Case study on structured JSON prompt engineering for AI image generation. Analyzes 4 real-world examples that achieved high engagement (513+ likes, 13K+ views) using hierarchical JSON schemas instead of natural language prompts. Each example demonstrates how structured data enables precise control over subject, environment, lighting, camera settings, and technical parameters. Includes complete JSON templates covering identity preservation, composition, negative prompts, and quality constraints. Useful for developers working on prompt optimization, AI image APIs, or studying the shift from text-based to structured prompt interfaces.

We found the same thing while building GTWY. Free-form prompts look powerful early, but structured inputs scale better in production. Once behavior needs to be predictable, structure wins.