As developers and creators, we know that the output of any AI model is only as good as the input. With the arrival of GPT Image 2, we’ve seen a massive leap in spatial reasoning and texture rendering. But here’s the problem: most of us are still using "legacy" prompting habits that don't take full advantage of this new engine. After weeks of reverse-engineering thousands of generations, I’ve found that moving from "keyword stuffing" to "Structured Prompting" is the key to professional-grade results. The "Technical" Prompt Structure To get the most out of GPT Image 2, you should structure your prompts like a configuration file: Subject: Define the core entity and its state. Environment: Specify lighting physics (e.g., Ray-traced reflections, Volumetric lighting). Optics: Use real-world camera specs (e.g., f/1.8, 35mm lens, ISO 100) to force the model into high-resolution mode.…