Building a Video-to-Prompt Pipeline: Lessons from TubePrompter

Building a Video-to-Prompt Pipeline: Lessons from TubePrompter Building a system that takes a video URL and returns usable prompts for AI generators sounds straightforward until you actually try it. Over the past several months, we built TubePrompter — a free tool that converts YouTube, TikTok, and Instagram videos into prompts for Sora, Midjourney, Runway, and other AI video generators. This article covers the architectural decisions we made, the problems we didn't expect, and what we'd do differently. Architecture Overview The system has four main layers: Client (Next.js 16) └── API Routes └── Video Ingestion Service └── Analysis Pipeline └── Prompt Generation Engine Each layer handles a distinct concern, and the boundaries between them matter more than you'd think. Why Next.js 16 for a Video Analysis Tool? This seems counterintuitive — why use a React meta-framework for something that's primarily a backend processing task? The answer is developer velocity. Next.js App Router with Se