Why I stopped using DOM locators for End-to-End tests altogether—and replaced them with computer vision

If you’ve ever written End-to-End (E2E) tests using Selenium, Cypress, or Playwright, you know the ultimate pain: flakiness. You write a perfect test. It runs green. Two weeks later, a frontend developer changes a wrapper div, renames a CSS class, or adds a promotional pop-up. Suddenly, your CI/CD pipeline is red, and your test fails with the dreaded ElementNotInteractableException. I’ve spent years in QA automation, and I realized we are testing UIs fundamentally wrong. Humans don't look at the DOM to click a button. We look at the screen. So, why do our automated tests rely on hidden HTML structures? I decided to fix this and built AIQA Systems - an automation approach that ditches DOM locators completely in favor of Computer Vision (CV) and Large Language Models (LLMs). Here is how it works, what it costs, and why I believe this is the future of QA. ❌ The Problem with the DOM-based Approach Standard automation relies on finding elements via IDs, XPaths, or CSS selectors. // The old