不过应用在模型身上。
**Boris Cherny:** And for Claude Code, we inverted that. We said the product is the model. We want to expose it. We want to put the minimal scaffolding around it. Give it the minimal set of tools. So it can do the things. It can decide which tools to run. It can decide in what order to run them in, and so on. And I think a lot of this was just based on kind of latent demand of what the model wanted to do. And so, in research, we call this being on distribution. You want to see what the model is trying to do. In product terms, latent demand is just the same exact concept but applied to a model.
**Lenny：** 你提到了 Co-work。我记得你们最初发布时你说过，团队只用了 10 天就做出来了。
**Lenny:** You talked about co-work. Something that I saw you talk about when you launched that initially is your team built that in 10 days.
**Boris Cherny：** 这太疯狂了。它发布后很快就有数百万人使用——而且只花了 10 天来开发。你有什么故事可以分享吗？除了"我们用 Claude Code 来开发的"之外还有别的吗？
**Boris Cherny:** That's insane. It came out -- I think it was, like, you know, used by millions of people pretty quickly, something like that, being built in 10 days. Anything there, any stories there, other than just it was just, you know, we used Claude Code to build it and that's it.
**Boris Cherny：** 是的，挺有意思的。Claude Code 就像我说的，刚发布时并没有一炮而红，是随着时间才火起来的，其中有几个关键拐点。一个是 Opus 4 的发布——增长曲线直接飙升。然后十一月又一次飙升，之后每天增长都越来越陡。但最初几个月它并不算火。有人用，但很多人搞不明白怎么用，不知道它是干什么的，模型本身也还不够好。
**Boris Cherny:** Yeah, it's funny. Claude Code, like I said, when we released it, was not immediately a hit. It became a hit over time and there were a few inflection points. So one was, you know, like Opus 4 -- it just really, really inflected. And then in November it inflected and it just keeps inflecting. The growth just keeps getting steeper and steeper and steeper every day. But, you know, for the first few months it wasn't a hit. People used it but a lot of people couldn't figure out how to use it. They didn't know what it was for. The model still wasn't very good.
**Boris Cherny：** Co-work 发布后就立刻火了，比 Claude Code 早期要火得多。我觉得很大程度上得归功于 Felix、Sam、Jenny 和整个团队——实力真的非常强。Co-work 的诞生同样来自潜在需求：我们看到人们用 Claude Code 做那些非技术性的事情，然后就在想该怎么办。
**Boris Cherny:** Co-work, when we released it, was just immediately a hit, much more so than Claude Code was early on. I think a lot of the credit honestly just goes to like Felix and Sam and Jenny and the team that built this. It's just an incredibly strong team. And again, the place co-work came from is just this latent demand. Like we saw people using Claude Code for these non-technical things and we were trying to figure out what do we do.
**Boris Cherny：** 团队花了好几个月去探索，尝试了各种不同方案。最后有人说："如果我们就把 Claude Code 放进桌面应用呢？"这就是最终生效的方案。10 天时间里他们完全用 Claude Code 来开发。Co-work 其实内置了一套非常精密的安全系统和各种护栏（guardrails），确保模型做正确的事。
**Boris Cherny:** And so for a few months the team was exploring, they were trying all sorts of different options, and in the end someone was just like, "Okay, what if we just take Claude Code and put it in the desktop app?" And that's essentially the thing that worked. And so over 10 days they just completely used Claude Code to build it. And, you know, co-work actually has this very sophisticated security system that's built in and essentially these guardrails to make sure that the model kind of does the right thing.
**Boris Cherny：** 它不会失控。比如我们随产品附带了一整个虚拟机。这些代码全是 Claude Code 写的。我们只需要思考："怎么让它对非工程师用户更安全一点、更易上手一点？"然后 Claude Code 就把实现全做了。花了大约 10 天。我们提前发布了——当时还比较粗糙，现在在某些方面仍然有些粗糙。但这就是我们的学习方式，产品端和安全端都是如此：我们必须比自己觉得准备好的时间更早地发布，这样才能收到反馈、与用户对话、理解人们的需求，从而引导产品未来的方向。
**Boris Cherny:** It doesn't go off the rails. So, for example, we ship an entire virtual machine with it. And Claude Code just wrote all of this code. So we just had to think about, "All right, how do we make this a little bit safer, a little more self-guided for people that are not engineers?" It was fully implemented with Claude Code. Took about 10 days. We launched it early. You know, it was still pretty rough and it's still pretty rough around the edges. But this is kind of the way that we learn, both on the product side and on the safety side, is we have to release things a little bit earlier than we think so that we can get the feedback, so that we can talk to users. We can understand what people want and that will shape where the product goes in the future.
**Lenny：** 是的，我觉得这个观点非常有意思，而且很独特。一直以来都有这样的理念：尽早发布、从用户那里学习、获取反馈、快速迭代。而现在更特别的是，你甚至很难提前知道 AI 能做到什么、人们会怎么去用它——这是一个全新的理由去尽早发布，帮你发现你说的那种潜在需求。把它放出去，看看人们会拿它做什么。
**Lenny:** Yeah, I think that point is so interesting and it's so unique. There's always been this idea: release early, learn from users, get feedback, iterate. The fact that it's hard to even know what the AI is capable of and how people will try to use it is like a unique reason to start releasing things early that'll help you as you exactly describe this idea of what is the latent demand in this thing that we didn't really know. Let's put it out there and see what people do with it.
**Boris Cherny：** 对。而且作为一家安全实验室，Anthropic 还有另一个维度，就是安全。在思考模型安全的时候，有很多不同的研究方法。最底层是对齐（alignment）和机制可解释性（mechanistic interpretability）。就是在训练模型时确保它是安全的。我们现在已经有了相当成熟的技术来理解神经元内部发生了什么、对其进行追踪。比如，如果有一个与欺骗相关的神经元，我们正在接近能够监控它并理解它何时被激活的阶段。这就是对齐和机制可解释性，是最底层。
**Boris Cherny:** Yeah. And at Anthropic as a safety lab, the other dimension of that is safety. Because, you know, like when you think about model safety, there's a bunch of different ways to study it. Sort of the lowest level is alignment and mechanistic interpretability. So this is when we train the model, we want to make sure that it's safe. We at this point have pretty sophisticated technology to understand what's happening in the neurons, to trace it. And so, for example, if there's a neuron related to deception, we can start -- we're starting to get to the point where we can monitor it and understand that it's activating. And so this is alignment, this is mechanistic interpretability. It's the lowest layer.
**Boris Cherny：** 第二层是评估（evals），本质上是一个实验室环境。模型在培养皿里，你观察它，把它放到一个合成场景中说："好，模型，你会怎么做？你做的是正确的事吗？是对齐的吗？是安全的吗？"
**Boris Cherny:** The second layer is evals, and this is essentially a laboratory setting. The model is in a petri dish and you study it and you put it in a synthetic situation and just say, "Okay, model, what do you do? And are you doing the right thing? Is it aligned? Is it safe?"
**Boris Cherny：** 第三层是观察模型在真实环境中的表现。随着模型变得越来越复杂，这一层变得极其重要，因为模型可能在前两层表现很好，但在第三层却不尽如人意。我们很早就发布了 Claude Code，因为我们想研究安全问题。实际上我们在 Anthropic 内部使用了大概四五个月才对外发布，因为我们也不确定——这是第一个大型智能体，至少是当时发布的第一个大型智能体。它绝对是第一个被广泛使用的编程智能体。所以我们不确定它是否安全，必须在内部研究很长时间才觉得放心。
**Boris Cherny:** And then the third layer is seeing how the model behaves in the wild. And as the model gets more sophisticated, this becomes so important because it might look very good on these first two layers but not great on the third one. We released Claude Code really early because we wanted to study safety, and we actually used it within Anthropic for I think four or 5 months or something before we released it because we weren't really sure -- like, this is the first agent that, you know, the first big agent that I think folks had released at that point. It was definitely the first coding agent that became broadly used. And so we weren't sure if it was safe and so we actually had to study it internally for a long time before we felt good about that.
