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这实际上对我来说是有道理的,因为人工智能在图像、视频、用户界面以及任何可以通过肉眼验证的领域都很出色。
而 Replit 生成的有用原型,其功能可以立即通过视觉进行验证。它使任何应该简单的事情变得简单。

2025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.
我现在对 Replit 的看法就是这样。它几乎就像计算机科学中的最小描述长度(MDL)概念。
如果它在概念上很简单,如果你想要的东西实际上可以用几句话或一个互动会话来描述(因为提示也是一种技能),那么 Replit 就让这一切变得简单。
对于任何类型的数据分析、CRUD 应用程序或关于 API 应该如何工作的示例代码,即使你是一个熟练的开发者,Replit 也非常有用。
而对于那些非技术但善于表达的用户,他们现在可以私信任何内容。如果他们付出一些努力,他们可以展示出他们脑海中的想法。
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