Image generation control

The practice of using specific inputs—ranging from natural language to structured data—to manipulate AI Image Generators for precise, predictable, and repeatable visual outputs.

Control Modalities

• prompt-engineering: Utilizing natural language descriptions to influence subject, lighting, and composition.
• Structured Prompting: Implementing formal data formats to define scene parameters and reduce ambiguity.
  • JSON Prompts: A technique for ChatGPT Image 2.0 that uses json objects to achieve granular, advanced control over the generation process.
  • Allows for a highly precise workflow by establishing structured instructions for the model to interpret.
• Parameter Tuning: Manipulating technical variables (e.g., aspect ratio, seeds, or weights) to refine iterative outputs.

Related Concepts

• generative-ai
• prompt-engineering
• Automation Workflows

Sources

• 2026 04 26 Craig Does AI JSON Prompts for Advanced ChatGPT Image 2.0 Control

Source Notes

• 2026-04-10: [[lab-notes/2026-04-10-Google-Nano-Banana-2-Rapid-Professional-AI-Image-Generation-and-Contro|New Nano Banana Update: How to Use Nano Banana 2]]
• 2026-04-26: Craig Does AI: JSON Prompts for Advanced ChatGPT Image 2.0 Control