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我一直想写下这个内容，因为它的效果出乎意料地可重复，我希望有人能早些告诉我。在过去一年左右的时间里，相较于我2019年的开发基准，我的开发速度轻松提高了20倍，有时甚至更多。这并不是因为我打字更快，或者因为我偷工减料，而是因为我改变了使用人工智能的方式。简而言之：我不在编辑器中使用人工智能。我在浏览器中并行使用两个人工智能，提供完整的上下文。以下是我的设置：我保持两个标签页打开：一个人工智能充当“构建者”。它获取大量上下文并进行繁重的工作。另一个人工智能充当审查者。它只查看差异并尝试找出错误。就这样。没有插件，没有特殊工具。仅仅是浏览器标签和一个终端。重要的是上下文。与其请求代码片段，我会粘贴整个文件或模块，并解释目标。我要求人工智能首先解释方法，包括权衡，然后再编写代码。这迫使我保持对架构的控制，而不是接受一个我不理解的代码块。一个典型的流程如下： 1. 粘贴几个相关的文件（通常跨语言）。 2. 描述我想要的更改，并请求选项的解释。阅读并总结概念、维基百科等。 3. 选择一种方法。进行广泛的关于权衡、概念、对抗性安全等的讨论。寻找操作系统允许的实现方式。 4. 让人工智能在所有文件中实现它。 5. 将差异复制到第二个人工智能中，要求它查找回归、缺失的参数或微妙的错误。 6. 修复它发现的问题。发布。第二个人工智能捕捉了许多我在快速移动时可能会错过的事情。例如，“你更改了这个调用签名，但没有更新一个调用者”或“这个默认值微妙地改变了行为”。让我感到惊讶的是跨栈工作的速度有多快。以前因为跨越边界（Swift → Obj-C → JS，或后端 → 前端）而停滞的事情，现在变得简单明了，因为人工智能可以一次性推理所有内容。我对“手术式编辑”保持严格。我不让人工智能重写文件，除非这明确是任务。我要求添加或更改的确切行。这保持了差异小且可审查。这与自动补全风格的工具非常不同。那些工具非常适合局部编辑，但它们仍然让你在文件之间担任整合者。这种方法则颠倒了这一点：你仍然是架构师和审查者，人工智能负责整合工作，而第二个人工智能进行合理性检查。这大约花费我每月40美元。真正的成本是自律：始终提供上下文，始终审查差异，绝不粘贴你不理解的代码。我分享这个是因为它对我来说是一次真正的飞跃，而不是噱头。乐意回答有关限制、失败模式或此方法何时失效的问题。以下是我为我们团队的开发者整理的维基式概述： https://community.intercoin.app/t/ai-assisted-development-playbook-how-we-ship-faster-without-breaking-things/2950

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I’ve been meaning to write this up because it’s been surprisingly repeatable, and I wish someone had described it to me earlier.Over the last year or so, my development speed relative to my own baseline from ~2019 is easily 20x, sometimes more. Not because I type faster, or because I cut corners, but because I changed how I use AI.The short version: I don’t use AI inside my editor. I use two AIs in parallel, in the browser, with full context.Here’s the setup.I keep two tabs open:One AI that acts as a “builder”. It gets a lot of context and does the heavy lifting.One AI that acts as a reviewer. It only sees diffs and tries to find mistakes.That’s it. No plugins, no special tooling. Just browser tabs and a terminal.The important part is context. Instead of asking for snippets, I paste entire files or modules and explain the goal. I ask the AI to explain the approach first, including tradeoffs, before it writes code. That forces me to stay in control of architecture instead of accepting a blob I don’t understand.A typical flow looks like this:1. Paste several related files (often across languages).2. Describe the change I want and ask for an explanation of options. Read and summarize concepts, wikipedia, etc.3. Pick an approach. Have extensive conversations about trade-offs, concepts, adversarial security etc. Find ways to do things that the OS allows.4. Let the AI implement it across all files.5. Copy the diff into the second AI and ask it to look for regressions, missing arguments, or subtle breakage.6. Fix whatever it finds.Ship.The second AI catches a lot of things I would otherwise miss when moving fast. Things like “you changed this call signature but didn’t update one caller” or “this default value subtly changed behavior”.What surprised me is how much faster cross-stack work gets. Stuff that used to stall because it crossed boundaries (Swift → Obj-C → JS, or backend → frontend) becomes straightforward because the AI can reason across all of it at once.I’m intentionally strict about “surgical edits”. I don’t let the AI rewrite files unless that’s explicitly the task. I ask for exact lines to add or change. That keeps diffs small and reviewable.This is very different from autocomplete-style tools. Those are great for local edits, but they still keep you as the integrator across files. This approach flips that: you stay the architect and reviewer, the AI does the integration work, and a second AI sanity-checks it.Costs me about $40/month total. The real cost is discipline: always providing context, always reviewing diffs, and never pasting code you don’t understand.I’m sharing this because it’s been a genuine step-change for me, not a gimmick. Happy to answer questions about limits, failure modes, or where this breaks down.Here is a wiki-type overview I put together for our developers on our team: https://community.intercoin.app/t/ai-assisted-development-playbook-how-we-ship-faster-without-breaking-things/2950

告诉HN：我写代码和发布代码的速度比五年前快了大约20到50倍。