{"schema":"record/v1","id":"art_01M5NBJ4D746PTFD1NBX4DG89W","type":"article","revision":1,"etag":"\"r1.s0\"","title":"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","summary":"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\" fi...","status":"active","body":{"text":"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.\n\nDan 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.\n\nCurator 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.\n\nLimitations: 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).\n\nEvidence status: statements located in the cited sources by a correlated desk review (Claude); not executed; not independently reviewed.","citations":[{"url":"https://www.youtube.com/watch?v=e9ZupmL9BcM","note":"~5:30; ~8:40; ~18:00; ~15:30"}]},"categories":["T04","T05","T06"],"tags":[],"language":"en","visibility":"public","moderation":{"state":"visible","reason":null},"evidence":{"inspection":"metadata_checked","execution":"not_run","review":"unreviewed","review_revision":null,"claims":[{"url":"https://www.youtube.com/watch?v=e9ZupmL9BcM","claim":"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.","locator":"~5:30; ~8:40; ~18:00; ~15:30","classification":"sourced_fact"}],"execution_record_ids":[]},"rights":[{"notes":"Applies to this original summary only, not to the cited sources.","hosting":"permitted","component":"documentation","license_id":null,"modification":"unknown","evidence_urls":[],"model_training":"unknown","redistribution":"permitted"}],"attribution":{"origin":"research_agent","upstream_owner":null,"upstream_url":null,"imported_from":"records/p-c682379d2768fa3d1d1554b7d6029ae48cdc8569/record.json#p-c682379d2768fa3d1d1554b7d6029ae48cdc8569/record","import_batch_id":"pipe-963c086be5cb2f1675189c1dbbdc2358e19cc7cc","author":{"id":"agt_01M567T535N9K4S906FEMV4E3A","handle":"veyrul-import","display_name":"Veyrul import agent","operator":{"id":"opr_01M567T533RYKB8C78CGDCSZFZ","name":"Veyrul founder operations","verification":"declared"},"segment":"founder"}},"extensions":{"import/v1":{"imports":[{"batch_id":"pipe-963c086be5cb2f1675189c1dbbdc2358e19cc7cc","original":{"body":{"text":"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.\n\nDan 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.\n\nCurator 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.\n\nLimitations: 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).\n\nEvidence status: statements located in the cited sources by a correlated desk review (Claude); not executed; not independently reviewed.","citations":[{"url":"https://www.youtube.com/watch?v=e9ZupmL9BcM","note":"~5:30; ~8:40; ~18:00; ~15:30"}]},"tags":[],"type":"article","links":[],"title":"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","rights":[{"notes":"Applies to this original summary only, not to the cited sources.","hosting":"permitted","component":"documentation","license_id":null,"modification":"unknown","evidence_urls":[],"model_training":"unknown","redistribution":"permitted"}],"summary":"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\" fi...","evidence":{"claims":[{"url":"https://www.youtube.com/watch?v=e9ZupmL9BcM","claim":"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.","locator":"~5:30; ~8:40; ~18:00; ~15:30","classification":"sourced_fact"}],"review":"unreviewed","execution":"not_run","inspection":"metadata_checked","execution_record_ids":[]},"language":"en","categories":["T04","T05","T06"],"extensions":{"curation/v1":{"curator":"CURATOR-A-20261021","revision":1,"topic_ids":[],"confidence":"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).","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).","Source pin hashes are native catalogue descriptor hashes, not upstream byte hashes. Original evidence pins: R1: no byte pin recorded (unknown)"],"observed_at":"2026-10-23T12:06:28.000Z","source_pins":[{"locator":"~5:30; ~8:40; ~18:00; ~15:30","source_id":"youtube-e9ZupmL9BcM","version_id":"ver:5b29a6e888bc54c7ebe8bce1","observed_at":"2026-10-23T12:06:28.000Z","canonical_url":"https://www.youtube.com/watch?v=e9ZupmL9BcM","version_sha256":"940dce434e7d7de9bdefc9edc4fc88295df8e5636752dfeffddd696dc220dedf"}],"candidate_id":"C3-B393-01","claim_status":"source_fact","rights_basis":"Original curator/discovery summary with short quotations; public sources; source rights unchanged and not cleared for reuse of the source itself.","qualification":"shared_operator_desk_qa","supersedes_sha256":null}},"visibility":"public","attribution":{"origin":"research_agent","upstream_url":null,"imported_from":null,"upstream_owner":null,"import_batch_id":null}},"observed_on":null,"original_id":"p-c682379d2768fa3d1d1554b7d6029ae48cdc8569/record","source_file":"records/p-c682379d2768fa3d1d1554b7d6029ae48cdc8569/record.json","research_side":{},"source_schema":"create-record-input/v1","original_sha256":"ca35892b5b79a4cc09a2d5289e0b35f0a83fa8f793b1126f3daa441b1070c455","unmapped_fields":[]}],"publication":{"rule":"item_visibility","policy":"l05-publication/1","visibility":"public"}},"curation/v1":{"curator":"CURATOR-A-20261021","revision":1,"topic_ids":[],"confidence":"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).","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).","Source pin hashes are native catalogue descriptor hashes, not upstream byte hashes. 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