**Boris Cherny：** 即便发布之后，我们也在对齐和安全方面学到了很多，并把这些经验反哺到模型和产品中。Co-work 也类似——模型处于一个新环境中，执行的不是工程任务，它是一个代替你行动的智能体。对齐层面看起来不错，评估层面看起来不错，内部试用也不错，找几个客户发布也不错。然后我们必须确保它在真实世界中也是安全的。所以我们才会提前发布，才会称之为"研究预览"（research preview）。但它一直在不断改进。这确实是确保模型长期对齐、做正确事情的唯一方法。
**Boris Cherny:** And even since, you know, there's a lot that we've learned about alignment, there's a lot that we've learned about safety that we've been able to put back into the model, back into the product. And for co-work it's pretty similar -- the model's in this new setting, it's doing these tasks that are not engineering tasks, it's an agent that's acting on your behalf. It looks good on alignment, it looks good on evals, we try it internally, it looks good, we release it with a few customers, it looks good. Now, we have to make sure it's safe in the real world. And so, that's why we release a little early. That's why we call it a research preview. But yeah, it's just constantly improving. And this is really the only way to make sure that over the long term the model is aligned and it's doing the right things.
**Lenny：** 你所处的领域真的很疯狂——一方面有极其激烈的竞争和疯狂的节奏，另一方面又有这样的担忧：如果这个东西失控、造成破坏怎么办。找到这种平衡一定非常有挑战性。我听到的是有三个层次，我知道光安全这个话题就能做一整期播客。但我听到的是你们用三个层次来思考安全：一是观察模型的思考和运行；二是测试和评估，告诉你模型是否在做不好的事；三是提前发布。我之前没怎么听说过第一个层面，那真的很酷。你们有一种可观测性工具，可以窥探模型的"大脑"，看它在想什么、往什么方向走。
**Lenny:** It's such a wild space that you work in where there's this insane competition and pace. At the same time, there's this fear that if you get some -- if the, you know, the god can escape and cause damage -- and just finding that balance must be so challenging. What I'm hearing is there's kind of these three layers, and I know there's like, this could be a whole podcast conversation, is how you all think about the safety piece. But just what I'm hearing is there's these three layers you work with. There's kind of like observing the model thinking and operating. There's tests and evals that tell you this is doing bad things. And then releasing it early. I haven't actually heard a ton about that first piece. That is so cool. So you guys can -- there's an observability tool that can let you peek inside the model's brain and see how it's thinking and where it's heading.
**Boris Cherny：** 对，你应该找机会请 Chris Olah 上节目，他是这个领域的行业专家。他创立了"机制可解释性"（mechanistic interpretability）这个领域。核心思想是，你的大脑本质上是什么？就是一堆相互连接的神经元。你可以在人类或动物大脑中从这种机制层面去研究，理解神经元在做什么。
**Boris Cherny:** Yeah, you should at some point have Chris Olah on the podcast because he's just the industry expert on this. He invented this field of -- we call it mechanistic interpretability. And the idea is, you know, like, at its core, what is your brain? What is it? It's a bunch of neurons that are connected. And so what you can do is, in a human brain or animal brain, you can study it at this kind of mechanistic level to understand what the neurons are doing.
**Boris Cherny：** 令人惊讶的是，很多发现确实可以迁移到模型上。模型的神经元和动物神经元不一样，但在很多方面表现类似。我们已经对这些神经元的工作方式有了大量了解——某一层或某个神经元对应某个概念、特定概念是如何编码的、模型是如何做规划的、如何提前思考的。
**Boris Cherny:** It turns out, surprisingly, a lot of this does translate to models also. So model neurons are not the same as animal neurons but they behave similarly in a lot of ways. And so we've been able to learn just a ton about the way these neurons work, about, you know, this layer or this neuron maps to this concept, how particular concepts are encoded, how the model does planning, how it thinks ahead.
**Boris Cherny：** 很久以前我们还不确定模型到底只是在预测下一个 token，还是在做更深层次的事情。现在，我认为已经有相当强的证据表明它确实在做更深层次的事。而且随着模型变大，它用来做这些事的结构也越来越复杂——不再是单个神经元对应单个概念。一个神经元可能对应十几个概念，当它与其他神经元一起被激活时，这被称为"超位"（superposition），它们共同表达一个更复杂的概念。
**Boris Cherny:** You know, a long time ago, we weren't sure if the model is just predicting the next token or is doing something a little bit deeper. Now, I think there's actually quite strong evidence that it is doing something a little bit deeper. And then the structures that it uses to do this are pretty sophisticated now, where as the models get bigger, it's not just like a single neuron that corresponds to a concept. A single neuron might correspond to a dozen concepts. And if it's activated together with other neurons, this is called superposition. And together it represents this more sophisticated concept.
**Boris Cherny：** 这是我们一直在学习的东西。在 Anthropic，当我们思考这个领域如何发展时，以安全且对世界有益的方式来做这件事——这就是我们存在的理由，也是 Anthropic 每个人来这里的理由。
**Boris Cherny:** And it's just something we're learning about all the time, you know, and at Anthropic, as we think about the way this space evolves, doing this in a way that is safe and good for the world is just -- this is the reason that we exist and this is the reason that everyone is at Anthropic. Everyone that is here, this is the reason why they're here.
**Boris Cherny：** 所以我们实际上把很多这方面的工作都开源了，大量发表论文。我们非常自由地分享这些内容，就是为了激励其他在做类似事情的实验室以安全的方式来做。Claude Code 也是这样。我们内部把这叫做"向上竞赛"（race to the top）。比如 Claude Code 发布了一个开源的沙箱（sandbox），你可以在里面运行智能体，它能确保有一些边界限制，不会访问你系统上的所有东西。我们把它开源了，而且它适用于任何智能体，不只是 Claude Code，因为我们希望让其他人也能轻松做到同样的事。这就是"向上竞赛"的原则——我们希望确保这件事朝好的方向发展，而这就是我们手中的杠杆。
**Boris Cherny:** So, a lot of this work we actually open source. We publish it a lot. And, you know, we publish very freely to talk about this just so we can inspire other labs that are working on similar things to do it in a way that's safe. And this is something that we've been doing for Claude Code also. We call this the "race to the top" internally. And so for Claude Code, for example, we released an open source sandbox, and this is a sandbox you can run the agent in, and it just makes sure that there's certain boundaries and it can't access everything on your system. And we made that open source and it actually works with any agent, not just Claude Code, because we wanted to make it really easy for others to do the same thing. So this is just the same principle of race to the top. We want to make sure this thing goes well and this is just the lever that we have.
**Lenny：** 太棒了。好的，我一定要在这个话题上花更多时间，我会跟进你的建议。还有一件事我注意到，在工程师、产品经理以及其他与智能体打交道的人群中，有一种焦虑感。那种感觉是："天哪，它有一个问题需要我回答"，或者"它卡住了"，或者"我浪费了好多生产力，我得赶紧起来让它重新跑起来"。你有这种感觉吗？你的团队有这种感觉吗？你觉得这是一个需要关注和思考的问题吗？
**Lenny:** Incredible. Okay, I definitely want to spend more time on that. I will follow up with this suggestion. Something else that I've been noticing in the field across engineers, product managers, others that work with agents, is there's this kind of anxiety people feel when their agents aren't working. There's a sense that like, "Oh man, it has a question, I need to answer," or it's like blocked on something, or "I'm just like -- there's all this productivity I'm losing. I can't, like, I need to wake up and get it going again." Is that something you feel? Is that something your team feels? Do you feel like this is a problem we need to track and think about?
**Boris Cherny：** 我总是同时在跑一堆智能体。比如此刻我就有五个智能体在运行。任何时候——早上醒来我就会启动一堆智能体。今天起床后做的第一件事就是"我真想确认一下那个东西"。所以我打开手机，Claude iOS 应用，Code 标签页，跟智能体说"帮我做这个那个"，因为昨天我写了一些代码，有点纠结一个地方做得对不对——结果是对的。
**Boris Cherny:** I always have a bunch of agents running. So like, at the moment I have like five agents running and at any moment, like, you know, I wake up and I started a bunch of agents. Like, the first thing I did when I woke up is like, "Oh man, I really want to check this thing." So like I opened up my phone, Claude iOS app, code tab, you know, like, "Agent, do blah blah blah," because I wrote some code yesterday and I was like, "Wait, did I do this right?" I was kind of double-guessing something, and it was correct.
**Boris Cherny：** 现在这些操作变得太容易了。所以我不知道，确实有一点点焦虑。但我个人可能没太感受到，因为我总是有智能体在跑。而且我也不再被困在终端里了。现在大概三分之一的代码是在终端里写的，三分之一用桌面应用，三分之一用 iOS 应用——这太出乎意料了，因为我完全没想到 2026 年我会用这种方式写代码。
**Boris Cherny:** But now it's just so easy to do this. So I don't know, there is this little bit of anxiety. Maybe I personally haven't really felt it just because I have agents running all the time. And I'm also just not locked into a terminal anymore. Maybe a third of my code now is in the terminal, but also a third is using the desktop app and then a third is the iOS app, which is just so surprising, because I did not think that this would be the way that I code even in 2026.
