Working with AI Feels More Like Leadership Than Coding

与人工智能共事，感觉更像是领导而非编程

For most of my career, code gave me certainty. A program did what its instructions told it to do. If the same input produced a different result, we called it a bug. 在我职业生涯的大部分时间里，代码给予我的是确定性。程序只会执行指令所要求的内容。如果相同的输入产生了不同的结果，我们称之为“漏洞”（bug）。

People were never like that. As a leader, I can explain a task and get exactly what I asked for. I can also get something better because a colleague understood the intent behind the request. Sometimes the result shows that I was not as clear as I thought. 人却从不如此。作为一名领导者，我可以解释一项任务并得到我所要求的确切结果。有时我甚至能得到更好的结果，因为同事理解了请求背后的意图。有时结果则表明，我并没有自己想象中表达得那么清晰。

Working with AI feels closer to the second experience. AI runs on software, but working with it is not fully predictable. The same request can produce a different answer. It can make a useful connection, miss an obvious point, or surprise me with an approach I had not considered. 与人工智能共事的感觉更接近后者。AI 虽然运行在软件之上，但与它协作并非完全可预测。同一个请求可能会产生不同的答案。它可能会建立有用的关联，忽略显而易见的要点，或者用一种我未曾考虑过的方法给我带来惊喜。

This is frustrating when I treat AI like a compiler. It becomes more useful when I treat the interaction as a form of collaboration. That does not make AI a person. It has no lived experience, accountability, or human judgment. The comparison is about how we work. 当我把 AI 当作编译器来对待时，这种不确定性会令人沮丧。但当我把这种互动视为一种协作时，它就变得更有用了。这并不意味着 AI 成为了一个人。它没有生活经验、责任感或人类的判断力。这种类比仅仅是关于我们如何工作。

Good leaders do more than issue instructions. They share context, explain the desired outcome, set boundaries, and respond to what comes back. The same habits improve my work with AI. A good prompt helps, but a shared working context helps more. Examples, corrections, and reusable instructions reduce misunderstandings. 优秀的领导者不仅仅是下达指令。他们会分享背景信息、解释预期的结果、设定界限，并对反馈做出回应。同样的习惯也能改善我与 AI 的协作。好的提示词（prompt）固然有帮助，但共享的工作背景更有帮助。示例、修正和可复用的指令能减少误解。

Over time, the system becomes better aligned with how I think and what I need from it. The investment is not in pretending that AI is human. It is in becoming better at expressing intent. 随着时间的推移，系统会越来越契合我的思维方式以及我对它的需求。这种投入并非为了假装 AI 是人类，而是为了让自己更善于表达意图。

We spent years learning how to tell computers exactly what to do. Now we also need to explain why the work matters, what a good result looks like, and where judgment is needed. For me, that is the shift. 我们花了多年时间学习如何告诉计算机确切要做什么。现在，我们还需要解释这项工作为何重要、什么样的结果才算好，以及在哪些地方需要判断力。对我而言，这就是转变所在。

AI is making software work less like issuing commands to a machine and more like leading through a conversation. The technology is new. The leadership skills are not. AI 正在让软件工作变得不再像是在向机器下达命令，而更像是在通过对话进行领导。技术是新的，但领导力技能并非如此。

This note led to a thoughtful discussion on Hacker News. I recommend reading through all the comments; the agreement, criticism, and different experiences add more to the idea than I could fit here. 这篇笔记在 Hacker News 上引发了深入的讨论。我建议大家通读所有的评论；其中的共鸣、批评和不同的经验，比我在此处所能涵盖的内容更能丰富这一观点。