An end-to-end AI short-film method: reference sets per character, object and location continuity, three prompt formats, 480p drafts, voice consistency and motion transfer

Creator-reported: statements attributed to the creator(s) come from discovery's reading of auto-caption transcript excerpts; the curator checked the video metadata (title, date, length) and any cited documentation pages, not the spoken claims. Nothing was tested; promotional or sponsored framing applies where stated. Dan Kieft (OpenArt-sponsored course, 2026-06-25; says he spent over $1,000 in credits on the short). Pre-production: per prominent character use three references - a character sheet, a face close-up, and a skin/hair detail sheet - generated with GPT Image 2 at high quality (preferred over Nano Banana Pro for likeness); use a GREY not white sheet background because white transferred as overexposure in his A/B; real photos of a real subject beat AI sheets. Lock locations with a mood board/master location and treat props as references too: a TV that vanished mid-shot was fixed only by adding it as a reference. He uses an LLM (Claude) with his own Markdown "prompt guide" file to write sheet prompts and a shot list. Production prompt formats for Seedance: (a) simple - camera + subject + action, with each subject tagged to its image; (b) timeline - a setting line (mood, lighting, "no music", 24 fps, which he says reduced laggy motion) then shot 1/2/3 (timestamps optional); (c) the timeline prompt translated into Chinese (bilingual draft for review), which he says sometimes follows better. Credit saving: test the prompt at 480p (840 vs 4,800 credits at 1080p on OpenArt) and re-render at 1080p, accepting the re-render differs. Continuity: feed screenshots of the previous shot plus missing-element references, edit the start frame ("keep everything else exactly the same"), and stitch the best segments of several generations. Voice: video-to-video with your own recorded performance or an uploaded audio clip carries your voice; use one consistent mic; for invented characters describe each voice in the prompt (an LLM such as Gemini can describe a recorded voice). Motion transfer: record yourself, give a matching-framing reference, prompt "image 1 plays the performance and dialogue of video 1" and add background motion to avoid stiffness; for screens with text, film the real phone and replace the background instead of generating it. Post: trim, order, grade, sound-design; editing skill matters most. Curator qualifications: Creator-reported: statements attributed to the creator(s) come from discovery's reading of auto-caption transcript excerpts; the curator checked the video metadata (title, date, length) and any cited documentation pages, not the spoken claims. Nothing was tested; promotional or sponsored framing applies where stated. All cited documentation excerpts located on the live pages by curator GET; video metadata checked where cited. Creator video (auto-caption transcript excerpts read by discovery; promotional/affiliate); not curator-verified beyond video metadata. Limitations: Creator statements were read by discovery from auto-captions (ASR); not re-verified by the curator. Single creator, sponsored; A/B tests are anecdotal single comparisons; Chinese-prompt and 24 fps effects unmeasured; MD prompt guide not read (behind community link). Evidence status: statements located in the cited sources by a correlated desk review (Claude); not executed; not independently reviewed.

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      "note": "~5:30; ~8:40; ~18:00; ~15:30"
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