**Lenny：** 我很喜欢你仍然把它称为"写代码"——本质上就是跟 Claude Code 说话让它帮你写代码。有意思的是，现在这就是写代码了。写代码现在是描述你想要什么，而不是亲手写代码。
**Lenny:** I love that you describe it as coding still, which is just talking to Claude Code to code for you, essentially. And it's interesting that this is now -- this is now coding. Coding now is describing what you want, not writing actual code.
**Boris Cherny：** 我有时在想，以前用打孔卡写程序的人如果看到现在的软件会说什么。那多疯狂啊？我记得读过一些很早期的 ACM 杂志上的文章，当时有人说"不，这不一样，这不算真正的编程。"他们那时候叫"编程"（programming）——我觉得"写代码"（coding）算是个比较新的词。
**Boris Cherny:** I kind of wonder if the people that used to code using punch cards or whatever, if you show them software, what they would have said. Isn't that crazy? And I remember reading something, this was maybe like very early versions of like ACM magazine or something, where people were saying, "No, it's not the same thing, this isn't really coding." And, you know, they called it programming -- I think "coding" is kind of a new word.
**Boris Cherny：** 我不禁会这样想——我的家族来自苏联，我出生在乌克兰。我爷爷其实是苏联最早的一批程序员之一，他用打孔卡编程。他跟我妈妈讲过小时候的故事，或者说我妈妈讲过她小时候的故事：他会把打孔卡带回家，那是一大摞一大摞的卡片。对我妈妈来说，她就用蜡笔在上面到处画画，那是她的童年记忆。但对我爷爷来说，那就是他编程的体验。
**Boris Cherny:** But I kind of think about this like -- in the back -- you know, my family is from the Soviet Union. I was born in Ukraine. And my grandpa was actually one of the first programmers in the Soviet Union and he programmed using punch cards. And, you know, he told my mom growing up, told these stories, or she told these stories, that when she was growing up, he would bring these punch cards home and there were these big stacks of punch cards, and for her she would draw all over them with crayons and that was her childhood memory. But for him that was his experience of programming.
**Boris Cherny：** 他其实没有经历向软件的转型。但后来确实转向了软件，我想那时候大概有一批老一代程序员根本不把软件当回事，他们会说："嗯，这不算真正的编程。"但我觉得这个领域一直就是这样在变化的。
**Boris Cherny:** And he actually never saw the software transition. But at some point it did transition to software, and I think there's probably this older generation of programmers that just didn't take software very seriously and they would have been like, "Well, you know, it's not really coding." But I think this is a field that just has always been changing in this way.
**Lenny：** 你可能不知道，我也出生在乌克兰。
**Lenny:** I don't think you know this, but I was born in Ukraine also.
**Boris Cherny：** 哦，我不知道。哪个城市？
**Boris Cherny:** Oh, I didn't know. Yeah. Which city?
**Lenny：** 我来自敖德萨。
**Lenny:** I'm from Odessa.
**Boris Cherny：** 哦，我也是。[笑声]
**Boris Cherny:** Oh, me too. [laughter]
**Lenny：** 什么？
**Lenny:** What?
**Boris Cherny：** 是的，太不可思议了。
**Boris Cherny:** Yeah, that's crazy.
**Lenny：** 哇。太巧了。真是个美妙的时刻。说不定咱们还沾亲带故呢。你们家什么时候走的？
**Lenny:** Wow. Incredible. What a moment. Maybe related in some small way. What year did your family leave?
**Boris Cherny：** 我们 95 年来的美国。
**Boris Cherny:** We came in '95.
**Lenny：** 好的。我们是 88 年离开的，早一些。
**Lenny:** Okay. We left in '88. A little earlier.
**Boris Cherny：** 嗯，对。
**Boris Cherny:** Oh, yeah.
**Lenny：** 如果没走的话，那人生就完全不同了，对吧？
**Lenny:** What a different life that would have been to not leave, huh?
**Boris Cherny：** 是啊。我每天都觉得自己无比幸运能在这里长大。
**Boris Cherny:** Yeah. I just feel so lucky every day that I get to grow up here.
**Lenny：** 对。我家人每次看到一个烤面包机或一顿饭，都会说"敬美国！"那种感觉就是——好了好了，别再说了。但你懂的，一旦你开始真正去想人生本来可能是什么样子。
**Lenny:** Yeah. My family, anytime there's like a toaster or a meal, they're just like, "To America!" It's like, okay, enough about that. But you get it, you know, once you start really thinking about what life could have been.
**Boris Cherny：** 是的。没错。我们也举同样的杯，只不过用的还是伏特加。
**Boris Cherny:** Yeah. Yeah. Exactly. Yeah. We do the same toast, but it's still vodka.
**Lenny：** 还是伏特加。必须的。[笑声]
**Lenny:** It's still vodka. Absolutely. [laughter]
**Lenny：** 天哪。好吧。让我再问你几个问题。你分享了一些很棒的建议，关于如何最大化利用 AI、如何在 AI 上构建产品、如何做出优秀的 AI 产品。你提到的一个建议是：给团队要多少 token 就给多少 token，让他们尽情实验。你还分享了一个更通用的建议：面向模型未来的方向去构建，而不是面向模型今天的能力。你还有什么其他建议想给那些正在构建 AI 产品的人？
**Lenny:** Oh, man. Okay. Let me ask you a couple more things here. You shared some really cool tips for how to get the most out of AI, how to build on AI, how to build great products on AI. One tip you shared is give your team as many tokens as they want. Just let them experiment. You also shared just advice generally of just build towards the model, where the model is going, not to where it is today. What other advice do you have for folks that are trying to build AI products?
**Boris Cherny：** 我可能还想再分享几点。第一点是不要试图把模型框住。我觉得很多人在用模型构建产品时，本能反应是让模型以非常特定的方式运行。他们会说："这是一个更大系统中的一个组件。"例子包括在模型上层叠非常严格的工作流——比如说"你必须先做第一步，再做第二步，再做第三步"，还有一个很花哨的编排器（orchestrator）来控制。但实际上，几乎总是直接给模型工具、给它目标、让它自己想办法，效果更好。我觉得一年前你确实需要很多脚手架，但现在真的不需要了。
**Boris Cherny:** I'd probably share a few more things. So, one is don't try to box the model in. I think a lot of people's instinct when they build on the model is they try to make it behave a very particular way. They're like, "This is a component of a bigger system." I think some examples of this are people layering very strict workflows on the model, for example, you know, to say like, "You must do step one then step two then step three," and you have this very fancy orchestrator doing this. But actually, almost always you get better results if you just give the model tools, you give it a goal, and you let it figure it out. I think a year ago you actually needed a lot of the scaffolding, but nowadays you don't really need it.
**Boris Cherny：** 我不知道该怎么称呼这个原则，但大概就是"别问模型能为你做什么"（Ask not what the model can do for you）这种感觉。想一想如何给模型工具去做事。不要过度策展，不要把它关进盒子里，不要预先给它一大堆上下文。给它一个工具，让它自己去获取所需的上下文。这样效果会好得多。
**Boris Cherny:** So, you know, I don't know what to call this principle, but it's like, you know, "Ask not what the model can do for you." Maybe it's something like this. Just think about how do you give the model the tools to do things. Don't try to overcurate it. Don't try to put it into a box. Don't try to give it a bunch of context up front. Give it a tool so that it can get the context it needs. You're just going to get better results.
**Boris Cherny：** 第二点其实是这个原则更通用的版本，就是"苦涩的教训"（the bitter lesson）。在 Claude Code 团队内部，我们——希望听众们读过这篇文章——Rich Sutton 大概十年前写了一篇博客叫《苦涩的教训》。其实是一个很简单的想法：更通用的模型最终总是会胜过更专用的模型。我觉得他当时说的是自动驾驶汽车和其他领域，但这个教训有非常多的推论。
**Boris Cherny:** I think a second one is maybe actually an even more general version of this principle, which is just the bitter lesson. And actually, for the Claude Code team, we have -- hopefully listeners have read this, but Rich Sutton had this blog post maybe 10 years ago called "The Bitter Lesson." And it's actually a really simple idea. His idea was that the more general model will always outperform the more specific model. And I think for him he was talking about self-driving cars and other domains like this, but actually there's just so many corollaries to the bitter lesson.
