資料來源#
- A Field Guide to Fable: Finding Your Unknowns
- Anthropic's Boris Cherny: Why Coding Is Solved, and What Comes Next
- Boris Cherny: We Cut 80% of Claude Code's Prompt
- How Anthropic's product team moves faster than anyone else | Cat Wu (Head of Product, Claude Code)
- Loop Engineering
- Thread by @AndrewYNg
摘要#
Claude Code 的創作者與技術主管,任職於 Anthropic。他以工程師為背景,著有 Programming TypeScript。2024 年底透過內部孵化團隊「Anthropic Labs」加入 Anthropic(該團隊也催生了 Claude Code、MCP 與 Anthropic 桌面應用程式,之後解散;到 2026 年中,Mike Krieger 以「第二輪」名義重新組建)。截至 Cat Wu 登上 Lenny's Podcast(2026 年 4 月)時,他是節目史上最受聽眾收聽的來賓。
重要主張與立場#
- 對他來說,寫程式已經解決了。 他所有程式碼都透過 Claude Code 撰寫;曾有好幾天每天提交 150 個 PR。補充說明:對於非常大型的程式碼庫或訓練分布之外的語言,這件事還不成立。
- 以手機驅動的工作流程。 現在大部分工作都在 iOS Claude app 上完成;同時運行約 5–10 個工作階段,白天有「幾百個」代理程式,夜間則有「幾千個」。
- 迴圈是未來。 他大量使用
/loop(由 Claude 排程的 cron 工作)來照看 PR、修復 CI、整理 Twitter 回饋。他認為 Agent Loop Pattern 與平行代理程式扇出是下一個 harness 原語(參見 Harness Shrinkage as Models Improve)。到 2026 年 6 月,這個立場更明確成為 Loop Engineering 的核心論點:「我現在不再提示 Claude。我會讓迴圈去提示 Claude,並想辦法決定接下來該做什麼。我的工作就是寫迴圈。」 - 為下一個模型打造。 他在 2024 年底打造 Claude Code 時就知道產品市場契合度(PMF)尚不存在;2025 年 5 月 Opus 4 推出後,PMF 才到來,之後每次發布都帶來轉變(4.5 → 4.6 → 4.7)。
- 跨領域的通才。 Claude Code 團隊每個人都會寫程式,包括工程經理、PM、設計師、資料科學家、財務人員與使用者研究員(參見 Engineer PM Convergence)。
- 印刷機的類比。 他認為 Printing Press Software Democratization 是理解 AI 輔助軟體建置最恰當的歷史類比。
- 把模型當作生物體,而非系統。(YC 訪談,2026 年 7 月)在模型之上建構「和我做過的所有工程工作都截然不同」——不需要預先設計系統;模型「幾乎就像一個活生生的生物……每一代模型的行為都不一樣,個性也略有不同」,因此應採取經驗式的做法:嘗試、觀察、反覆調整。他反對一招走天下的文化(「別聽 LinkedIn 網紅的話」),並指出過度規格化是資深工程師常犯的錯誤——說明任務、護欄與退出條件,「接著就讓模型放手去做」(Vibe Coding vs. Agentic Engineering)。
- 驗證是引出能力的關鍵。「交給它一個太難的任務,再給它工具,讓它像你自己一樣驗證成果」——驗證「大概是人們最常做不對、也最重要的一件事」。他常用的示範是一個在 Slack 裡的 Claude 工作階段,將 Electron 桌面應用程式改寫成 Swift,並在 macOS VM 裡替兩個應用程式截圖、逐像素比對來驗證;這項工作持續了兩週以上,還會把進度截圖即時發布到自己建立的 Slack 頻道。
- 「寫程式已解決」的適用範圍(更新版)。 仍不包括深層系統程式碼、分散式系統,以及像素層級的 UI 驗證;他在 YC 訪談(2026 年 7 月)進行的聽眾投票顯示,完全使用代理程式撰寫程式碼的人占了很大一部分,約有一半的受訪者使用代理程式撰寫超過 50% 的程式碼。
背景#
他在國中時第一次學會用 TI-83 計算機寫程式——用 BASIC 寫了一個代數解題程式,在數學考試時作弊,後來因微積分超出 BASIC 的能力而改用組合語言重寫;他也曾寫過一份早期的 TI-83 程式設計網路指南。他給資工系學生的建議由此而來:透過打造實用作品來學習,培養設計感、商業感與和使用者交談的能力,不要只學理論。
工作風格(根據 Cat Wu 的說法)#
