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AI video generation pushes toward entire, consistent, multi‑shot narratives by sustaining characters, environments, and story beats across scenes. Maintaining identity, camera continuity, and temporal coherence strains current diffusion and transformer pipelines, conditioning methods, and memory strategies. Prompts, shot lists, and storyboard controls guide transitions, while editing and post‑processing bridge gaps between clips. Metrics for narrative faithfulness, object permanence, and dialogue alignment remain unsettled as sequence length and compute demands rise. Progress improves control and duration, yet end‑to‑end reliability over many shots is still an open challenge.