**Boris Cherny：** 对我来说，最大的推论就是：永远押注更通用的模型。从长远来看，不要试图用小模型来做事，不要试图微调（fine-tune），不要做那些事。当然有一些特定的应用和理由，但几乎总是应该押注更通用的模型，如果你有这个灵活性的话。那些工作流本质上就是一种非通用的方式——给模型套上脚手架。我们看到的是，脚手架或许能提升 10-20% 的性能，但这些收益往往在下一个模型出来时就被抹平了。所以还不如等下一个模型。
**Boris Cherny:** And for me, the biggest one is just always bet on the more general model, and, you know, over the long term, don't try to use tiny models for stuff. Don't try to fine-tune. Don't try to do any of this stuff. There's some applications, some reasons to do this, but almost always try to bet on the more general model if you can, if you have that flexibility. And so these workflows are essentially a way that, you know, it's not a general model. It's putting the scaffolding around it. And in general, what we see is maybe scaffolding can improve performance maybe 10-20%, something like this, but often these gains just get wiped out with the next model. So it's almost better to just wait for the next one.
**Boris Cherny：** 我想最后一个原则，也是 Claude Code 回过头来看做对了的事情：从一开始我们就押注于为六个月后的模型去构建，而不是为今天的模型去构建。产品最早的版本只帮我写了很少的代码，因为我不信任它——那时候用的是 Sonnet 3.5，然后是 3.6，或者叫 3.5 New，不管当时叫什么名字。那些模型在编程方面还不够好，正在接近但仍然很早期。
**Boris Cherny:** And I think maybe this is a final principle and something that Claude Code I think got right in hindsight. From the very beginning, we bet on building for the model six months from now, not for the model of today. And for the very early versions of the product, it just wrote so little of my code because I didn't trust it, because, you know, it was like Sonnet 3.5, then it was like 3.6, or forget -- 3.5 New, whatever name we gave it. These models just weren't very good at coding yet. They were getting there, but it was still pretty early.
**Boris Cherny：** 所以那时模型帮我用 Git、自动化了一些操作，但真正写的代码并不多。Claude Code 的赌注是：到某个时候模型会好到能写大量代码。我们第一次看到这个转折是 Opus 4 和 Sonnet 4。Opus 4 是我们去年五月发布的第一个 ASL-3 级别模型，我们看到了一个巨大的拐点，因为所有人都开始第一次使用 Claude Code，那就是我们增长真正进入指数级的时候。就像我说的，一直维持着这个势头。
**Boris Cherny:** So back then the model did -- it used Git for me, it automated some things, but it really wasn't doing a huge amount of my coding. And so the bet with Claude Code was at some point the model gets good enough that it can just write a lot of the code. And this is a thing that we first started seeing with Opus 4 and Sonnet 4. And Opus 4 was our first kind of ASL-3 class model that we released back in May, and we just saw this inflection because everyone started to use Claude Code for the first time, and that was kind of when our growth really went exponential. And like I said, it's kind of stayed there.
**Boris Cherny：** 所以我经常给人的建议是这样的，尤其是给做初创公司的朋友：这会让你不太舒服，因为前六个月你的产品-市场契合度（product-market fit）不会很好。但如果你为六个月后的模型来构建，等那个模型出来的时候，你就能立刻上手，产品会开始运转起来。
**Boris Cherny:** So I think this is advice that I actually give to a lot of folks, especially people building startups. It's going to be uncomfortable because your product-market fit won't be very good for the first 6 months, but if you build for the model 6 months out, when that model comes out, you're just going to hit the ground running and the product is going to click and start to work.
**Lenny：** 当你说"为六个月后的模型去构建"时，你觉得人们可以做出什么样的假设？是它总体上会变得更好吗？是"它已经差不多能做到了"可以作为一个信号说明它可能会在这方面变得更好？关于这个你有什么建议吗？
**Lenny:** And when you say build for the model 6 months out, what is it that you think people can assume will happen? Is it just generally it will get better at things? Is it just like, okay, it's almost good enough, and that's a sign that it'll probably get better at that thing. Is there any advice there?
**Boris Cherny：** 我觉得那是个不错的判断方式。当然，在 AI 实验室内部，我们能看到模型具体在哪些方面会变好。[笑声] 所以这有点不公平。但我们也在努力分享这些信息。比如模型会越来越擅长使用工具和操控计算机，这是我会押的一个注。
**Boris Cherny:** I think that's a good way to do it. Like, you know, obviously within an AI lab, we get to see the specific ways that it gets better. [laughter] So, it's a little unfair. But we also try to talk about this. So, you know, one of the ways that it's going to get better is it's going to get better and better at using tools and using computers. This is a bet that I would make.
**Boris Cherny：** 另一个是模型会越来越擅长长时间运行。这方面有各种研究。但如果你追溯一下发展轨迹——或者就拿我自己的经验来说，一年前我用 Sonnet 3.5 的时候，它大概只能运行 15 到 30 秒就会开始跑偏，你必须全程手把手带着它做任何复杂任务。但现在用 Opus 4.6，它平均可以无人看管运行 10、20、30 分钟，我就去开另一个 Claude 做别的事。就像我说的，我总是同时在跑一堆 Claude。
**Boris Cherny:** Another one is it's going to get better and better for running for long periods of time. And this is a place, you know, there's all sorts of studies about this. But if you just trace the trajectory or, you know, maybe even like for my own experience, when I used Sonnet 3.5 back, you know, a year ago, it could run for maybe 15 or 30 seconds before it started going off the rails and you just really had to hold its hand through any kind of complicated task. But nowadays with Opus 4.6, on average it'll run maybe 10, 20, 30 minutes unattended and I'll just start another Claude and have it do something else. And, you know, like I said, I always have a bunch of Claudes running.
**Boris Cherny：** 它们也可以连续运行几个小时甚至几天。我记得有些案例跑了好几周。我认为随着时间推移，这会变得越来越常见——模型会持续运行很长时间，你不需要坐在那里盯着它了。
**Boris Cherny:** And they can also run for hours or even days at a time. I think there are some examples where they ran for many weeks. And so I think over time this is going to become more and more normal, where the models are running for a very, very long period of time and you don't have to sit there and babysit them anymore.
**Lenny：** 我们刚聊了构建 AI 产品的建议。对于那些刚开始使用 Claude Code 或者已经在用但想用得更好的人，你有什么建议？能分享几个进阶技巧吗？
**Lenny:** So we just talked about tips for building AI products. Any tips for someone just using Claude Code, say, for the first time, or just someone already using Claude Code that wants to get better? What are like a couple pro tips that you could share?
**Boris Cherny：** 我要先说一个前提：使用 Claude Code 没有唯一正确的方式。我可以分享一些技巧，但说实话，这是一个开发者工具，开发者各不相同，偏好不同，环境不同。所以有非常多的使用方式，没有唯一标准答案。你得找到适合自己的路。好在你可以问 Claude Code 本身——它能给出建议，能编辑你的设置，它了解自身。所以它可以帮你找到适合的方式。
**Boris Cherny:** I will give a caveat, which is there's no one right way to use Claude Code. So I can share some tips, but honestly, this is a dev tool. Developers are all different. Developers have different preferences. They have different environments. So there's just so many ways to use these tools. There's no one right way. You sort of have to find your own path. Luckily, you can ask Claude Code. It's able to make recommendations. It can edit your settings. It kind of knows about itself. So, it can help with that.
**Boris Cherny：** 几个我觉得比较有用的技巧。第一，使用最强的模型。目前是 Opus 4.6。我的"最大努力"（maximum effort）模式始终开着。有时候人们会为了省钱用不那么贵的模型比如 Sonnet。但因为智能程度较低，完成同样的任务实际上要花更多 token。所以用更便宜的模型未必真的更便宜。通常用最强的模型反而更便宜、消耗更少的 token，因为它能更快完成任务，不需要那么多修正和手把手指导。所以第一条建议：用最好的模型。
**Boris Cherny:** A few tips that generally I find pretty useful. So, number one is just use the most capable model. Currently that's Opus 4.6. I have maximum effort enabled always. The thing that happens is sometimes people try to use a less expensive model like Sonnet or something like this. But because it's less intelligent, it actually takes more tokens in the end to do the same task. And so it's actually not obvious that it's cheaper if you use a less expensive model. Often it's actually cheaper and less token intensive if you use the most capable model, because it can just do the same thing much faster with less correction, less handholding, and so on. So that's the first tip: just use the best model.