Cat Wu(Claude Code 與 Cowork 的產品主管)形容 Boris 是「產品願景家」,負責設定 3–6 個月的願景;她則將願景轉化為近期的行動路徑,並處理跨職能協調。他們估計兩人有 80% 的想法相通,剩下 20% 則分屬各自負責的領域。這種分工「界線非常模糊」——也是團隊內 Engineer PM Convergence 的典型情形。
重要引言#
- 「迴圈就是現階段的未來。如果你還沒試過,我非常非常推薦。」
- 「軟體將會完全普及,人人都能打造……我想也許即使是今天,最適合寫會計軟體的人也不是工程師,而是非常優秀的會計師。」
- 「如果你是從頭開始,那就可以用 AI 原生的方式從基礎開始打造。」
相關連結#
- Claude Code — 創建並領導這項產品
- Cat Wu — 產品主管夥伴
- Anthropic — 任職公司
- Agent Loop Pattern — 最重度的使用者,也是主要倡議者
- Loop Engineering — 「我的工作就是寫迴圈」是這門實務得名所依據的兩則從業者引言之一
- Engineer PM Convergence — 他以自己的團隊作為原型
- Seven Powers Applied to AI — 從 Acquired 節目聽眾角度談哪些護城河能在 AI 時代存續
- Printing Press Software Democratization — 他所採用的詮釋框架
- Harness Shrinkage as Models Improve — 他預測 Claude Code「一年後可能只剩 100 行程式碼」;YC 訪談補上了方法論(消融、
SIMPLE=1、不靠提示也能變得更聰明) - Dynamic Workflows: An Algebra for Agents — 他設計了「代理程式代數」(他的函數式程式設計背景讓這項產品成形);他在台上的 Bun 改寫說法,部分已被 Jarred Sumner 的第一手方法論取代——正式環境的說法仍成立,「一個提示、一個動態工作流程」與「超過 10 萬行程式碼」則不成立
- Latent Capability Overhang — 他提出產品端的詮釋框架:「受限」與「產品能力落差」
- Compute Allocator — 「對我來說,寫程式已經解決了」是前提;Thariq Shihipar 的資源分配框架則指出,這件事成立後仍需要什麼角色
- Building Is Cheap, Arguing Is Expensive — 他與 Fiona Fung 討論重構方法時,直接產生三個真實 PR,而非只在白板上討論
- Vibe Coding vs. Agentic Engineering — Karpathy 也有一段平行的「寫程式已解決」歷程;兩人都把自己視為案例研究
- The Three Loops of AI-Native Building — Andrew Ng 將「loop engineering」成為流行語歸功於他(以及 Peter Steinberger),隨後也為這個說法劃定範圍:他的迴圈是三層迴圈中最內層的一層
- Unknowns as the Agentic Bottleneck — Thariq Shihipar 將他列為未知事項很少的典範:「我很清楚,他們知道自己想要什麼,細節也很明確……但他們也會假設未知事項。」
資料來源#
- Anthropic's Boris Cherny: Why Coding Is Solved, and What Comes Next — Sequoia AI Ascent 2026 訪談
- Boris Cherny: We Cut 80% of Claude Code's Prompt — Y Combinator 訪談(2026-07-27,
practitioner-opinion):消融方法、把模型視為生物體的立場、以驗證引出能力、Electron→Swift Slack 實驗、TI-83 背景故事 - How Anthropic's product team moves faster than anyone else | Cat Wu (Head of Product, Claude Code) — Lenny's Podcast(以合作夥伴身分提及)
- Thread by @AndrewYNg — 歸功於他(以及 Steinberger)讓「loop engineering」廣為流傳(
practitioner-opinion) - A Field Guide to Fable: Finding Your Unknowns — 引為未知事項很少的代理程式程式設計師典範(
practitioner-opinion)
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