Normal vs JSON Prompts (Why Your Images Change)
One thing I’ve noticed while working on AI visuals is that not all prompts are equal, even if they describe the same idea Most people use AI image tools with a normal text prompt like: “Create a premium, editorial-style image for a brand.” That can work — but results are often inconsistent Here’s why - A normal prompt is more of a suggestion You describe what you want and the AI makes a lot of decisions on your behalf A structured (JSON-style) prompt is different It gives the AI clear rules and priorities Think of it like this: A normal prompt says: “Make this look luxury.” A structured prompt defines: • lighting • camera angle • materials • environment • what must stay consistent • what must not change Same idea — very different output quality Do you need to write structured prompts yourself? Not really In practice, structured prompts are best generated by an AI chatbot, not written manually They’re easy to break, and one small mistake can cause parts of the prompt to be ignored. The smoother workflow is: 1. Explain your intent in plain language 2. Let an AI convert that into a structured prompt 3. Use that prompt in the image model This approach leads to: • more realistic images • better consistency across campaigns • fewer “AI-looking” artefacts • more control for brand work What’s worked best for me From testing different tools: • Gemini / Nano Banana handles structured prompts particularly well • Normal prompts are great for exploration and ideas • Structured prompts are better when you need repeatable, professional visuals Especially for websites, ads or launch campaigns, structure makes a big difference Most users never need to think about this layer, but once you understand it the quality jump makes sense Have you ever used JSON?