I’ve spent the last few weeks building a documentary video generation pipeline. A topic goes in (say: “Sankebetsu brown bear incident 1915 Hokkaido”) and a finished mp4 comes out (a ten-minute narrated documentary, 27 scenes, original visuals, voiced by a documentary-grade TTS), all running on a homelab cluster.

Between those two endpoints sits a chain of eight passes that hand off to each other. Several fan out to “do N things in parallel and aggregate.” Several produce artifacts measured in MB per scene that should not be shoved through a message broker. A few are the right place to put a human in the loop, where one minute of editorial review saves hours of GPU time downstream.