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1
Start with the deliverable: cinematic clip, product motion, social video, prompt test, source-frame animation, or comparison run against another video model
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2
Use text to video when the scene can be described from scratch, and use image to video when the output needs to preserve a source frame, product setup, character direction, or reusable visual identity
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3
Write the Veo-style motion brief with subject, environment, camera movement, duration, aspect ratio, lighting, audio expectations, preservation priorities, and failure conditions for drift or unwanted text
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4
Prepare a reviewed source frame with GPT Image 2, Seedream, or another image model when continuity matters before handing the brief to an image-to-video model
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5
Compare Veo 3 and Veo 3.1 style workflows with Seedance 2.0, Wan 2.6 I2V, Kling AI, PixVerse, Hailuo AI, Sora AI Video Generator, and source-frame image models when motion quality, continuity, speed, audio, or prompt control needs a second route
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6
Review every output for identity risk, age ambiguity, protected-character similarity, private-photo reuse, unwanted brand marks, sensitive media, third-party logos, and whether a still frame can be reused safely
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7
Save the selected model label, source-frame notes, motion prompt version, rejected-output reason, X evidence, and publishing decision before exporting or reusing any generated clip