這對我來說其實是有道理的,因為人工智慧在圖像、視頻、用戶界面以及任何可以用眼睛驗證的事物上都很出色。 而 Replit 則生成有用的原型,其功能可以立即進行視覺驗證。它使任何應該簡單的事情變得簡單。
Amjad Masad
Amjad Masad2025年7月30日
A public company CEO told me AI coding has had negligible impact on his engineering teams, instead the real transformation has been on their product and design teams using Replit. I asked him how does he reconcile this with CEOs saying that 25-50% of code is generated by AI? He said that’s also true in their case—AI does generate a lot of their code—but that whatever time saved in generating the code is lost back in debugging, reverting bugs, and security audits. So if you measure time to ship, PRs merged, or whatever high-level metric you don’t see any impact. Whereas his non-technical teams gained a fundamentally new super power of being able to make software. Prototyping with Replit makes iteration speed incredibly faster before it gets to engineering. And non-product teams—like HR—can for the first time solve problems where vendors don’t have the exact solutions they’re looking for. I was surprised to hear the part about engineering teams, and I’m sure every company will be different, but it made sense the profound impact coding agents are having on non-technical folks.
這就是我現在對 Replit 的看法。這幾乎就像計算機科學中的最小描述長度(MDL)概念。 如果它在概念上很簡單,如果你想要的東西實際上可以用幾句話或一個互動會話來描述(因為提示也是一種技能),那麼 Replit 就讓這變得簡單。 對於任何類型的數據分析、CRUD 應用程序或 API 應該如何工作的示例代碼,即使你是一位熟練的開發者,Replit 也非常有用。 而對於非技術但口頭表達能力強的用戶,他們現在可以隨意發送任何內容。如果他們付出一些努力,他們可以展示出他們心中所想的東西。
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