AI 时代的工作方式
2025-09-28
最近稍微有些空闲时间，想做一个小项目。初步想好了 MVP 原型，具体落地去做的时候，自然少不了要考虑 业务方向定位、产品交互设计、技术实现，以及后面的营销推广等等环节。
以前一个人打算做一个小产品，想到有这么一大堆事情需要做，是一个非常让人头疼甚至令人望而却步的事情。这次从寻找业务方向开始，我尝试用 ChatGPT 和我一起来工作，在主页选择输入框右侧的语音模式后，我尝试和 ChatGPT 聊关于项目的想法，希望让他理解我想做的事情，通过一分钟的语音交流，他理解了我想做的东西。然后在我的引导下，我们开始进行产品原型和技术实现的初步讨论，通过我对他给出方案的反馈，他可以马上进行修正和优化反馈。让我吃惊的是，和 ChatGPT 整个交互过程，就像和一个非常懂 业务、产品、技术、运营 的同事交流一样，而且对方能给你秒级的回应，工作效率惊人。
我是做技术的，使用 AI 来帮助写代码已经成为日常。当 ChatGPT 问世的时候，我就预感到未来在技术工种之前不会存在壁垒：前端、客户端、服务端 … 只要精通一门技术方向，通过 AI 的帮助，你可以轻易打破技术方向或技术栈的壁垒。只要一个工程师具备扎实的技术基本功，在一个方向上有过深入的研究，借助 AI 他一定可以具备全栈的能力。这对一些专业领域的职业同样适用，比如律师、医生、会计师、教师等。
通过这次尝试，我发现在 AI 时代，职位之间的壁垒也将被打破。只要你清楚各岗位的日常职责及协作方式，就能跨越这些界限。
在技术工程方向上，相比 AI，人类暂时难以被替代的是理解需求的能力，如果一个工程师能很好的让 AI 理解需求，他就能带着 AI 来帮他干活。
在未来的商业化组织中，也是一样的道理，只要你能完全理解组织中各个角色的工作，你也能像老板一样组织 AI 来帮你完成更复杂的商业任务。
所以，我认为未来 AI 的发展，也将会带来更多的 “一人公司” 的形态。借助 AI，更多的个人，可以做出过去依赖密集的资源投入才能做出的事情。
这是一个挺好的时代，你说呢？
Building with AI: My Experiment in the Age of One-Person Companies
Recently, with a bit of spare time on my hands, I decided to take on a small side project. As soon as I started mapping out how to deliver an MVP prototype, I was quickly reminded of how many moving parts go into building even the simplest product—business positioning, product design, technical implementation, and eventually, marketing and growth.
In the past, thinking through all of these steps on my own often felt overwhelming, sometimes enough to stop me before I even got started. This time, I approached it differently: I invited ChatGPT into the process. Using its voice mode, I began explaining my project ideas. Within a minute of conversation, it grasped what I was trying to do. From there, we moved into early discussions on product design and technical feasibility. I gave feedback, it refined its answers instantly.
What struck me was how natural the collaboration felt. The experience was like working with a colleague who understands business, product, technology, and operations all at once—and one who can deliver thoughtful responses in seconds. The efficiency boost was eye-opening.
As someone with a technical background, I’ve already been using AI to assist with coding on a daily basis. But when ChatGPT first launched, I had an intuition: the traditional walls between technical roles would soon break down. Frontend, backend, client-side—it wouldn’t matter. Master one domain deeply, and with AI’s support, you could easily cross boundaries. With strong fundamentals and domain expertise, any engineer could evolve into a full-stack problem solver.
This experiment reinforced a broader realization: in the AI era, it’s not just technical silos that disappear, but also the barriers between job functions themselves start to collapse. If you understand what different roles in an organization actually do, and how they fit together, AI can help you step into those roles on demand.
For now, the one area where humans still hold the edge is understanding needs. If an engineer can articulate requirements clearly, AI can handle much of the execution. The same logic extends to business: if you understand the responsibilities of each function in a company, you can orchestrate AI much like a founder coordinates a team—driving complex projects forward almost single-handedly.
This is why I believe the future of AI will accelerate the rise of the one-person company. With the right tools, individuals will be able to build products and businesses that once required large teams and heavy capital investment.
It feels like we’re standing at the threshold of a remarkable era. Don’t you think?