An 8-chapter manual, n8n workflow, production scripts, and a meta-system for adapting it to your own channel with AI as your collaborator — not your author.
For operators who want to run and adapt a documented AI pipeline — not a one-click product.Every chapter, every script, every prompt was refined against actual daily uploads — not whiteboard examples. The numbers below describe what was built and what it costs to run.
A reference build you can run as-is, the manual that explains every decision, and the meta-method for adapting it to your channel.
process_job.sh (FFmpeg composition), watcher.sh (inotify watcher), and youtube_upload.py (Python uploader). Ready to deploy.A few excerpts before you decide. The full chapters, scripts, and assets are included after purchase.
This is an automated YouTube Shorts production pipeline. Once configured, it generates and uploads one Short per day to your channel with minimal day-to-day intervention.
Daily flow: a unique topic is selected from a 100-topic rotation pool with anti-repetition logic. GPT-4o writes the script and on-screen text. An OpenAI image model generates 5 textured editorial illustrations, and OpenAI TTS produces a narration clip per card. FFmpeg composes an 18–22 second vertical video, with each card's duration driven by its narration audio. The result is uploaded to YouTube with title, description, and tags.
You set it up once. After that, the workflow runs on its own schedule, requiring only occasional check-ins.
Chapters 1–7 get the reference build running. This chapter helps you turn that working reference build into a channel that feels like your own.
The reference build is a case study. Every piece of it — the visual tone string in Chapter 3, the FFmpeg color values in Chapter 4, the prompt-category weighting in the GPT-4o call — represents one set of decisions that worked for one channel.
The point of this chapter is to give you a working method for replacing those decisions with your own, using AI tools (ChatGPT, Claude, or whichever you prefer) as collaborators rather than authors.
Frames from a Short generated by the same reference pipeline, with upload disabled for the anonymous demo. Same generation workflow, same scripts, same FFmpeg composition — 1080×1920 vertical, 18–22s, each card's duration driven by its narration audio.
Most automation packages give you a template to copy. This one gives you a working example — and a method for rebuilding it for your own channel with AI as your collaborator. Chapter 8 is where that method lives.
One scheduled trigger per day. AI generates the script and illustrations. The host composes the video. The Python uploader pushes it to YouTube. You check the log once a day if you want to.
The package is best for a specific kind of person. Reading both columns before buying saves everyone a refund conversation.
No subscription. No upsells. The Founding price is a thank-you for being early — it reflects the package as it exists today, before any future additions. Founding pricing applies for the first 30 days after public launch; the current Founding window is shown at checkout. After that, the package moves to its Regular price of $499.
One-time. Lifetime download access. 6 months of compatibility updates.
After purchase: instant download of all files. Support is best-effort by email — no SLA. The package is a reference implementation, not a managed service. No performance guarantees — the system is what you receive, your channel's success is your work.
Click any question to expand.
5 weeks of daily production. 8 chapters. Documented incidents. Meta-system for adaptation with AI. One-time purchase, lifetime access.
Checkout opens soon. Questions: support@caseandmethod.com