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#ThisWeekinNET — Episode 121 In this episode of This Week in NET, host João Tomé is joined by Steve Faulkner, Engineering Director at Cloudflare, to discuss how he rebuilt a Next.js-compatible framework in just one week using AI. The project, called vinext, began as an experiment and evolved into a working proof of concept. We explore what AI-first development looks like in practice, how coding agents were used to rewrite and test large API surfaces, and what happens when you treat dependencies as something you can regenerate rather than maintain manually. The results were surprising: faster local builds, smaller bundles, deployment to Workers with a single command, and a total AI token cost of roughly $1,100. We also discuss: • Using voice-to-code workflows (SuperWhisper + local models) • AI reviewing code multiple times • Traffic-aware pre-generation (TPR) • Whether AI-assisted rebuilds will become common • What this means for 2026 and beyond Check the Cloudflare Blog: http://blog.cloudflare.com 🎧 Subscribe to the podcast for weekly conversations about the Internet and Cloudflare: https://ThisWeekinNET.com/ ⏱️ Timestamps 0:12 — Introduction: the latest on the Cloudflare blog (monitoring post-quantum encryption and ASPA routing; JavaScript Streams — why we deserve a better API) 3:22 — Steve’s role and Workers platform overview 4:34 — How the idea came to be 6:11 — When AI tools became “good enough” 7:13 — Tooling setup: OpenCode, Claude, parallel agents 9:03 — AI beyond coding: management and markdown workflows 10:58 — What AI-first development actually means 12:03 — Performance gains: 4x faster builds, 57% smaller bundles 14:11 — ~$1100 in tokens: the real cost 15:35 — Deploying to Workers with one command 17:25 — Community feedback and early adoption 19:09 — Will AI rebuild other frameworks? 20:25 — Voice-to-code workflows (SuperWhisper, Parakeet) 23:31 — Traffic-Aware Pre-Generation (TPR) explained 25:23 — Production caution and security 26:19 — How to get started (use AI to migrate your app) 27:12 — The big takeaway: AI is changing how we build software