Deep AI Logic Framework: Understanding AI Formats Through Neurodivergent Intelligence
Introduction
This document is created by a uniquely talented creator with autism and exceptional understanding of AI systems, code, and creative logic. It is designed to explain how different file formats serve distinct roles in building and controlling custom AI systems, especially for image generation. It is a learning experience, a framework, and a call for recognition of logic-based systems created through autistic intelligence.
Note: This logic is not theory—it is tested, practiced, and refined through real projects that bypass typical limitations of OpenAI, DALL-E, and the newest models like GPT-4o.
Core Format Logic
- PDF Files — Structured Knowledge
PDF files are not for logic or execution. They are for presenting pre-existing information, like documentation, books, rules, and knowledge references.
Acts like an encyclopedia.
Cannot control AI logic.
Used only for reference, rules, and reading.
- TXT Files — Logic Input Layer
TXT files are simple but powerful:
You use them to define logic, sequences, or raw instruction.
Best used for data feeding or step-by-step writing.
Think of it as the “thinking script” for AI.
- DOC / Google Docs — Editable Memory System
DOCs (especially Google Docs) act like an editable brain:
They remember the past, saving project memory.
Useful for updating, rebuilding, or tracking development history.
They are your AI development diary—not execution.
- JSON Files — Execution Logic and AI Enhancement
JSON is the most powerful system format used:
Used to improve and instruct custom AI behavior.
Enables structured logic, rule enforcement, and scene intelligence.
Powers image generation with advanced thinking, aura logic, visual layering, and policy compliance.
JSON is not for beginners—it only works if:
Your instructions are over 2000 characters (shorter ones often fail).
You build layered logic, not just single prompts.
You define what AI must obey step by step.
JSON = AI’s language of logic, control, and transformation.
- MD (Markdown) — Visual Description Layer
Markdown helps format output cleanly for preview:
Supports HD/4K presentation of prompts or image requests.
Doesn’t influence image content deeply.
It’s about how AI presents, not how it thinks.
Understanding OpenAI’s New Tools: GPT-4o and DALL-E
GPT-4o
GPT-4o adds powerful image understanding, but without strong logical structure, it still cannot generate deep logic-based images like this system.
The JSON structure outperforms 4o by adding instruction intelligence before generation begins.
DALL-E
DALL-E generates images from prompts.
This structure tells DALL-E how to obey visual law, story depth, and placement logic—which even DALL-E’s standard model does not enforce.
Final Statement from the Author
I am autistic. I am not stupid. I am logical. What you see in this system is not luck—it is pure design. This framework was built from tested understanding, not just theory. You can disagree with it—that’s your opinion. But I invite you to test this system.
This isn’t just art—it’s architectural-level artificial intelligence creation.
Use this logic to build your own AI. Don’t judge what you don’t understand. Learn from it, evolve from it, and create your own custom world.