Hey everyone! 👋 I've been experimenting with AI coding agents, and one thing kept bothering me: AI is getting really good at building applications. But who's actually testing them like real users would? Sure, we have E2E tests. But those usually follow scenarios we've already anticipated. Real users are different. They double-click buttons, abandon forms, open multiple tabs, lose their internet connection, or do things nobody thought to test. So I built Chaosfolk 👾, my first open-source project. The idea is pretty simple: Instead of writing every test scenario manually, you unleash a group of simulated AI users on your application. Each one gets its own behavior profile, goals, and browser session. Some are impatient. Some get distracted. Some struggle with unfamiliar interfaces. Others explore everything. Chaosfolk also introduces failures like network interruptions, latency, and storage errors. But here's the part I really wanted to get right: Finding something suspicious isn't enough. I wanted reproducible evidence. Chaosfolk captures browser actions, screenshots, and execution traces, then uses replay scenarios and control runs to help verify whether a problem is reproducible. It's built with Python and Playwright, packaged as an Agent Skill for AI coding workflows. ✅ Open source (MIT license) ✅ Real browser interactions ✅ Simulated user behaviors ✅ Fault injection ✅ Replayable test scenarios ✅ HTML reports with evidence It's still in alpha, and there's plenty of room for improvement. I'm especially interested in feedback from people working with AI coding agents, browser automation, or QA. What would you improve? What kinds of user behaviors or failure scenarios would you add? GitHub: https://github.com/loukan42/chaosfolk Would love to hear your thoughts, even if it's criticism! 👾   submitted by   /u/LoukaN [link]   [comments]