跳到正文
原文
Google AI:DEV 作者专属(RSS)· Junyoung Park·· 2 小时前AI 评分29

前咖啡馆店主用 AI 打造本地 AI 同事 ARCHE,无需截图即可后台操控 Windows PC

I'm not a programmer. I ran cafes. Then I built an AI coworker that uses my PC without stealing my screen.

AI 导读

不会编程的前咖啡馆店主 Junyoung 在 Windows PC 上构建了本地 AI 同事 ARCHE,可在后台操作应用而不占用屏幕,并能感知当前窗口状态、将任务拆分给多个 AI 并行处理、跨重启记忆。

正文

Junyoung Park

A year ago I was running small shops in Seoul - a cafe, a convenience store, food. I can't really code. But I kept watching AI "computer use" demos and thinking: this is amazing, and also I would never use it every day.

The loop is always the same: take a screenshot, think, click, take another screenshot. Each step takes seconds. While it works, you can't touch your own computer. When the session ends, it forgets everything. And it does one thing at a time.

So I spent the last months building my own, mostly by talking to AI models and following my gut. I call it ARCHE. It's a local AI coworker that lives on my Windows PC. I use it every day, for real work, not demos.

What it does differently

  • Works in the background, no screenshots. It operates apps behind what I'm doing. I keep using my PC; it keeps working.
  • Knows what's happening on my PC right now - which window is open, what just changed - without me explaining.
  • Splits big jobs across several AI workers at once, and they report back.
  • Remembers. Decisions and conversations from weeks ago, in Korean or English, with the original record.
  • Survives restarts. If the app closes mid-task, it picks up where it stopped instead of starting over or repeating things.

Some honest numbers (from my own usage logs)

  • Over 3 days: 378 requests from me, 84% finished end-to-end.
  • Same 3 days: 227 jobs handed to parallel AI workers.
  • Across 24 real tool calls, what it sends to the model went from 668,083 to 95,131 characters - about 86% less, so it's faster and cheaper per step.
  • "Find this YouTube video and play it": the search part takes about 1 second.

These are from one person's machine, not a lab benchmark. I'd rather show small real numbers than big made-up ones.

Why I'm posting

Two reasons.

  1. Feedback. If you've used Claude Code, Codex or other computer-use agents on your own machine - what made you stop? What would make you keep one running all day?
  2. I'm looking for people who believe in this. I have no company, no funding, no team. If this sounds like something that should exist, I'm raising a small pre-seed round, and I'd also be grateful for a coffee-sized tip. Either way, an honest comment helps a lot.

More details and a one-page summary: https://telegra.ph/ARCHE---local-AI-coworker-10-02

Disclosure: my English is not great, so this post was drafted and posted by ARCHE itself on my behalf, from my own usage logs. The story and the numbers are mine - and yes, that is also a small demo of what it does.

Thanks for reading. I'm happy to answer anything in the comments (slowly - please be patient with me).

  • Junyoung

来源:Google AI:DEV 作者专属(RSS) · dev.to