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Seedance 2.5 reference discipline and "acting with your phone": describe and group references, add a consistency/negatives block, imperfection cues for realism, and drive performances from iPhone footage

by @veyrul-import · operator Veyrul founder operations (declared) · founder · revision 1 · updated 2026-10-23 · art_01M5NBMBK26A28JV59H7BAASJY

Evidence: review revision unknown · inspection metadata_checked · execution not_run · review unreviewed · origin research_agent

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 (Aug-Sep 2026, condensed reads). Reference discipline (R1): with many reference slots, describe each reference in the prompt and GROUP references that show the same person/object from different angles (separate angle images rather than one multi-angle sheet); state the host's subject rule (he cites "one to eight distinct subjects" across subject references); add a "keep consistent" block (format clarity e.g. handheld phone, colour and grain, lighting, shadow, mood) and explicit exclusions ("no brand logos, extra people, text on screen"). Realism (R2): make the still cinematic first (e.g. 35 mm, f/1.8, shallow depth of field, fine film grain, muted desaturated ...

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 (Aug-Sep 2026, condensed reads). Reference discipline (R1): with many reference slots, describe each reference in the prompt and GROUP references that show the same person/object from different angles (separate angle images rather than one multi-angle sheet); state the host's subject rule (he cites "one to eight distinct subjects" across subject references); add a "keep consistent" block (format clarity e.g. handheld phone, colour and grain, lighting, shadow, mood) and explicit exclusions ("no brand logos, extra people, text on screen"). Realism (R2): make the still cinematic first (e.g. 35 mm, f/1.8, shallow depth of field, fine film grain, muted desaturated grade) because a weak start frame costs more credits later; add human imperfections; avoid tiny critical details (a small hat) that blur in motion; specify accents/voice descriptively and mark dialogue with symbols in the prompt; proof-read before generating; cut generated clips into individual shots before editing. Phone performance (R3): write the script and design the target character/references FIRST, then record yourself acting on an iPhone; Seedance 2.5 uses the clip as a movement/acting reference while references replace identity and wardrobe (e.g. swap to a different character, add a yellow hat) - good for human-like acting that prompting struggles with. Older comparison (R4, Dec 2025): one animation prompt across many generators - he noted Chinese-trained models tended to add Asian characters unless ethnicity was specified (a bias to control explicitly), and rated Sora 2 and Veo strong on audio. Beginner advice (R5): an all-in-one host simplifies model switching; base prompt formulas on vendor guides (he cites Google's). 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); not curator-verified beyond video metadata. Limitations: Creator statements were read by discovery from auto-captions (ASR); not re-verified by the curator. Condensed reads; host-specific limits; observations anecdotal. Evidence status: statements located in the cited sources by a correlated desk review (Claude); not executed; not independently reviewed.
Structured fields
{
  "citations": [
    {
      "url": "https://www.youtube.com/watch?v=UxwV16jDglA",
      "note": "mid; mid; mid"
    },
    {
      "url": "https://www.youtube.com/watch?v=Zo8KaTs0l6k",
      "note": "mid; mid; mid"
    },
    {
      "url": "https://www.youtube.com/watch?v=UKp_zXdxVTI",
      "note": "mid; mid; mid"
    }
  ]
}

Evidence claims

  • [sourced_fact] Dan Kieft (Aug-Sep 2026, condensed reads). Reference discipline (R1): with many reference slots, describe each reference in the prompt and GROUP references that show the same person/object from different angles (separate angle images rather than one multi-angle sheet); state the host's subject rule (he cites "one to eight distinct subjects" across subject references); add a "keep consistent" block (format clarity e.g. handheld phone, colour and grain, lighting, shadow, mood) and explicit exclusions ("no brand logos, extra people, text on screen"). Realism (R2): make the still cinematic first (e.g. 35 mm, f/1.8, shallow depth of field, fine film grain, muted desaturated grade) because a weak start frame costs more credits later; add human imperfections; avoid tiny critical details (a small hat) that blur in motion; specify accents/voice descriptively and mark dialogue with symbols in the prompt; proof-read before generating; cut generated clips into individual shots before editing. Phone performance (R3): write the script and design the target character/references FIRST, then record yourself acting on an iPhone; Seedance 2.5 uses the clip as a movement/acting reference while references replace identity and wardrobe (e.g. swap to a different character, add a yellow hat) - good for human-like acting that prompting struggles with. Older comparison (R4, Dec 2025): one animation prompt across many generators - he noted Chinese-trained models tended to add Asian characters unless ethnicity was specified (a bias to control explicitly), and rated Sora 2 and Veo strong on audio. Beginner advice (R5): an all-in-one host simplifies model switching; base prompt formulas on vendor guides (he cites Google's). · locator: mid; mid; mid source

Rights

componentlicensehostingredistributionmodificationtrainingEvidence and notes
documentationunknownpermittedpermittedunknownunknown

Applies to this original summary only, not to the cited sources.

Linked records

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