Short Film · Oct 6, 2026
I directed an 8-minute short film where AI did the script, footage sourcing, edit, VFX and sound mix. Here's the pipeline and what I learned
I directed an 8-minute short film where AI did the… by smith2008. Watch the Short Film video, explore the shared prompt and visit the original Reddit post.
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Pipeline • Script and research: Claude (running in Claude Code) wrote all the narration and checked every figure against a source (NASA, Lawrence Livermore, TOP500). • Footage: it found and downloaded real public-domain and Creative Commons footage (NASA, DVIDS, USGS, Wikimedia Commons, Mixkit) and logged the source and license of every clip. • Edit and VFX: the edit is Python code. A GPU compositor written in PyTorch does the color grading, masks, mirror effects, typography and a face-tracking HUD (OpenCV face detection). ffmpeg does the encoding. • Sound: ElevenLabs voices, music and sound effects via fal. Every narration take was checked word for word with speech-to-text before it went in. The score was composed from section plans timed to the cuts, then mixed and mastered to -14 LUFS. • Me: direction, taste, and the final call on what stays. What I learned • The hardest part wasn't generation, it was rights. Every clip needed its source and license tracked so the credits…
The prompt behind it.
Original prompt
: voice direction tags, ducking under narration and a mastered mix make a bigger difference than any single visual effect. • I also rendered a second version with all the stock footage replaced by AI video generated locally (MiniMax H3 on an RTX 4090, 123 clips, about 2 hours of GPU time). It looked good, but the real footage won.
Video and prompt by smith2008. Original post ↗


