Length alone is not continuity. Long-form AI video needs a timeline, persistent state and a method for directing what survives from one generated interval into the next.
IAMCCS long-video workflows are designed around authored sequences rather than isolated clips.
A final frame can preserve appearance, but it cannot by itself describe every moving state that matters across a cut or continuation: camera velocity, gesture phase, fabric motion, environmental movement, sound tails and the temporal pressure of the previous shot.
The practical solution is to carry more of the production state through the timeline: shot planning, positioned guide images, local prompts, overlap or latent context where the model supports it, audio continuity and an explicit editorial handoff.
Global direction, interval-level prompts, media placement, timing and audiovisual continuity organised before sampling.
Frame validation, first/last-frame control, overlap conditioning, continuation and disk-backed long-video operations.
Motion control and reliable LoRA routing for longer generative chains where state and phase changes need explicit management.
The Shotboard acts as the authored source of truth. A model branch generates the current interval; continuity-aware paths preserve the state that matters; audio and editorial tools return the result to a usable timeline.