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We Rebuilt Next.js in a Week with AI—vinext Delivers 4x Faster Builds

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How We Rebuilt Next.js with AI in One Week: The vinext Story

The Core Question: In an era of rapidly advancing AI, is it possible to reconstruct a massive frontend framework like Next.js from scratch in just a few days? The answer is a resounding yes. By leveraging a strict test suite, clear architectural planning, and state-of-the-art AI models, a single engineer built vinext in under a week—a Vite-based, high-performance alternative to Next.js.

Last week, one engineer and an AI model rebuilt the most popular front-end framework from scratch. The result is vinext (pronounced “vee-next”), a drop-in replacement for Next.js. It is built on Vite and deploys to Cloudflare Workers with a single command. In early benchmarks, it builds production apps up to 4x faster and produces client bundles up to 57% smaller. The entire project cost about $1,100 in tokens.


Image Credit: Cloudflare Blog

The Next.js Deployment Dilemma: Why Rebuild the Wheel?

The Core Question: If Next.js is already the industry standard, why go through the trouble of rebuilding it?

Next.js is undeniably the most popular React framework, powering millions of websites and offering a top-tier developer experience. However, it faces a significant challenge when deployed within the broader Serverless ecosystem: its tooling is entirely bespoke.

Next.js has invested heavily in Turbopack. While powerful, deploying it to platforms like Cloudflare, Netlify, or AWS Lambda requires reshaping the build output to fit the target environment. This is the problem OpenNext was designed to solve. Despite significant engineering effort from multiple providers, OpenNext often becomes a game of “whack-a-mole.” Because it relies on reverse-engineering Next.js build outputs, unpredictable changes between versions can cause breaking issues, making it a fragile foundation.

Personal Reflection:
This highlights a fundamental truth about software infrastructure: adaptation layers built on top of “black box” outputs are inherently fragile. No matter how good the adapter is, if the underlying logic shifts without warning, maintenance becomes a never-ending battle. Instead of constantly patching the output, it is often more efficient to rethink the implementation from the ground up.

Even with Next.js developing a first-class adapters API, developers are still locked into the Turbopack toolchain. Furthermore, during development, next dev runs exclusively in Node.js. If your application relies on platform-specific APIs—like Durable Objects, KV namespaces, or AI bindings—you cannot test them in a standard dev environment without cumbersome workarounds. This disconnect between development and production environments hinders productivity and introduces risk.

Introducing vinext: A New Implementation on Vite

The Core Question: What if, instead of adapting Next.js output, we reimplemented its API surface directly on Vite?

vinext is not a wrapper around Next.js or Turbopack. It is a clean reimplementation. It implements the Next.js API surface—routing, server rendering, React Server Components (RSC), server actions, caching, and middleware—entirely as a Vite plugin. Vite is the build tool of choice for the majority of the frontend ecosystem, powering frameworks like Astro, SvelteKit, Nuxt, and Remix.


Image Credit: Cloudflare Blog

By utilizing the Vite Environment API, vinext output runs natively on any platform. For developers, the migration barrier is exceptionally low.

npm install vinext

Simply replace next with vinext in your scripts. Your existing app/, pages/, and next.config.js files work as-is.

Operational Commands:

vinext dev          # Start dev server with HMR
vinext build        # Production build
vinext deploy       # Build and deploy to Cloudflare Workers

Application Scenario:
Imagine you are building an e-commerce platform that uses Cloudflare Durable Objects to manage real-time shopping cart states. In a traditional Next.js setup, you would need complex configurations like getPlatformProxy to simulate the environment locally. With vinext, the entire application (including the dev server) runs inside workerd. This allows you to use Durable Objects and AI bindings directly during development, with no compromises or extra configuration needed.

Performance Benchmarks: A Leap in Speed and Size

The Core Question: How much improvement does vinext actually offer in terms of build speed and bundle size?

Early benchmark results are striking. We compared vinext against Next.js 16 using a shared 33-route App Router application. To ensure a fair comparison measuring bundler and compilation speed (rather than type-checking or static generation), we disabled TypeScript and ESLint checks in the Next.js build and used force-dynamic.

Production Build Time

Framework Mean Time vs Next.js
Next.js 16.1.6 (Turbopack) 7.38s Baseline
vinext (Vite 7 / Rollup) 4.64s 1.6x faster
vinext (Vite 8 / Rolldown) 1.67s 4.4x faster

Client Bundle Size (Gzipped)

Framework Gzipped Size vs Next.js
Next.js 16.1.6 168.9 KB Baseline
vinext (Rollup) 74.0 KB 56% smaller
vinext (Rolldown) 72.9 KB 57% smaller

Technical Deep Dive:
Vite’s architecture, particularly the upcoming Rolldown bundler (Rust-based) in Vite 8, offers structural advantages in build performance. While these figures stem from a specific test fixture, the trend is clear: vinext significantly reduces build wait times and minimizes the JavaScript payload users must download, leading to faster page loads and better Core Web Vitals.


