"⚛️ Tanner Linsley Built a React Clone in One Day — Here's Why It Matters"

Last week, Tanner Linsley — creator of TanStack Query, Table, Router, and half the libraries keeping modern React apps alive — did something that turned heads in the frontend community. He spent a day prompting an AI agent to regenerate React's public API as a ~9KB runtime, quietly shipped it on his blog and tanstack.com, and just moved on.

The result? A React-compatible runtime that runs 2–3× faster than stock React, scoped specifically to TanStack Start.

Let me unpack why this matters — not just as a neat demo, but as a signal about where frontend is heading.

What Actually Happened

Tanner took the public React API surface — useState, useEffect, createContext, createElement, the whole works — and had an AI agent reimplement it from scratch. The output is a ~9KB runtime that's API-compatible with React but optimized for TanStack Start's specific needs.

// This works exactly like you'd expect — just faster
import { useState, useEffect } from '@tanstack/react-like'

function Counter() {
  const [count, setCount] = useState(0)
  
  useEffect(() => {
    document.title = `Count: ${count}`
  }, [count])
  
  return <button onClick={() => setCount(c => c + 1)}>{count}</button>
}

The key insight: by shedding backwards compatibility with legacy React patterns and optimizing for a specific router/framework context, you can drop significant runtime overhead.

Why 2–3× Faster?

Stock React carries decades of design decisions. The reconciler, the event system, the fiber architecture — all built for maximum flexibility across every possible use case. That's the right call for a general-purpose library. But if you're building a framework with known constraints (like TanStack Start's file-based routing and streaming SSR), you can make aggressive optimizations:

• Simplified reconciliation: If you know the component tree shape at build time, you can skip runtime work
• Smaller bundle: 9KB gzipped vs React's ~42KB means less parsing and less memory
• Specialized scheduling: No need for concurrent mode's complexity when your routing guarantees certain patterns

The Bigger Picture: AI-Generated Framework Internals

The most provocative part of this story isn't the performance numbers — it's how it was built. An AI agent generated this in a single day. That's a capability we haven't fully processed yet.

Think about what this unlocks:

• Framework experimentation becomes cheap: Want to try a different reconciliation algorithm? Describe it, let the AI build it, benchmark, iterate.
• Domain-specific runtimes: E-commerce sites don't need the same React features as data dashboards. Custom runtimes tailored to your workload become feasible.
• Teaching tools: A stripped-down React clone is the best way to understand how React works internally. This could be an incredible educational resource.

Should You Use It?

Probably not in production — at least not yet. Tanner himself isn't properly releasing it (though it's on npm if you're curious). It's an experiment, a proof of concept, and a glimpse of what's coming.

But the pattern is worth paying attention to. We're entering an era where:

1. Framework internals become a commodity (AI can generate them)
2. Performance optimization moves from "general case" to "specific use case"
3. The boundary between framework author and framework consumer blurs

The Bottom Line

Tanner's React clone isn't a replacement for React. It's a harbinger. When a framework's public API can be reimplemented in a day by an AI and run 2–3× faster, it tells us that React's value has shifted from its implementation to its ecosystem, conventions, and developer experience.

The next time someone tells you a piece of infrastructure is "too complex to rebuild," remember: someone just rebuilt React in a day.