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多年来，我一直默默专注于我的工作，但现在我感到有必要指出一个日益明显的问题。 1. 正确模型 ≠ 采用模型历史事实：在前端生态系统中，胜出的不是那些创建最精确抽象的人，而是那些以最少摩擦提供“工作感觉”的人。结果：正确的思维模型 → 采用率低，而错误但简单的模型 → 爆发式增长。这并非巧合。 2. 为什么基于意图/确定性模型没有成功？原因显而易见。认知负担：意图 + 有限状态机 + 时间线需要： “我知道我在做什么”，“我正在设计生命周期”，“我正在有意识地产生状态。” 但对于当今的前端人群来说，这并非一个特性，而是一个障碍。因为生态系统奖励的是：快速演示、快速工作、快速简历加分对于拥有这种背景的人来说：有限状态机 = 恐惧，确定性 = 不必要，显式生命周期 = “过度工程” UI 的容错率非常高：在后端：错误的抽象 → 系统崩溃，金钱损失，数据损坏。在 UI 中：加载指示器多转了一会儿，状态出现故障，用户刷新。换句话说：前端错误可以被容忍很长时间。这使得糟糕的抽象得以生存。 React 的副作用：“隐藏，保存”文化： React 做了这些：隐藏了生命周期，隐藏了并发，隐藏了协调。结果：“即使你不理解它，它也能工作”的文化。这种文化：培养了仪式性的死记硬背，而不是工程。写一个 hook，如果它有效，那就好。但它为什么有效，它是如何工作的？没有人问。 “氛围编码者”的爆发不是原因，而是结果因为这种情况并非始于 ChatGPT、Gemini、Cluade 或 Copilot。这些加速了现有的衰退。基础已经奠定。已经有一群人不知道抽象是什么，不知道状态是什么，不知道并发是什么，但却记住了框架。 AI 只是做了这件事：它形式化了“我不需要思考”的感觉。 3. 不是框架，而是基础设施层最大的错误是：“让我们构建一个新的 UI 框架。” 这会消亡，而且确实消亡了。 -> “https://dayssincelastjsframework.com/” 然而，如果创建了一个将自己定位为运行时层、意图引擎、状态协调器、提交解析器的结构，它就会成为 React、Vue 和 Svelte 等巨头之上的一个隐形层。采用是这样的：“如果你想用就用”或者“如果你不想用就完全看不到它”。 4. 最重要的教训（也许是所有教训）我清楚地写下这句话：“前端世界目前没有在产生工程，而是在产生类似传送带的行为。” 这就是为什么正确的抽象不会立即获胜，但它不可避免。因为：UI 变得越来越有状态，AI 交互正在增加，并发是不可避免的。在这一点上：“加载指示器 + hook”模型将会崩溃，人们将不得不再次问“为什么？”。而且是的：“在这种混乱中呼吁标准是毫无意义的。” 但当从正确的层、正确的问题和正确的痛点入手时，这种模型不可避免地会创造价值。这与炒作无关，而与耐心有关。 --- 说了这么多，我意识到有抱怨，但解决方案在哪里？我打开了一个 GitHub 仓库，并添加了一个“AI 支持的”RFC 提案。欢迎任何想加入的人参与。谢谢。 https://github.com/laphilosophia/temporal-intent-resolution

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For many years, I focused quietly on my work, but now I feel compelled to point out a problem that is becoming increasingly apparent.--1. Correct Model ≠ Adopted ModelHistorical fact: In the frontend ecosystem, the winners aren't those who create the most accurate abstraction; they're those who provide the “feel of working” with the least friction.The result: correct thought model → low adoption and incorrect but easy model → explosion.This is no coincidence.2. Why Didn't Intent-Based / Deterministic Models Succeed?There are several obvious reasons.Cognitive Tax:Intent + FSM + timeline requires:“I know what I'm doing,” “I'm designing the lifecycle,” “I'm consciously producing the state.”But for today's FE crowd, this isn't a feature, it's a barrier. Because the ecosystem rewarded: quick demo, quick job, quick CV lineFor someone with this profile:FSM = fear, determinism = unnecessary, explicit lifecycle = “overengineering”Failure Tolerance is Very High in UI:In the backend: wrong abstraction → system crashes, money is lost, data is corrupted.In the UI: the spinner spins a moment too long, the state glitches, the user refreshes.In other words: Frontend errors can be tolerated for a long time. This has allowed bad abstractions to survive.React's Side Effect: The “Hide, Save” Culture:React did this: hid the lifecycle, hid concurrency, hid reconciliation.Result: a “it works even if you don't understand it” culture.This culture: grew ritual memorization, not engineering.Write a hook, if it works, fine. But why does it work, how does it work? No one asks.The Vibe-Coder Explosion is Not a Cause, but a ConsequenceBecause this situation didn't start with ChatGPT, Gemini, Cluade or Copilot. These accelerated the existing decay. The groundwork was already laid.There was already a crowd that didn't know abstraction, didn't know what state was, didn't know what concurrency was, but had memorized the framework.AI just did this: it formalized the feeling of “I don't need to think.”4. Not a Framework, but an Infrastructure LayerThe biggest mistake was: “Let's build a new UI framework.” This dies, and it did die.-> “https://dayssincelastjsframework.com/”However, if a structure is created that positions itself as a runtime layer, intent engine, state coordinator, commit resolver, it becomes an invisible layer above giants like React, Vue, and Svelte.Adoption comes like this: “Use it if you want” or “Don't see it at all if you don't want to.”5. The Most Important Lesson (Perhaps All of Them)I'm writing this sentence clearly: “The frontend world is not producing engineering right now; it's producing conveyor belt-like behavior.”That's why the right abstraction doesn't win immediately, but it is inevitable.Because: UIs are becoming more stateful, AI interaction is increasing, concurrency is inevitable.At this point: the “spinner + hook” model will collapse, and people will have to ask “why?” again.And yes: “It's pointless to shout for standards in this mess.”But when approached from the right layer, with the right problem, and the right pain point, this model inevitably creates value.This isn't about hype; it's about patience.---After all these words, I realized there's complaint, but where's the solution?I opened a GitHub repo and added an “AI-supported” RFC-Proposal. Participation is open to anyone who wants to join.Thank you.https://github.com/laphilosophia/temporal-intent-resolution

关于 FE 生态系统的一个（谦逊的）新提议