Original Summary

Playwright gives AI agents a browser, but agent-driven browsing can still be slow and surprisingly token-heavy. I’ve been working on Hyper-Browsing , an open-source agent skill built on Playwright + your local Chrome session. The basic idea is simple: On a new website, the agent uses a set of built-in tools to inspect forms, handle dynamic pages, scroll virtual lists, detect state changes, and extract only the parts of the DOM it actually needs. But the more interesting part is what happens afterward. When a useful workflow succeeds, Hyper-Browsing can save what it learned as site knowledge + reusable scripts. The next time the agent visits that site, it can skip most of the DOM exploration and directly reuse the known path. So the loop becomes: discover → use → learn → reuse A few other things I cared about: compact DOM inspection to reduce agent context/tokens reuse of your existing Chrome login/session local browser control instead of a hosted browser fallback to discovery if a saved workflow breaks after a site update For repeated tasks, it feels roughly ~10x faster to me than having an agent drive plain Playwright from scratch each time. That’s a subjective observation, not a benchmark. There are a couple of demos in the README showing both a first-time visit and a previously learned site: https://github.com/miter37/hyper-browsing If anyone here works with browser agents, I’d especially like feedback on websites or workflows where this approach breaks down or still feels inefficient.   submitted by   /u/Ok-Preference8227 [link]   [comments]

  • 情报分类：技术学习与提效
  • 分类依据：内容涉及技术、AI、软件工具或工程实践
  • 信息来源：Reddit · SideProject
  • 发布时间：2026/9/22 08:10:55