Image Credit: Unsplash

Deploying to Cloudflare Workers: Native Cloud Experience

The Core Question: How does vinext achieve a seamless transition from code to production?

vinext treats Cloudflare Workers as a first-class deployment target. A single command takes you from source code to a running Worker:

vinext deploy

This command handles the entire pipeline: building the application, auto-generating the Worker configuration, and deploying. Both App Router and Pages Router work out-of-the-box on Workers, supporting full client-side hydration, interactive components, client-side navigation, and React state management.

Configuring Caching Strategies

For production caching, vinext includes a Cloudflare KV cache handler that supports Incremental Static Regeneration (ISR) by default:

import { KVCacheHandler } from "vinext/cloudflare";
import { setCacheHandler } from "next/cache";

// Bind the KV namespace to the cache handler
setCacheHandler(new KVCacheHandler(env.MY_KV_NAMESPACE));

Configuration Flexibility:
While KV is an excellent default for most applications, the caching layer is designed to be pluggable. You can easily swap in R2 storage, which is better suited for applications with large cached payloads or specific access patterns. This flexibility ensures developers can choose the caching strategy that best fits their application’s needs.

Traffic-aware Pre-Rendering: Solving the Build Bottleneck

The Core Question: Large websites often suffer from linear build times that scale with page count. How does vinext solve this?

In traditional Next.js, a site with 10,000 product pages using generateStaticParams() requires 10,000 renders at build time. Even if 99% of those pages rarely receive traffic, the build time scales linearly, often resulting in 30-minute builds or longer.

vinext introduces Traffic-aware Pre-Rendering (TPR) to solve this bottleneck. This experimental feature uses actual traffic data to guide the build process.

How TPR Works

Cloudflare acts as a reverse proxy, possessing precise traffic data for your zone. TPR queries Cloudflare’s zone analytics at deploy time to pre-render only the pages that actually receive visits.

Operational Example:

vinext deploy --experimental-tpr

Console Output Simulation:

Building...
Build complete (4.2s)

TPR (experimental): Analyzing traffic for my-store.com (last 24h)
TPR: 12,847 unique paths — 184 pages cover 90% of traffic
TPR: Pre-rendering 184 pages...
TPR: Pre-rendered 184 pages in 8.3s → KV cache

Deploying to Cloudflare Workers...

Scenario Analysis:
For an e-commerce site with 100,000 product pages, the power law dictates that 90% of traffic usually goes to 50 to 200 pages. TPR pre-renders these high-traffic pages in seconds. The remaining pages fall back to on-demand SSR and are cached via ISR after the first request. This strategy eliminates the need for generateStaticParams() and decouples your build time from your production database, significantly optimizing CI/CD pipelines.

Inside the Process: How AI Wrote a Framework

The Core Question: How can a single engineer and an AI model complete such a massive engineering feat in just one week?

This project serves as a prime example of “AI-native” development. The first commit landed on February 13. By that evening, basic SSR for both Pages and App Routers, along with middleware and server actions, was functional. By the next afternoon, the App Router Playground was rendering most routes. By day three, vinext deploy was shipping apps to Cloudflare Workers. The rest of the week focused on hardening and testing.

Total Cost: Approximately $1,100 in API token fees.

The Four Pillars of Success

The success of this project relied on four critical factors aligning perfectly:

  1. Well-Specified Documentation: Next.js has extensive documentation and a massive community presence. Its API surface is deeply embedded in the training data of modern Large Language Models (LLMs). When asked to implement getServerSideProps, the model doesn’t hallucinate; it knows the spec.
  2. Comprehensive Test Suites: The Next.js repository contains thousands of E2E tests. vinext ported these tests directly, providing a mechanical specification that the AI could verify against.
  3. Solid Foundation: Vite handles the heavy lifting of HMR, ESM, and plugin APIs. We didn’t need to build a bundler; we just needed to teach Vite to “speak” Next.js.
  4. Model Evolution: Recent advancements in AI models allow them to maintain coherence over large codebases, reasoning about module interactions rather than just generating isolated snippets.

The “Human-in-the-Loop” Workflow

While AI wrote almost every line of code, quality gates were not skipped. The project established strict guardrails: 1,700+ Vitest unit tests, 380 Playwright E2E tests, and full TypeScript checking.

The Development Cycle:

  1. Define Task: e.g., “Implement the next/navigation shim including usePathname.”
  2. AI Implementation: The AI writes the code and accompanying tests.
  3. Verification: Run the test suite.
  4. Iteration: If tests fail, feed the error logs back to the AI for correction.
  5. Review: AI agents handled initial PR reviews, while the human engineer focused on architecture and correcting dead-end logic.

Personal Reflection:
This experience shifts the paradigm of software engineering. AI didn’t replace the engineer; it elevated their role. The engineer transformed from a “bricklayer” writing boilerplate to an “architect” and “supervisor.” When provided with direction, context, and guardrails, AI becomes a productivity multiplier. However, the human element remains essential for steering the project, spotting logical fallacies, and making judgment calls that models cannot yet handle.

Rethinking Software Abstraction Layers

The Core Question: What does this project teach us about the future of software architecture?