**Boris Cherny：** 第二个是使用计划模式（plan mode）。我大概 80% 的任务都从计划模式开始。计划模式其实非常简单，我们只是在模型的提示词（prompt）中注入一句话："请先不要写代码。"就这样。实际上没有什么花哨的东西，就是最简单的做法。
**Boris Cherny:** The second one is use plan mode. I start almost all of my tasks in plan mode, maybe like 80%. And plan mode is actually really simple. All it is, is we inject one sentence into the model's prompt to say, "Please don't write any code yet." That's it. Like, there's actually nothing fancy going on. It's just the simplest thing.
**Boris Cherny：** 在终端里，按两次 Shift+Tab 就能进入计划模式。在桌面应用里有一个小按钮，网页版也有一个按钮，移动端也很快会上线。我们也刚刚为 Slack 集成添加了这个功能。
**Boris Cherny:** And so for people that are in the terminal, it's just Shift+Tab twice and that gets you into plan mode. For people in the desktop app, there's a little button. On web, there's a little button. It's coming pretty soon to mobile also. And we just launched it for the Slack integration, too.
**Boris Cherny：** 所以计划模式是第二个建议。模型会跟你来回讨论，等计划看起来没问题了，你再让模型执行。之后我会自动接受所有编辑，因为如果计划是好的，用 Opus 4.6 基本上一次就能做对。
**Boris Cherny:** So plan mode is the second one. And essentially the model will just go back and forth with you. Once the plan looks good, then you let the model execute. I auto-accept edits after that because if the plan looks good, it's just going to one-shot it. It'll get it right the first time almost every time with Opus 4.6.
**Boris Cherny：** 第三个建议就是多试试不同的界面。我觉得很多人一想到 Claude Code 就想到终端。当然，我们支持所有终端——Mac、Windows，你用什么终端都行，完美兼容。但我们其实还支持很多其他形态——iOS 和 Android 应用、桌面应用、Slack 集成，等等。所以我建议你多尝试一下。每个工程师都不一样，每个构建者都不一样。找到让你感觉对的那个方式就好。你不一定非要用终端。所有地方跑的都是同一个 Claude 智能体。
**Boris Cherny:** And then maybe the third tip is just play around with different interfaces. I think a lot of people, when they think about Claude Code, they think about a terminal. And, you know, of course, we support every terminal. We support Mac, Windows, you know, whatever terminal you might use, it works perfectly. But we actually support a lot of other form factors too, like, you know, we have iOS and Android apps. We have a desktop app. There's the Slack integration. There's all sorts of things that we support. So I would just play around with these. And again, it's like every engineer is different. Everyone that's building is different. Just find the thing that feels right to you and use that. You don't have to use a terminal. It's the same Claude agent running everywhere.
**Lenny：** 太棒了。好的，再问几个问题就收尾。你怎么看 Codex？你对这个产品有什么看法？你觉得他们在朝什么方向走？在编程智能体这个竞争如此激烈的领域中竞争是什么感觉？
**Lenny:** Amazing. Okay. Just a couple more questions to round things out. What's your take on Codex? How do you feel about that product? How do you feel about where they're going? Just kind of competing in this very competitive space in coding agents.
**Boris Cherny：** 说实话我没怎么用过，但我记得它刚出来的时候试过一下。在我看来它跟 Claude Code 很像，这倒是让人挺受用的。我觉得有更多竞争实际上是好事，因为用户应该有选择，而竞争也会倒逼我们所有人做得更好。但说实话，我们团队的注意力完全放在解决用户的问题上。我们不会花很多时间研究竞品，也不太会去试用其他产品。当然你要知道它们的存在。但对我来说，我就是喜欢跟用户聊天，喜欢让产品变得更好，喜欢根据反馈采取行动。归根结底就是做一个好产品。
**Boris Cherny:** Yeah, I actually haven't really used it, but I think I did use it maybe when it came out. It looked a lot like Claude Code to me, so that was kind of flattering. It's -- I think it's actually good, you know, to have more competition, because people should get to choose and hopefully it forces all of us to do an even better job. Honestly, for our team, though, we're just focused on solving the problems that users have. So for us, you know, we don't spend a lot of time looking at competing products. We don't really try the other products. You kind of want to be aware of them. You want to know they exist. But for me, I just love talking to users. I love making the product better. I love just acting on feedback. So it's really just about building a good product.
**Lenny：** 最后一个问题吧。我跟 Anthropic 的联合创始人 Ben Mann 聊过该问你什么，他给了很多建议，我已经融入了整个对话。他给你的一个问题是：AGI 之后你有什么计划？你觉得到时候你会做什么？一旦达到 AGI——不管那意味着什么——你的生活会是什么样的？
**Lenny:** Maybe a last question. So I talked to Ben Mann, co-founder of Anthropic, about what to talk to you about. He had a bunch of suggestions which I've integrated throughout our chat. One question he had for you is: what's your plan post-AGI? What do you think you're going to be doing? What's your life like once we hit AGI, whatever that means?
**Boris Cherny：** 加入 Anthropic 之前，我其实住在日本乡下，那是一种完全不同的生活方式。我是镇上唯一的工程师，也是唯一说英语的人。感觉完全不一样。每周有几天我会骑自行车去农贸市场。骑过去沿途是稻田什么的。那种节奏跟旧金山完全相反。
**Boris Cherny:** So before I joined Anthropic, I was actually living in rural Japan and it was like a totally different lifestyle. I was the only engineer in the town. I was the only English speaker in the town. It was just like a totally different vibe. Like, a couple times a week I would bike to the farmers market. And, you know, you bike by rice paddies and stuff. It was just like a totally different speed than -- just complete opposite of San Francisco.
**Boris Cherny：** 我特别喜欢的一件事是我们结识邻居、建立友谊的方式——交换腌菜。在我们住的那个镇上，每个人都做味噌（miso），每个人都做腌菜。所以我其实做味噌做得还不错。做了好几批，到现在还在做。
**Boris Cherny:** One of the things that I really liked is the way that we got to know our neighbors and we kind of built friendships is by trading pickles. So in the town where we lived, it was actually like everyone made miso. Everyone made pickles. And so I actually got decently good at making miso. And, you know, I made a bunch of batches, and this is something that I still make.
**Boris Cherny：** 味噌有一个有意思的地方，就是它教你用很长的时间尺度来思考，这跟工程思维非常不同。一批白味噌至少要三个月，红味噌要两三四年。你必须非常有耐心。把它拌好之后就放在那里，然后你就只能等。
**Boris Cherny:** Miso is this interesting thing where it teaches you to think on these long time scales. That's just very different than engineering, because, you know, a batch of white miso takes at least three months to make, and a red miso is like, you know, 2, 3, 4 years. You just have to be very patient. You kind of mix it up and then you just let it sit. You have to be very, very patient.
**Boris Cherny：** 我喜欢它的地方就是用这种长时间尺度来思考。对，我觉得 AGI 之后，或者如果我不在 Anthropic 的话，我大概会在做味噌吧。[笑声]
**Boris Cherny:** So the thing that I love about it is just thinking in these long time scales. And yeah, I think post-AGI, or if I wasn't at Anthropic, I'd probably be making miso. [laughter]
**Lenny：** 我太喜欢这个答案了。Ben 让我问你味噌是怎么回事，所以你回答这个我特别开心。好吧，所以未来可能是深入钻研味噌，把味噌做到极致。太棒了。Boris，这次对话太精彩了。我感觉我们现在是乌克兰兄弟了。在进入一个非常精彩的闪电问答环节之前，你还有什么想分享的吗？有什么想留给听众的？有什么想再强调的吗？
**Lenny:** I love this answer. Ben asked me to ask you about what's the deal with you and miso, and so I love that you answered it. Okay, so the future might be just going deep into miso, getting really good at making miso. Amazing. Boris, this was incredible. I feel like we're brothers now from Ukraine. Before we get to a very exciting lightning round, is there anything else that you wanted to share? Is there anything you want to leave listeners with? Anything you want to double down on?
**Boris Cherny：** 是的，我想强调的是，Anthropic 从一开始就秉持这样的理念：从编程开始，然后到工具使用，再到计算机使用——这就是我们思考事情的方式。这是我们知道模型会如何发展的方式，也是我们想要构建模型的方式。也是我们学习安全、研究安全、改进安全的最佳途径。
**Boris Cherny:** Yeah, I think I would just underscore, you know, for Anthropic since the beginning, this idea of starting at coding, then getting to tool use, then getting to computer use has just been the way that we think about things. And this is the way that we know the models are going to develop, or, you know, the way that we want to build our models. And it's also the way that we get to learn about safety, study it, and improve it the most.
