React and Remix Choose Different Futures

October 27, 2025

Split image artwork with Hokusai’s traditional woodblock wave on the left transforming into a pixelated and then digital-style wave on the right, featuring vivid colors and grid lines; text at the bottom reads “THE · WAVE · OF · THE · FUTURE.”

I attended Remix Jam two weeks ago, then spent this past week watching React Conf 2025 videos. I have spent the last decade shipping production code on React and the last two years on Remix.Now both ecosystems are shifting, and what seemed like different approaches has become incompatible visions.

React Conf’s technical announcements were incremental: React 19.2 APIs, View Transitions experiments, the compiler getting more sophisticated. The message was clear: React is listening to the community while accepting complexity on your behalf. Stability, Composability, Capability: those are the values.The Remix team announced something else entirely: they’re breaking with React. The mental model shifts introduced by use client and the implementation complexity of Server Components forced a choice. And Remix 3 chose Simplicity. Remix 2 users pay the price; there’s no upgrade path.

That choice, to sacrifice Stability for Simplicity, makes explicit what was already true: these values cannot coexist.

Source: React and Remix Choose Different Futures

A really interesting reflection on where React and Remix are headed as they diverge, and how the values embedded in each are quite distinct.

I feel we’re at a time of real disruption when it comes to how we architect for the web—something I’ve been saying for the last year or so. React and Remix are diverging around this, but we also need to consider the impact of large language models on how we architect for the web.

If, as I think is extremely likely, we increasingly rely on LLMs to do a lot of the heavy lifting when it comes to writing code, the key question becomes: what kind of code works best with those models?
Some people argue that React does, because there’s so much training data—so much React code on the web that models will have learned from. But as one interviewee on the AI-Native Dev podcast a little while ago observed, a lot of that is just pretty average React code. And how much is enough? We don’t actually know.

When I work with LLMs on web technologies and ask them to generate web content and applications with functionality using “vanilla” JavaScript, CSS, and HTML, they do a very good job. They’re very steerable. I think they know enough, quite honestly. The web platform fundamentals are very well documented, and that documentation is probably very high quality, which helps.

Anyway, it’s a complex and challenging time. Pieces like this are valuable in helping us think through and reason about where we go from here.