A comprehensive guide to design system engineering (DSE): when it’s relevant, how AI changes things, and pointers for getting started. From Michael Abernethy, Principal Frontend Engineer at Rubrik

The majority of AI products remain tethered to a single, monolithic UI pattern: the chat box. While conversational interfaces are effective for exploration and managing ambiguity, they frequently become suboptimal when applied to structured professional workflows.

Atomic design systems have emerged as a methodology for creating scalable and maintainable user interfaces. This comprehensive guide explores what atomic design is, examines whether atomic design is still relevant in 2025, and reveals how atomic design principles can be adapted beyond their original chemistry metaphor. Drawing from a decade of industry experience and direct insights from Brad Frost himself, this article provides practical guidance for implementing modern design systems…

Atomic Design is one of the most frequently mentioned patterns when talking about frontend architecture.

Traditionally we’ve shied away from building because the chasm to go from designing to shipping requires learning to code, test, and bug fix. All of it required massive time investment to learn syntax, that changes every few years while core principles stay the same. Most of us are designers because we’re visual thinkers in a way.

These details aren’t accidents. They’re decisions. Careful, intentional decisions made by people who care deeply about craft.

As a design engineer, a role that’s all about craft, thoughtfulness and creativity, I should be skeptical of AI. By definition AI is not particularly great at those things, at least for now. But despite that, I kinda enjoy using it?

All of us are fighting a war on three fronts (thanks to AI). Customer product expectations are higher than ever. Distribution channels are collapsing. And everyone – big incumbents, new startups, even your own customers with vibecoding – are coming for your value prop.

UX faced instability from layoffs, hiring freezes, and AI hype; now, the field is stabilizing, but differentiation and business impact are vital.

Summary: Accelerating AI capabilities will shift focus from raw intelligence to autonomous agents and Generative UI, making UX the primary business moat. Multimodal integration and physical AI will revolutionize workflows, rendering static interfaces and single-purpose tools obsolete. However, progress faces hurdles like compute shortages and a widening class divide between premium and free-tier users.