When building YouClip (an AI video clipper), I had heavy Python scripts for FFmpeg and AI analysis running in Docker containers.

The traditional way to connect them to my Next.js frontend would be writing a complex message queue system (using Redis/Celery/BullMQ).

The Problem

Writing queue logic is boring. Debugging stuck jobs involves digging through obscure terminal logs. You can’t "see" where the process failed easily.

The Solution: N8N as a "Control Plane"

I didn’t replace the heavy code—the video processing still happens in optimized Python scripts. But I replaced the "Glue Code" (retries, state management, error handling) with self-hosted N8N workflows.

Why this architecture wins:

  1. Visual Debugging: I can see exactly which step a vid…

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