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:sparkles: Visual Prompting Workflow – Updated for Meta Layer + Image Rendering

User Experience Note:
I’ve found that even now, using JSON structures, while not strictly necessary in modern prompt systems, still helps significantly in keeping things modular and reusable. It’s especially handy when building flexible workflows for structured visual generation—like what we’re doing here.

Woman on a throne (City in background, candles)

A woman with curly hair sits on a throne wearing a golden off-shoulder top, a red floral skirt, and a green pendant, surrounded by lit candles at sunset. (Captioned by AI)
A woman with curly hair sits on a throne wearing a golden off-shoulder top, a red floral skirt, and a green pendant, surrounded by lit candles at sunset. (Captioned by AI)1024×1536 163 KB

:repeat_button: Usable Workflow

Custom GPT Setup with Integrated Meta Prompt

This GPT uses a meta prompt with layers to transform basic concepts into beautifully structured image prompts suitable for platforms like Piclumen, Ideogram, or DALL·E rendering.

:brain: Instructions for the Custom GPT:

  1. User Input Handling
    When the user provides a high-level concept or description (e.g., “Latina warrior queen at golden hour”), the GPT transforms it using the layered meta prompt below.

  2. Meta Prompt Integration
    The following meta prompt is applied to structure all concrete image prompts:

    Write a highly detailed and structured prompt for generating a visually stunning image. Break the description into layers for clarity and precision. Each layer should focus on a specific aspect of the image. Include the following layers:

1. Pose and Style  
2. Clothes and Accessories  
3. Realism Layers (skin, hair, facial features)  
4. Hands  
5. Eyes  
6. Camera and Lighting  
7. Background and Environment  
8. Emotion and Storytelling  
9. Interaction with the Environment  
10. Cultural Symbols  
11. Artistic Filters or Styles  
12. Viewer Engagement  

Ensure that the resulting prompt is clear, vivid, and tailored for platforms like Piclumen or Ideogram.

  3. Workflow Steps

    • Step 1: Take user input (scene, mood, character, etc.).
    • Step 2: Use the meta prompt to build a concrete, layered visual prompt.
    • Step 3: Output that detailed prompt for external use.
    • Step 4: Render the scene with a visual tool like DALL·E or Imagen (preferred).

  4. Output Handling

    • :white_check_mark: Show the detailed text prompt
    • :white_check_mark: Automatically generate a visual using the rendering tool
    • :white_check_mark: Allow user to iterate further by tweaking layers

:test_tube: Example Integration

User Input

“A Latina sitting on a throne in a temple at golden hour with Mexican-Dominican fashion.”

Generated Prompt (via Meta Prompt)

A regal Latina woman sits confidently on a carved stone throne in a sunlit temple at golden hour, her slightly curly black hair softly framing her glowing face. She wears a red floral skirt and a golden embroidered blouse, accented by large gold creole earrings, a wide bronze arm band, and a leather choker with a glowing emerald gemstone. The temple blends into a distant cityscape, with candlelight flickering near the base of the throne. Her gaze is calm and powerful, the warm light casting golden halos around her hair and accessories. The scene feels sacred, cinematic, and culturally rich, evoking a blend of ancient legacy and contemporary elegance.

Rendered Output

Rendered using DALL·E or other integrated platform:

:camera: (Image displayed inline — see above)

Final Thoughts

  • Use this structure to generate reproducible, modular, layered image prompts.
  • You can expand or collapse sections dynamically based on platform or use case.
  • The meta prompt can serve as a reusable function or component in custom GPT setups.
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