The proliferation of abstraction layers in software is largely a concession to human cognitive limits. We cannot hold an entire complex system in our heads, so we build frameworks and glue code to manage the complexity. Each layer exists to make the next level of abstraction manageable for a human developer.

AI changes this equation. It can hold the entire system context and write the necessary code without needing an intermediate framework to stay organized. It requires only a specification and a foundation. vinext proves that by providing an API contract and a build tool, AI can bridge the gap without the bloat of intermediate layers.

This signals a potential shift in how we build software. As AI capabilities grow, the abstraction layers designed solely to aid human comprehension may dissolve, leading to leaner, more efficient software stacks.

Status and Practical Guide

The Core Question: Is vinext ready for production, and how can developers start using it?

vinext is currently in an experimental phase. It is less than a week old and has not yet been battle-tested with massive production traffic. However, it boasts an extensive test suite covering 94% of the Next.js 16 API surface. Early adopters, such as National Design Studio with their CIO.gov project, are already seeing benefits in build times and bundle sizes.

Quick Migration Guide

vinext provides an Agent Skill to automate the migration process. It works with tools like Claude Code, Cursor, and Codex.

Automated Migration Steps:

  1. Install the skill package: 
    npx skills add cloudflare/vinext
  2. Open your project in your AI coding tool and enter: 
    migrate this project to vinext

    The skill handles compatibility checks, dependency installation, and configuration generation.

Manual Migration Steps:

npx vinext init    # Initialize and migrate an existing Next.js project
npx vinext dev     # Start the development server
npx vinext deploy  # Deploy to Cloudflare Workers

The source code is open-sourced, and contributions are welcome.

Practical Summary & Checklist

Key Takeaways:

  • Origin: vinext is a Vite-based alternative to Next.js designed to solve Serverless deployment friction.
  • Performance: It builds up to 4.4x faster and produces bundles up to 57% smaller than Next.js.
  • Innovation: Traffic-aware Pre-Rendering (TPR) uses real-world analytics to optimize build strategies, drastically reducing build times for large sites.
  • AI Engineering: The project demonstrates that with clear specs and guardrails, AI can reconstruct complex frameworks rapidly and cost-effectively.
  • Availability: Currently experimental, it offers an automated migration path for most Next.js APIs.

Developer Action Plan:

  1. Evaluate Fit: If your project relies heavily on static pre-rendering without dynamic data, consider waiting or exploring alternatives like Astro.
  2. Try Migration: For SSR/ISR applications, run npx skills add cloudflare/vinext in a test branch to assess compatibility.
  3. Verify Features: Specifically test React Server Components, Server Actions, and platform-specific bindings (e.g., KV, Durable Objects).
  4. Report Issues: Submit any compatibility bugs to the GitHub repository to help improve the ecosystem.

One-Page Summary

Aspect Details
Project Name vinext (“vee-next”)
Core Tech Vite, React Server Components, Rolldown
Competitor Next.js (Turbopack)
Build Performance 1.67s (vinext) vs 7.38s (Next.js)
Bundle Size 72.9 KB (vinext) vs 168.9 KB (Next.js)
Deployment Cloudflare Workers (Primary), other Vite-compatible platforms
Dev Cost ~$1,100 (AI Token cost)
Timeline ~1 Week (1 Engineer + AI)
API Coverage 94% Next.js 16 API
Status Experimental, Open Source

Frequently Asked Questions (FAQ)

1. Is vinext fully compatible with Next.js?
vinext currently covers 94% of the Next.js 16 API surface, supporting both App Router and Pages Router. Most existing app/, pages/, and next.config.js configurations work immediately, though developers should review the documentation for unsupported features.

2. Does vinext support Static Site Generation (SSG)?
vinext currently prioritizes ISR (Incremental Static Regeneration). It does not yet support full static pre-rendering at build time for all pages. For purely static content sites, users might consider Astro or wait for future updates.

3. What is Traffic-aware Pre-Rendering (TPR)?
TPR is an experimental feature that analyzes real visitor traffic at deploy time. It pre-renders only the most visited pages rather than every possible page, significantly reducing build times for large websites.

4. Must I deploy to Cloudflare Workers?
While Cloudflare Workers is the primary target, vinext is built on Vite, making about 95% of the code platform-agnostic. Cloudflare is actively collaborating with other hosting providers to expand support.

5. Is the quality of an AI-built framework reliable?
Yes. While AI generated the code, every line passes through the same quality gates as human-written code: over 1,700 unit tests, 380 E2E tests, and strict TypeScript checks.

6. Is vinext ready for production use?
It is currently labeled “experimental.” While sites like CIO.gov are already using it, developers should proceed with caution and conduct thorough testing before deploying to critical production environments.

7. How do I get started with vinext?
The easiest method is to run npx skills add cloudflare/vinext in your project root and use an AI coding assistant to handle the migration. Alternatively, run npx vinext init manually.

8. Why is vinext faster than Next.js?
vinext leverages Vite and the upcoming Rolldown bundler (written in Rust), which offer structural performance advantages. It also avoids the overhead of Next.js’s bespoke toolchain, streamlining the compilation process.

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