How to build a reliable video-to-prompt pipeline

Short summary

The author describes a video-to-prompt pipeline that treats the output as the last stage of a compiler: video is first converted into a structured JSON record (shots, camera, dialogue, actions), then rendered for a specific video model. Key stages include canonical ingestion, dual-signal shot segmentation, word-level transcription mapping, and schema-validated per-shot descriptions. The structured record stays model-neutral so different video models can consume it.

• •Treat video-to-prompt as a compiler: convert video to structured JSON record, then render for target model
• •Dual-signal segmentation (visual discontinuity + semantic change) prevents missed events at cuts
• •Word-level transcription timestamps mapped to shots prevents dialogue attribution errors

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