Rethinking AI Image Prompts Through Object-Oriented Design
Recently, I dove deep into how I craft prompts for AI image generation, inspired by a talk I did for べこくり. It’s not just about throwing words into the input box; it’s about structuring those words like an object-oriented system, where each element has a clear role and relationship. This approach transformed my workflow with seedream4.5, and I used Nano Banana Pro to create stylish, annotated breakdowns of the characters generated.
The visuals I created don’t just show the character but also how each feature relates to the prompt’s structure. The yellow vectors you see? They’re not part of the prompt but hint at the physical dynamics and movement ranges of the human body. It’s a subtle insight that can inspire more natural and believable poses in your AI art—something I hadn’t realized I was missing before.
What really surprised me was how much this method made me think about the prompt as a system rather than a simple text input. It’s almost like coding, where each attribute is an object with properties that influence the final image. This clarity helped me avoid common prompt mistakes and fine-tune my descriptions, yielding cleaner, more intentional results.
For creators curious about the UI and illustration side of this breakdown, I’m excited to share that a detailed guide on making these annotated images will be released soon. For now, I’m sharing three UI prompt breakdowns—two will be exclusive on my note page, but stay tuned here for the first.
Using this object-oriented approach shifted how I think about text to image processes and helped me get better control over my outputs. If you’re experimenting with AI art, I highly recommend trying to map out your prompt elements like objects and see how that changes your results.
You can find the full prompt here: ✨Prompt✨
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