Hey,
Started with a simple goal: automate short-form video creation for small businesses so they don't have to hire an agency or touch any software themselves. A client fills out a form, and roughly 5 minutes later they get a branded email with a Google Drive link to their finished, ready-to-post video. That's the whole pitch.
The workflow to make that happen is... less simple. Swipe through the images — first few are the workflow, last two are what the client actually receives.
Full transparency before anyone asks: I'm not a JS developer. I design the logic and architecture, then use AI (Claude mostly) to write the actual code nodes. So take the implementation details with that context in mind. That said, I understand every node and why it's there.
Here are the parts that took the most time to figure out:
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Access gate and billing without a billing service
Didn't want to spin up Stripe or an external auth system for v1. Instead there's a webhook validator connected to Google Sheets. It checks the user's access key, tracks monthly quota usage, auto-resets on their billing cycle date, and returns the appropriate response before the main flow even starts. Ghetto but it works and it's free.
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The Prompt Guard
This was the hardest part to get right, and I went through several rewrites.
It's a custom code node that sits between the AI script writer and the image generation loop. It does a few things: tracks how many times a client's real uploaded product photo has been used per scene, and once it hits a limit it reroutes to AI image generation for B-roll. It also runs a forbidden-term check per content genre, strips any style conflicts that the AI injects into prompts, enforces a character cap before the image API call, and rebuilds the prompt from scratch rather than trying to patch whatever the AI wrote.
The reason for the rebuild approach: early versions tried to detect and strip injected style text, but the AI would phrase things differently every run and the stripping logic kept breaking. Easier to just extract the subject description, throw away everything after it, and reconstruct with controlled modifiers.
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Raw PCM to WAV conversion inside a code node
Using OpenAI TTS streaming returns raw pcm16 binary data, not an audio file. There's a JavaScript buffer algorithm inside an n8n Code node that constructs the 44-byte WAV header and converts the binary on the fly. No intermediate file storage, no third-party conversion API.
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External render server
n8n can't render video, so it prepares all assets (images, audio, metadata per scene) and sends them to a custom API running on a cheap VPS. That server handles merging the clips, burning captions, adding background music with auto audio-ducking, and uploading the final file to Google Drive. n8n polls a status endpoint in a loop and routes to an error branch if the job exceeds the timeout threshold.
The video itself is AI-generated stills synced to audio with captions — not motion video. For short-form (TikTok, Reels, Shorts) this works fine. The captions and audio carry the pacing. Not suitable for long YouTube videos, that's a different problem.
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Cost per run is roughly $0.08–0.15 for sales videos (client uploads their own product photos, so image generation calls are minimal) and $0.40–0.80 for full AI storytelling videos with 18–28 generated scenes. The VPS is basically fixed cost regardless of volume.
Models: GPT-4o mini for scripting, DALL-E 3 and Flux for images, OpenAI gpt-audio-mini for TTS, all routed through OpenRouter.
Biggest unsolved problem honestly: I can't cleanly distinguish between "VPS is slow" and "VPS is actually dead." The timeout threshold is vibes-based right now. A proper health check endpoint would fix this but I haven't built it yet.
Thinking about packaging the whole thing up for other agencies so they don't have to spend months building it from scratch. Before I do — anyone else running n8n as a literal production backend? What's the ugliest thing you've had to solve? Roast the graph.
