AI coding agents can ship a working feature and still break the page users actually see. A visual QA agent closes that gap by driving the app like a user, comparing screenshots, checking flows, and refusing to let a polished pull request hide a broken interface.
AI-assisted development has changed the speed of shipping. A solo builder can ask an agent to add a dashboard, wire a settings page, or refactor onboarding in minutes. That speed is useful, but it creates a new failure mode: the code compiles, the unit tests pass, and the UI is wrong.
The button moved under a modal. A pricing card overflows on mobile. A loading state covers the main action. A generated component uses the wrong tenant data. The pull request looks fine in text, but the product feels broken.
That is where visual QA agents are becoming practical. Instead of treating QA as a manual pass at the end, you give an agent a scoped test mission: open the app, perform real user journeys, capture evidence, compare against baselines, and report what changed.
This guide shows how to build that workflow without turning it into a flaky science project.
