Experimental UI as an Engineering Discipline

Experimental UI, custom layouts, generative art, spatial navigation, is often dismissed as eye candy or “designer code.” When it’s done as engineering, it becomes repeatable, maintainable, and fast. This post is about how to do it that way.

Constraints as creativity

The best experimental UI works within constraints: a performance budget, accessibility requirements, and a clear contract with the rest of the app. Constraints force choices. “We have 50 KB for this interaction” leads to smarter techniques than “we’ll optimize later.” Treat the budget and a11y as part of the brief, not an afterthought.

Technique over trend

Trends (e.g. glassmorphism, parallax everywhere) age badly. Technique, how you use transform and opacity, how you structure your animation loop, how you lazy-load and dispose, lasts. Invest in understanding the platform: compositor, requestAnimationFrame, IntersectionObserver, and the visibility API. That knowledge transfers to every project.

Measurable outcomes

Experimental UI should still have success criteria: Lighthouse score, CLS, time to interactive, and keyboard/screen-reader usability. If the experience is beautiful but fails accessibility or performance, it’s incomplete. Define “done” up front and measure.

Reusability and abstraction

Even one-off experiences benefit from abstraction: a small motion library, a shared pattern for “reveal on scroll,” or a consistent way to pause animations when the tab is hidden. That reduces bugs and makes the next experiment faster. Experimental UI as engineering means building a toolkit, not only a single page.

Summary

Experimental UI as engineering means: constraints as part of the brief, technique over trend, measurable outcomes (performance and a11y), and reusable patterns. When you treat it that way, the result is both expressive and robust.