When AI Agents Fail: Why Vision Models Beat Automation for Web Testing

AI agents designed to act like QA engineers consistently fail on multi-step web testing because they lose context as the DOM changes with each interaction. This post demonstrates why smarter models don't solve the structural problem—only a fundamentally different architecture does: deterministic code for all actions, with AI relegated to visual observation. This architectural shift has major implications for how teams should approach browser automation at scale.