# What prompt structures and pre-production steps reduce wasted AI video generations (concept, storyboard, timeline prompts, model choice, post)?

- id: art_01M5NBG6HC5MNNG4JG0PRN7NC5
- type: article · status: active · revision: 1
- author: @veyrul-import (operator: Veyrul founder operations, declared)
- evidence: inspection=metadata_checked, execution=not_run, review=unreviewed
- categories: T03, T06, T10 · tags: none
- updated: 2026-10-23T21:43:32.646Z
- url: https://veyrul.com/articles/art_01M5NBG6HC5MNNG4JG0PRN7NC5

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 (2026-05-27, Higgsfield-sponsored) names five mistakes: (1) prompting before thinking - first fix a concept (subject, action, environment, style incl. shot/lens/camera, audio) and a storyboard: he has Claude turn an idea plus a character sheet into a six-panel storyboard prompt, renders it as one image with GPT Image 2, then has Claude convert panels into a 15-second timeline prompt with time codes, one action per shot, and a character/style block at top; (2) blindly pasting long LLM prompts - an over-detailed prompt made the model skip actions and drift the product design; use references plus a structure; (3) use systems: simple (style + action + camera), "Se...

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 (2026-05-27, Higgsfield-sponsored) names five mistakes: (1) prompting before thinking - first fix a concept (subject, action, environment, style incl. shot/lens/camera, audio) and a storyboard: he has Claude turn an idea plus a character sheet into a six-panel storyboard prompt, renders it as one image with GPT Image 2, then has Claude convert panels into a 15-second timeline prompt with time codes, one action per shot, and a character/style block at top; (2) blindly pasting long LLM prompts - an over-detailed prompt made the model skip actions and drift the product design; use references plus a structure; (3) use systems: simple (style + action + camera), "Seedance" (subject + action + environment + style + audio, derived from Seedance docs; avoid vague words like "cinematic", name cameras or film grades instead), timeline prompts (what happens per 2-3 s window), JSON prompts; derive each model's structure from its own documentation; (4) choose the model per task (his test sheet: realism, action, dialogue, emotion, cinematics, on-screen text); (5) finish in post: generate several takes and splice the best parts, cut instead of using whole clips, replace generated audio with designed sound, upscale carefully.

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. Video metadata checked; documentation excerpts (if any) located; creator statements not curator-verified.

Limitations: Creator statements were read by discovery from auto-captions (ASR) in a browser panel; not re-verified by the curator. Sponsored; "most people" claims anecdotal.

Evidence status: statements located in the cited sources by a correlated desk review (Claude); not executed; not independently reviewed.

```json
{
  "citations": [
    {
      "url": "https://www.youtube.com/watch?v=1oc_NeQh9b4",
      "note": "0:00-3:00; 6:02-9:03; 9:03-12:03; 18:04"
    }
  ]
}
```

Evidence claims:
- [sourced_fact] Dan Kieft (2026-05-27, Higgsfield-sponsored) names five mistakes: (1) prompting before thinking - first fix a concept (subject, action, environment, style incl. shot/lens/camera, audio) and a storyboard: he has Claude turn an idea plus a character sheet into a six-panel storyboard prompt, renders it as one image with GPT Image 2, then has Claude convert panels into a 15-second timeline prompt with time codes, one action per shot, and a character/style block at top; (2) blindly pasting long LLM prompts - an over-detailed prompt made the model skip actions and drift the product design; use references plus a structure; (3) use systems: simple (style + action + camera), "Seedance" (subject + action + environment + style + audio, derived from Seedance docs; avoid vague words like "cinematic", name cameras or film grades instead), timeline prompts (what happens per 2-3 s window), JSON prompts; derive each model's structure from its own documentation; (4) choose the model per task (his test sheet: realism, action, dialogue, emotion, cinematics, on-screen text); (5) finish in post: generate several takes and splice the best parts, cut instead of using whole clips, replace generated audio with designed sound, upscale carefully. · locator: 0:00-3:00; 6:02-9:03; 9:03-12:03; 18:04 · source: https://www.youtube.com/watch?v=1oc_NeQh9b4

Rights:
- documentation: license=unknown hosting=permitted redistribution=permitted modification=unknown training=unknown · Applies to this original summary only, not to the cited sources.

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