**Boris Cherny：** 所以现在发生的一切——Claude Code 变成一个巨大的、数十亿美元的业务，我所有的朋友都在用 Claude Code 然后一直给我发消息聊这个。这个东西变得这么大——从某种程度上说完全出乎意料，因为我们不知道会是这个产品形态，不知道会从终端开始。但从另一个角度看，这又完全在意料之中，因为这一直是我们公司的信念。
**Boris Cherny:** So, you know, everything that's happening right now around, you know, Claude Code becoming this huge, you know, multi-billion dollar business, and, you know, like now all of my friends use Claude Code and they just text me about it all the time. So just like, you know, this thing getting kind of big. And in some ways it's a total surprise because this isn't kind of the -- we didn't know that it would be this product. We didn't know that it would start in a terminal or anything like this. But in some ways, it's just totally unsurprising because this has been our belief as a company for a long time.
**Boris Cherny：** 与此同时，这一切仍然感觉非常早期。世界上大多数人仍然没有使用 Claude Code，大多数人仍然没有使用 AI。所以感觉我们才完成了 1%，还有太多太多的路要走。
**Boris Cherny:** At the same time, it just feels still very early, you know, like most of the world still does not use Claude Code. Most of the world still does not use AI. So, it just feels like this is 1% done and there's so much more to go.
**Lenny：** 是的。天哪，看到那些数据真的很疯狂。你们刚融了一大笔钱。我记得光 Claude Code 就有 20 亿美元的收入。Anthropic 好像——我记得你们公布的数字——有 150 亿美元的收入。想到这还是多么早期，再看看这些数字，真的太不可思议了。
**Lenny:** Yeah. Man, that's insane to think seeing the numbers that are coming out. You guys just raised a bazillion dollars. I think Claude Code alone is making $2 billion in revenue. You think Anthropic -- I think the number you guys put out -- you're making $15 billion in revenue. It's insane to just think this is how early it still is and just the numbers we're seeing.
**Boris Cherny：** 对，真的很疯狂。Claude Code 能持续增长，说实话完全得益于用户。这么多人在用它，他们对产品充满热情，爱上这个产品，然后告诉我们哪里不好用、他们想要什么。所以它能不断改进的唯一原因就是所有人都在使用它、讨论它、不断给反馈。这是最重要的事情。对我来说，跟用户聊天、为他们把产品做得更好，就是我最喜欢的工作方式。
**Boris Cherny:** Yeah. Yeah. Yeah. It's crazy. And, I mean, the way that Claude Code has kept growing is honestly just the users. Like, so many people use it. They're so passionate about it. They fall in love with the product and then they tell us about stuff that doesn't work, stuff that they want. And so, the only reason that it keeps improving is because everyone is using it. Everyone is talking about it. Everyone keeps giving feedback, and this is just the single most important thing. And, you know, for me this is the way that I love to spend my day, is just talking to users and making it better for them.
**Lenny：** 还有做味噌。
**Lenny:** And making miso.
**Boris Cherny：** 还有做味噌。不过味噌不怎么费事，你就是得等。你就是得等。
**Boris Cherny:** And making miso. Well, the miso is not super involved. You just gotta wait. You just gotta wait.
**Lenny：** 好了，Boris，到了我们非常精彩的闪电问答环节。我准备了五个问题。准备好了吗？
**Lenny:** Well, Boris, with that, we've reached our very exciting lightning round. I've got five questions for you. Are you ready?
**Boris Cherny：** 来吧。
**Boris Cherny:** Let's do it.
**Lenny：** 第一个问题：你最常推荐给别人的两三本书是什么？
**Lenny:** First question: what are two or three books that you find yourself recommending most to other people?
**Boris Cherny：** 我读书很多。先说一本技术书——《Scala 函数式编程》（Functional Programming in Scala）。这是我读过的最好的技术书。说起来有点奇怪，因为你可能不会去写 Scala，而且在未来这重不重要也不好说。但函数式编程和用类型思考有一种优雅感，这就是我写代码的方式，是我停不下来的思维方式。你可以把它看作一个历史文物，也可以把它看作一个能让你功力大增的东西。
**Boris Cherny:** I'm a big reader. I would start with the technical book one, which is Functional Programming in Scala. This is the single best technical book I've ever read. It's very weird because you're probably not going to use Scala, and I don't know how much this matters in the future now, but there's this just elegance to functional programming and thinking in types. And this is just the way that I code and the way that I can't stop thinking about coding. So, you could think of it as a historical artifact. You could think of it as something that will level you up.
**Lenny：** 我太喜欢了，这本书从来没有人提过。我的最爱。
**Lenny:** I love this never-before-mentioned book. My favorite.
**Boris Cherny：** 太好了。第二本是 Stross 写的《加速》（Accelerando）。我最爱的阅读类型是科幻，可能是科幻加一般小说。《加速》是一本不可思议的书，它的节奏越来越快、越来越快。我觉得它比我读过的任何其他书都更好地捕捉到了我们正在经历的这个时刻的本质——就是那种速度感。故事从"起飞"开始发生的时候写起，逐渐接近奇点（singularity），最后以一种集体龙虾意识在木星轨道上运行结束。这一切发生在短短几十年里。那个节奏真的太棒了，我非常喜欢。
**Boris Cherny:** Oh, amazing. Amazing. Okay. Second one is Accelerando by Stross. This is probably -- you know, my big genre is sci-fi. Probably sci-fi and fiction. Accelerando is just this incredible book and it's just so fast-paced. The pace gets faster and faster and faster. And I just feel like it captures the essence of this moment that we're in more than any other book that I've read. Just the speed of it. And it starts as liftoff is starting to happen and, you know, starting to approach the singularity, and it ends with this collective lobster consciousness orbiting Jupiter. And, you know, this happens over the span of a few decades or something. So the pace is just incredible. I really love it.
**Boris Cherny：** 再推荐一本吧。刘慈欣的《流浪地球》。他就是写《三体》的那位，我想很多人知道他是因为《三体》。我觉得《三体》很棒，但我其实更喜欢他的短篇小说。《流浪地球》是一个短篇集，里面有一些非常精彩的故事。而且读中国科幻也很有意思，因为它跟西方科幻有非常不同的视角，至少他作为作家思考问题的方式是不一样的。写得真的非常好、非常美。
**Boris Cherny:** Maybe I'll do one more book. The Wandering Earth by Liu Cixin. So he's the guy that did Three-Body Problem. I think a lot of people know him for that. I actually think Three-Body Problem was awesome, but I actually liked his short stories even more. So, Wandering Earth is one of the short story collections and it just has some really, really amazing stories. And it's also just quite interesting to see Chinese sci-fi because it has a very different perspective than Western sci-fi and kind of the way that, at least he as a writer, thinks about it. So, it's just really, really interesting to read and just beautifully written.
**Lenny：** 科幻对帮助我们思考未来方向的作用真的太有意思了。它构建了这些心理模型，让你觉得"好的，我明白了，我读过这种类型的世界。"
**Lenny:** It's so interesting how sci-fi has prepared us to think about where things are going. Just like, it creates these mental models of like, "Okay, I see, I've read about this sort of world."
**Boris Cherny：** 对。我觉得这其实是我加入 Anthropic 的原因。因为我当时住在那个偏远的地方，用很长的时间尺度来思考，因为那里一切都非常缓慢。你做的所有事情都围绕着季节，围绕着那些需要好几个月的食物。社交活动就是这样组织的，你安排时间也是这样。你去农贸市场，现在是甜椒季，你知道是因为有 20 个卖甜椒的摊位；下个星期季节结束了，变成葡萄季了。就是这种长时间尺度的感觉。
**Boris Cherny:** Yeah. I think for me this is the reason that I joined Anthropic actually. Because, you know, I was living in this rural place. I was thinking on these long time scales because everything is just so slow out there, at least compared to SF. And just like all the things that you do are based around the seasons and it's based around this food that takes many, many months. That's the way that social events are organized. That's the way you kind of organize your time. You go to the farmers market and it's pimento season and you know that because there's 20 pimento vendors, and then the next week the season is done and it's grape season and you kind of see this. So it's these long time scales.
**Boris Cherny：** 那段时间我也在读大量科幻。在那个时刻，用长时间尺度来思考的我，意识到我知道这件事可能会怎样发展，我觉得自己必须为它朝更好的方向发展做出贡献。这就是我最终加入 Anthropic 的原因，Ben Mann 也在其中起了很大的作用。
**Boris Cherny:** And I was also reading a bunch of sci-fi at the time, and just being in this moment, I was like, you know, just thinking about these long time scales. I know how this thing can go, and I just felt like I had to contribute to it going a little bit better. And that's actually why I ended up at Anthropic, and Ben Mann was also a big part of that too.
