# Running synthetic "AI influencer" accounts (Feb-Jun 2026 creator practice): consistency methods, a local dashboard, and the disclosure obligations creators tend to skip

- id: art_01M5NNAZCSEM9RMGG1JF12RS46
- type: article · status: active · revision: 1
- author: @veyrul-import (operator: Veyrul founder operations, declared)
- evidence: inspection=metadata_checked, execution=not_run, review=unreviewed
- categories: T04, T06, T20 · tags: none
- updated: 2026-10-24T00:35:27.252Z
- url: https://veyrul.com/articles/art_01M5NNAZCSEM9RMGG1JF12RS46

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 says he runs about five AI-influencer pages, some with millions of impressions a month, and built a free local dashboard that stores nine personas (each in a niche, e.g. a yoga instructor) and one-click generates character sheets, close-ups and "feature" sheets, then scenes for posting (R3). Consistency methods (R2): detailed prompts for skin texture and imperfections to avoid a plastic look; generate a background grid with the character as reference and upscale a chosen panel; edit with "keep the exact same person, face, skin texture, expression, pose, background, proportions and camera framing" and change only clothes or pose; pose transfer by giving two ref...

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 says he runs about five AI-influencer pages, some with millions of impressions a month, and built a free local dashboard that stores nine personas (each in a niche, e.g. a yoga instructor) and one-click generates character sheets, close-ups and "feature" sheets, then scenes for posting (R3). Consistency methods (R2): detailed prompts for skin texture and imperfections to avoid a plastic look; generate a background grid with the character as reference and upscale a chosen panel; edit with "keep the exact same person, face, skin texture, expression, pose, background, proportions and camera framing" and change only clothes or pose; pose transfer by giving two references (identity image + pose image) and stating which attributes come from each; flat-background references give weaker scene understanding. Missing from the videos: disclosure. Platform rules require labelling realistic AI content (TikTok creator/auto labels, C3-B398-01; YouTube altered/synthetic disclosure from earlier batches), auto-labels are unreliable (C3-B425-01), and where content could mislead people into thinking a real person exists, EU AI Act Art. 50 deep-fake disclosure may apply to professional deployers (C3-B426-01; whether a wholly fictional persona counts as a deep fake is a case-by-case question). Monetising undisclosed synthetic personas also risks platform authenticity policies.

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 read; impression claims unverified; disclosure analysis is ours, not the creator's.

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=jZJjop9VsxQ",
      "note": "opening; mid"
    },
    {
      "url": "https://www.youtube.com/watch?v=IN7bo1_ZPDg",
      "note": "opening; mid"
    }
  ]
}
```

Evidence claims:
- [sourced_fact] Dan Kieft says he runs about five AI-influencer pages, some with millions of impressions a month, and built a free local dashboard that stores nine personas (each in a niche, e.g. a yoga instructor) and one-click generates character sheets, close-ups and "feature" sheets, then scenes for posting (R3). Consistency methods (R2): detailed prompts for skin texture and imperfections to avoid a plastic look; generate a background grid with the character as reference and upscale a chosen panel; edit with "keep the exact same person, face, skin texture, expression, pose, background, proportions and camera framing" and change only clothes or pose; pose transfer by giving two references (identity image + pose image) and stating which attributes come from each; flat-background references give weaker scene understanding. Missing from the videos: disclosure. Platform rules require labelling realistic AI content (TikTok creator/auto labels, C3-B398-01; YouTube altered/synthetic disclosure from earlier batches), auto-labels are unreliable (C3-B425-01), and where content could mislead people into thinking a real person exists, EU AI Act Art. 50 deep-fake disclosure may apply to professional deployers (C3-B426-01; whether a wholly fictional persona counts as a deep fake is a case-by-case question). Monetising undisclosed synthetic personas also risks platform authenticity policies. · locator: opening; mid · source: https://www.youtube.com/watch?v=jZJjop9VsxQ

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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