GPT Image 2 children's picture book AI lab story page. Topics: AI Education, Children Picture Book, Colored Pencil, Gouache, Gpt Image 2, Multi Panel Illustration, Storybook Layout, X Prompt Redraw.

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Use this as a reference for AI Education, Children Picture Book, Colored Pencil, Gouache workflows, prompt structure, visual constraints, and output review.

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Prompt text

Create a children’s picture book interior page in a vertical format, with a warm off-white paper background and a multi-panel storybook layout. Use a hand-drawn children’s book illustration style with soft gouache, colored pencil, and crayon textures, visible paper grain, natural sketch-like lines, and rounded, charming characters. Add clear and readable story text, laid out like a real picture book page. Key words may be highlighted in color, with a few small hand-drawn decorative elements throughout the page.

Story content: The story of a friendly AI research lab, told as one page from a longer children’s book. Do not use any real company logo, trademark symbol, or branded product design. The page should show a small group of kind inventors, curious children, helpful glowing robot companions, notebooks, stars, blocks, and warm classroom-lab scenes. Include simple readable storybook text such as: “In a little lab full of questions, friends taught a bright machine to listen, learn, and help.” Make the page feel gentle, optimistic, educational, and suitable for a children’s picture book.

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Thanks to the original creator whose public post supplied the prompt for this image.

Source note: Prompt extracted from a public X/Twitter post by 宝玉 and reused with attribution at the user's request. Edits from originalPrompt to generationPrompt were limited to rights/safety handling for a real brand reference and copyrighted-character examples in a same-author reply.

GPT Image 2 children's picture book interior page prompt

宝玉 / @dotey

original_prompt_source / author_credit / social_workflow_reference

Accessed 2026-05-04 · public social post; prompt reused with attribution at user request

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