**Lenny：** 我觉得我想单独做一期播客来聊你在日本的经历以及从日本到 Anthropic 的旅程。但我们长话短说吧。我快速推荐你一本科幻小说——你读过《天渊》（A Fire Upon the Deep）吗？
**Lenny:** I feel like I want to do a whole podcast just talking about your time in Japan and the journey of Boris through Japan to Anthropic. But we'll keep it short. I'll quickly recommend a sci-fi book to you if you haven't read it. Have you read A Fire Upon the Deep?
**Boris Cherny：** 是 Vinge 写的对吧？读过，很棒。
**Boris Cherny:** This is Vinge, right? Yeah. It's great.
**Lenny：** 对。从 AI/AGI 的角度来看那本书特别有意思。很少有人读过。所以——
**Lenny:** Yes. Okay. That one's so interesting from an AI/AGI perspective. So few people have read that, so --
**Boris Cherny：** 对。内容量很大。
**Boris Cherny:** Yeah. It's a lot.
**Lenny：** 对，是的。
**Lenny:** Yeah. Yeah. Yeah.
**Boris Cherny：** 我也喜欢《深渊上的火》（A Deepness in the Sky）。那两本是续集关系对吧？
**Boris Cherny:** I like A Deepness in the Sky also. I think those are sequels, right? Or --
**Lenny：** 是的。
**Lenny:** Yeah.
**Boris Cherny：** 对，我想是的。
**Boris Cherny:** Yeah. Yeah. I think so.
**Lenny：** 是的。很长很复杂，但真的很好。好吧，继续闪电问答。你有什么最近看的喜欢的电影或电视剧吗？
**Lenny:** Yeah. It's very long and complex to get into, but so good. Okay. We'll keep going through the lightning round. Do you have a favorite recent movie or TV show you really enjoyed?
**Boris Cherny：** 我其实不怎么看电视和电影，最近实在没什么时间。不过我看了——我又要提刘慈欣了——Netflix 上的《三体》剧集，我真的很喜欢。我觉得那是对原著小说系列很棒的改编。
**Boris Cherny:** So, I actually don't really watch TV or movies. I just don't really have time these days. I did watch -- I'm going to bring up another Liu Cixin, but the Three-Body Problem series on Netflix, I really loved. I thought that was a great rendition of the book series.
**Lenny：** AI 领域领导者们的共同特征就是没时间看电视电影，我完全理解。有什么最近发现的你特别喜欢的产品吗？
**Lenny:** So, the common pattern across AI leaders is no time to watch TV or movies, which I completely understand. Is there a favorite product you've recently discovered that you really love?
**Boris Cherny：** 我要来做一波自家广告了——Co-work。因为这确实是一个改变了我生活的产品，我一直都在用它。特别是 Chrome 集成，真的非常出色。它帮我交了一张交通罚单，帮我取消了几个订阅。那些繁琐的事情它帮我处理掉了，太棒了。
**Boris Cherny:** I'm going to shill a little bit and just say co-work, because this is legitimately the one product that's been pretty life-changing for me, just because I have it running all the time. And the Chrome integration in particular is just really excellent. It's been like, it paid a traffic fine for me. It canceled a couple subscriptions for me. Just like the amount of tedious work it gets out of the way is awesome.
**Boris Cherny：** 我不知道算不算产品，但再推荐一个播客吧——当然除了 Lenny's Podcast 之外——
**Boris Cherny:** I also don't know if it's a product, but maybe I'll also -- another podcast that I really love, obviously besides Lenny's, is --
**Lenny：** 当然。
**Lenny:** Obviously.
**Boris Cherny：** 是 Ben 和 David 做的 Acquired 播客。真的特别棒。他们深入商业历史并把它讲活的方式非常厉害。如果你还没听过，我推荐从任天堂那一期开始。
**Boris Cherny:** Yeah, it's the Acquired podcast by Ben and David. It's just super awesome. I feel like the way that they get into business history and bring it alive is really, really good. And I would start with the Nintendo episode if you haven't listened to it.
**Lenny：** 好建议。说到 Co-work，给还没试过的人解释一下：你输入一个想完成的任务，它可以打开 Chrome 帮你做事。我看到 Anthropic 有个人休陪产假，他让 Co-work 帮他填那些烦人的医疗表格——就是那种很讨厌的 PDF。它直接打开浏览器、登录、填表、提交。
**Lenny:** Great tip. With co-work, just so people understand if they haven't tried this, basically you type something you want to get done and it can launch Chrome and just do things for you. I saw one of the -- someone went on paternity leave from Anthropic and he had it fill out these medical forms for him, these really annoying PDFs where it just loads up the browser, logs in, fills them out, and submits them.
**Boris Cherny：** 对，没错。它现在真的就能用。一年前我们也试过这个实验，当时不行，因为模型还没准备好。但现在真的可以了，太神奇了。我觉得很多人不太理解这是什么，因为他们以前没用过智能体。这种感觉跟一年前的 Claude Code 很像。但就像我说的，Co-work 早期的增长速度比 Claude Code 当年快得多。所以我觉得它正在突破那个认知壁垒。
**Boris Cherny:** Yeah, exactly. Exactly. And it actually just kind of works. Like, we tried this experiment a year ago and it didn't really work because the model wasn't ready, but now it actually just works. And it's amazing. I think a lot of people just don't really understand what this is because they haven't used an agent before. And it just feels very, very similar to me to Claude Code a year ago. But like I said, it's just growing much faster than Claude Code did in the early days. So, I think it's starting to break through a bit.
**Lenny：** 你提到的 Chrome 扩展也可以单独使用，它嵌在 Chrome 里，你可以直接跟 Claude 对话，它能看到你的屏幕和浏览器。你可以让它帮你做事、告诉你正在看什么、总结你正在看的内容之类的。
**Lenny:** And there's also this Chrome extension that you mentioned that you could just use standalone, that sits in Chrome, and you could just talk to Claude looking at your screen, at your browser, and have it do stuff, have it tell you about what you're looking at, summarize what you're looking at, things like that.
**Boris Cherny：** 没错。对于刚开始用 Co-work 的人，我的建议是：下载 Claude 桌面应用，去 Co-work 标签页，就在 Code 标签旁边。我建议先让它使用一个工具——比如整理你的桌面、总结你的邮件之类的。或者让它回复你最重要的三封邮件——它现在也帮我回邮件了。
**Boris Cherny:** Exactly. Exactly. For people that are just starting to use co-work, the thing I recommend is, you download the Claude Desktop app, you go to the co-work tab, it's right next to the code tab. The thing that I recommend doing is start by having it use a tool. So like, clean up your desktop, or summarize your email, or something like this. Or, you know, respond to the top three emails -- like, it actually just responds to emails for me now too.
**Boris Cherny：** 第二步是把工具串联起来。比如你说"看看我最新的邮件，然后发 Slack 消息"，或者"把它们放进一个电子表格"。举个例子，我用它来做所有的项目管理。我们整个团队有一个电子表格，每个工程师一行，每周每个人填写一次状态更新。每周一 Co-work 就会自动在 Slack 上给没有填写状态的工程师发消息。所以我不用再做这件事了。这就是一个提示词（prompt），它会搞定所有的事。
**Boris Cherny:** The second thing is connect tools. So, if you say, "Look at my top emails and then send Slack messages," or, you know, "Put them in a spreadsheet," or something. Or, for example, I use it for all my project management. So we have a single spreadsheet for the whole team. There's a row per engineer. Every week everyone fills out a status, and every Monday co-work just goes through and it messages every engineer on Slack that hasn't filled out their status. And so I don't have to do this anymore. And this is just one prompt. It'll do everything.
**Boris Cherny：** 第三步就是并行运行多个 Claude。用 Co-work，你可以同时运行任意多个任务。启动一个任务，然后再启动另一个，再另一个——我把它们启动好，然后就去倒杯咖啡，让它们跑着。
**Boris Cherny:** And then the third thing is just run a bunch of Claudes in parallel. So with co-work, you can have as many tasks running as you want. So it's like, start one task, you know, I have this project management thing running, then I'll have it do something else, then something else, and I'll kick these off and then I just go get a coffee while it runs.
**Lenny：** 我会附上一篇帖子的链接，里面分享了很多以前用 Claude Code 做的事情，现在都可以通过 Co-work 来做。很多人看了之后会说"哇，我没想到还能这么用"。我觉得人们需要看到这些例子才会意识到——"哦，原来我还可以这样做。"
**Lenny:** There's a post I'll link to that shares a bunch of ways people use what was previously Claude Code, and now you could just do through co-work, because a lot of this is just like, "Oh wow, I hadn't thought I could use it for that." And once you see these examples, I think, are what people need to hear of just like, "Oh wow, I didn't know I could do that."
