Torii Studio

AI generates your components. They work. But they break reusability principles. We've been reviewing AI-assisted frontend codebases and the pattern is consistent: 1. The component renders. 2. The tests pass. 3. The PR gets approved and merged into production. But underneath: - SRP gets violated - props get hardcoded - APIs are built for one case, not ten - the same component gets rewritten three times across the codebase None of it fails immediately. It just drifts until the codebase is full of components nobody wants to touch. We wrote about how to keep reusability principles intact when AI is doing the generating. Including how to encode them as guardrails and validate in isolation with Storybook. ➡️ https://lnkd.in/ewgH9PYP

90% test coverage sounds like a win. It's actually a trap. Not because your team did something wrong. Because the metric rewards the wrong thing. Coverage counts whether code was executed during a test. It doesn't count whether that test would catch a real bug. Those are two very different things. A test that renders a component and confirms it exists? That adds coverage. A test that simulates a user toggling annual billing and checks that the price actually changes? That also adds coverage. Same metric. Completely different protection. AI makes this gap wider. It's extremely good at generating the first kind. They pass on the first try, they're fast to produce, and they make your dashboard look healthy. Six months later, something breaks in production… and no test catches it. The fix isn't writing more tests. It's changing what you count. Teams that separate "existence tests" from "behavioral tests" and only track the second kind start catching regressions their coverage numbers told them didn't exist. The problem was never your engineers.  It was the illusion of safety. What metric does your team actually trust?

AI-generated code passes every check. It still breaks your system. We've been reviewing AI-assisted frontend PRs across production codebases. The pattern is consistent: The UI renders. The tests go green. The build doesn't fail. But underneath: - spacing tokens drift - components get duplicated - tests protect nothing - architecture loses coherence None of it fails catastrophically. It just compounds — quietly, over months. This is what we call the illusion of correctness. And it's one of the most expensive problems teams are walking into right now. We wrote about the three patterns behind it, and what to do about each one. ➡️ https://lnkd.in/egnn2YmF

Design consistency and engineering confidence don’t happen by accident 👉 they happen by process. We just published a new article showing how we use Storybook + automated testing to help teams: • Catch UI bugs before they hit production • Build reliable component libraries • Shorten delivery cycles • Maintain design integrity at scale From behavior tests and MSW mocks to CI/CD integration, this guide covers the full workflow our team applies across fast-moving startups and enterprise systems alike. If you care about quality, speed, and scalable front-end engineering, you’ll find it useful. 👇 Full article below: https://lnkd.in/g9iujFAH

Consistent design systems build confidence. Learn how to automate UI testing for React using tools like Chromatic, Percy, and Applitools — plus how to integrate it in CI/CD. Read more 👇 https://lnkd.in/dA-72Ruu