自动化我的工作
Automating my job away

原始链接: https://austinhenley.com/blog/automatingmyjob.html

在《自动化我的工作》一文中,Austin Z. Henley 探讨了激进自动化所带来的悖论。受“不要做三遍同一件事”这一原则的启发,Henley 开始利用人工智能来自动化他的编程任务。虽然他最初成功地完成了手头的工作,但很快就发现了一个意想不到的陷阱:自动化了显而易见的工作后,掩盖在下层的“粘合性工作”随之浮现。他发现自己不仅没有节省时间,反而需要同时管理多个智能体,导致上下文切换增多且更容易出错。 Henley 认为,真正的进步在于改变工作“方式”,而不仅仅是提高速度。他建议利用人工智能来生成“技能”——即能够自主判断何时以及如何部署脚本的智能体——而不是手动执行代码。他提出了一种主动式方案:让 AI 分析你最近的工作日志,以识别并起草新的自动化机会。最终,Henley 的实验表明,虽然自动化并没有让工作本身变得“更容易”,但它将工作重心从琐碎的执行转向了高层级的协调,并最终使 AI 能够协助设计自身的改进方案。

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原文
Automating my job away - Austin Z. Henley

6/7/2026

A sketch of a human building a robot, which builds a a robot, which builds a bigger robot.

This post was inspired by conversations with several colleagues: Sourav Pal, Gustavo Soares, the Excel Agent Science Team, John Lam, and Dan Morris.

I was talking to a friend who runs a startup and he said that he tells his team, "don't do anything three times." If they have to do something more than twice, they should automate it.

Surely, this is overkill? I already automated 95% of my coding-related tasks. What else would be left for me to do even? And the remaining bits are probably too hard to automate. But... I was wrong. Very, very wrong.

I started trying it. Slowly at first, because automation can be a distraction from getting work done in the moment. By the second week, I was leaning in head first—how deep does the rabbit hole go?

There was an unexpected consequence: By automating the laborious parts of my work, I had, in turn, filled my day with more laborious parts.

A menial task that took me 5 minutes once or twice a day turned into a menial task that I was doing 10-20 times a day. As I had automated the obvious parts, it left behind the glue work that never bothered me before. Now it was a substantial part of my day, and the context switching was killing me. It was no longer a linear step-by-step process since I was juggling several agents concurrently. Because of it, I was now making silly mistakes, which compounded the time and hair pulling.

"It never gets easier, you just go faster" — Greg LeMond

Try it yourself: Anytime you need to do something more than twice, spend the minimal time possible asking Copilot CLI to automate it. Don't write out a spec or give details or provide examples. Let it try to figure it out. Maybe it will fail, oh well, it is only a tiny bit of time spent, and then you can check where it failed and ask it to correct it.

A diagram showing 4 tiers: human writes a script intended for human use, AI generates a script intended for human use, AI generates a skill intended for AI use, and AI self-improves the skill for AI use.

I'm surprised at how far AI can get on the first try even when under-specified. But don't just generate Python scripts for automating tasks. Your agent should be generating skills so that it knows when and how to use the scripts. You shouldn't be running them manually.

Through this process, I also learned that automation allowed me to change how I worked, not just speed up my work.

Recently, Karpathy's autoresearch inspired the world to try self-improving agents. What if we expose a bunch of knobs to the agent and let it experiment continuously? Even better, what if we let the AI come up with new knobs?!

"Copilot, read my Copilot session logs from the last 7 days and propose opportunities for automation. Draft a reusable skill for each."

This article was not written by AI.

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