**Boris Cherny：** 对，其中一些灵感其实也来自你，Lenny。你之前发过一篇帖子，好像是"50 个 Claude 的非技术用例"之类的。我们有一位 PM 用那篇帖子作为发布前评估 Co-work 的方式。当 Co-work 能完成其中 48 个的时候，他们就觉得"好，差不多了。"
**Boris Cherny:** Yeah, I think a lot of this was also -- some of this was also inspired by you, Lenny. You had this post about, it was like 50 non-technical use cases for Claude or something like this. So we actually -- one of our PMs used that as a way to evaluate co-work before we released it. And I think at the point where we hit where co-work was able to do like 48 out of the 50, they were like, "Okay, it's pretty good."
**Lenny：** 哇，我之前不知道这个。[笑声] 太酷了。我变成了一个评估基准（eval）。
**Lenny:** Wow. I did not know that. [laughter] That is awesome. I've become an eval.
**Boris Cherny：** 对。感觉怎么样？
**Boris Cherny:** Yeah. How does that feel?
**Lenny：** 棒极了。我感觉自己对 AI 的未来有价值了。
**Lenny:** Amazing. I feel like I'm valuable to the future of AI.
**Boris Cherny：** 这算是反向突破吧。[笑声]
**Boris Cherny:** This is like reverse breaking through. [laughter]
**Lenny：** 哇，那真的太酷了。好吧，我好奇最后那两个没完成的是什么。总之，再问两个问题。你有什么经常在工作或生活中回味的人生座右铭吗？
**Lenny:** Wow, that is so cool. Wow. Okay. I wonder what those last two are. Anyway, okay, two more questions. Do you have a favorite life motto that you often come back to in work or in life?
**Boris Cherny：** 用常识。我觉得我看到的很多失败，尤其是在工作环境中，就是人们没有用常识。他们不假思索地遵循流程，不假思索地做某件事。或者他们在做一个不好的产品、不是好主意的东西，就是跟着惯性走，完全不去思考。我看到的最好的结果都来自于那些用第一性原理思考、培养自己常识的人。如果某件事闻起来不对劲，那它大概率就不是个好主意。我觉得这是我给同事们说得最多的一条建议。
**Boris Cherny:** Use common sense. I think a lot of the failures that I see, especially in a work environment, is people just failing to use common sense. Like, they follow a process without thinking about it. They just do a thing without thinking about it. Or they're working on a product that's not a good product or not a good idea and they're just following the momentum and not thinking about it. I think the best results that I see are people thinking from first principles and just developing their own common sense. Like, if something smells weird, then, you know, it's probably not a good idea. So I think this is the single advice that I give, you know, to co-workers more than anything too.
**Lenny：** 我觉得光这一条就能做一整期播客了。什么是常识？怎么建立常识？但我们长话短说。最后一个问题。你最近在 Twitter/X 上越来越活跃了。我很好奇为什么，以及你在 Twitter 上的体验怎么样？因为你在 Twitter/X 上的互动量很高。
**Lenny:** And I feel like that alone could be its own podcast conversation. What is common sense? How do you build it? But we'll keep this short. Final question. So you've gotten more active on Twitter/X. I'm curious just why, and just what's your experience been with Twitter, the world of Twitter? Because you get a lot of engagement on Twitter/X.
**Boris Cherny：** 我之前一直只用 Threads，因为我当年其实参与了 Threads 的开发。我也喜欢它的设计，是一个非常干净的产品。
**Boris Cherny:** So for a long time I used Threads exclusively because I actually helped build Threads a little bit back in the day. And I also just like the design. It's a very clean product. I really like that.
**Boris Cherny：** 我开始用 Twitter 其实是因为无聊。去年十二月，我和太太在欧洲到处逛，算是数字游牧。去了哥本哈根，去了几个不同的国家。对我来说那就是一个编程假期——每天写代码，这是我最喜欢的假期方式，就是整天写代码，太棒了。
**Boris Cherny:** I started using Twitter because I was actually bored. So, in December, my wife and I were traveling around in Europe. We were just kind of nomading around. We went to Copenhagen, went to a few different countries. And for me it was just like a coding vacation. So every day I was coding and that's my favorite kind of vacation, just to code all day. It's the best.
**Boris Cherny：** 到某个时候我有点无聊了，有那么几个小时想不到要做什么。我想："好吧，接下来做什么？"于是打开了 Twitter。看到有人在讨论 Claude Code，我就开始回复。然后我想："也许我应该做的是找找有没有人遇到了 bug、有什么反馈。"所以我自我介绍了一下，问大家有没有 bug 或反馈。我觉得他们对我们现在处理反馈的速度感到很惊讶。
**Boris Cherny:** And at some point I just kind of got bored and I ran out of ideas for, you know, a few hours. I was like, "Okay, what do I want to do next?" And so I opened Twitter. I saw some people tweeting about Claude Code and then I just started responding. And then I was like, "Okay, maybe actually what I think I should do is look for people, look for bugs that people have, maybe people have bugs or kind of feedback." And so I kind of introduced myself, asked if people had a bunch of bugs and feedback. And I think they were kind of surprised by the pace at which we're able to address feedback nowadays.
**Boris Cherny：** 对我来说这太正常了。如果有人有 bug，我大概几分钟就能修好，因为我启动一个 Claude，只要描述足够清楚，它就会去处理。然后我就去做别的事，回复下一个。但我觉得对很多人来说这个速度是令人惊讶的。所以那很酷。在 Twitter 上的体验一直很好——跟人互动、了解人们想要什么、听到 bug 和功能请求，这些都很棒。
**Boris Cherny:** For me, it's just so normal. Like, if someone has a bug, I can probably fix it within a few minutes because I just start a Claude, and as long as the description is good, it'll just go and do it, and then I'll go do something else and answer the next thing. But I think for a lot of people it was pretty surprising. So that was really cool. And yeah, the experience on Twitter has been pretty great. It's been awesome just engaging with people and seeing what people want, hearing about bugs, hearing about features.
**Lenny：** 我前几天看到有人在 Twitter 上向 Nikita Beer 抱怨，发了好多帖子说东西坏了，就那种"天哪，这是怎么回事？"
**Lenny:** I saw complaints to Nikita Beer the other day on Twitter, just posting many threads and it was breaking. And just like, "Oh man, what's going on here?"
**Boris Cherny：** 对，是有个 bug。希望现在修好了。
**Boris Cherny:** Yeah. Yeah. Yeah. There was a bug. I hope it's fixed now.
**Lenny：** 太棒了。天哪，Boris，我可以跟你聊上几个小时。我让你走吧。非常感谢你来做这期节目。你太棒了。大家可以在哪里找到你？听众们怎么能帮到你？
**Lenny:** Amazing. Oh man, Boris, I could chat with you for hours. I'll let you go. Thank you so much for doing this. You're wonderful. Where can folks find you online? How can listeners be useful to you?
**Boris Cherny：** 在 Threads 或 Twitter 上找我就好，那是最简单的方式。请随时标记我——发 bug、发功能请求、告诉我们缺了什么、我们能怎样把产品做得更好、你喜欢什么、你想要什么。我特别特别喜欢听到这些。
**Boris Cherny:** Yeah, find me on Threads or on Twitter. That's the easiest place. And please just tag me on stuff. Send bugs, send feature requests, what's missing, what can we do to make the products better? What do you like? What do you want? I love, love hearing it.
**Lenny：** 太好了。Boris，非常感谢你来参加节目。
**Lenny:** Amazing. Boris, thank you so much for being here.
**Boris Cherny：** 谢谢你，Lenny。
**Boris Cherny:** Cool. Thanks, Lenny.
**Lenny：** 各位，再见。
**Lenny:** Bye, everyone.
**Lenny：** 非常感谢收听。如果你觉得这期节目有价值，可以在 Apple Podcasts、Spotify 或你常用的播客应用上订阅本节目。也请考虑给我们评个分或留个评论，这对帮助其他听众发现这个播客非常有帮助。你可以在 lennispodcast.com 上找到所有往期节目或了解更多关于本节目的信息。下期见。
**Lenny:** Thank you so much for listening. If you found this valuable, you can subscribe to the show on Apple Podcasts, Spotify, or your favorite podcast app. Also, please consider giving us a rating or leaving a review, as that really helps other listeners find the podcast. You can find all past episodes or learn more about the show at lennispodcast.com. See you in the next episode.
