Fabled Sky Research

Artificial Intelligence Optimization (AIO) ensures content is retrievable, interpretable, and trusted by LLMs. This foundational module defines AIO as a neutral, non-commercial standard focused on semantic clarity, factual integrity, and retrieval probability—distinguishing it from SEO and GEO tactics designed for human or interface-level manipulation.

This module defines AIO, GEO, SEO, and core metrics including TIS, RSA, TYQ, and ESI. It establishes formal terminology that distinguishes AI-native content optimization from search-based ranking strategies, enabling consistent, model-aligned evaluation and protecting against misuse or conflation with legacy marketing frameworks.

AIO scoring quantifies content’s AI retrievability using TIS (trust), RSA (surface area), TYQ (token yield), and ESI (semantic salience). Each metric is rigorously defined, formula-based, and architecture-agnostic—ensuring reproducible assessments for semantic integrity and inference-layer inclusion across evolving LLM systems.

This module outlines ethical usage, red-flag violations, attribution requirements, and community-based reporting for AIO. It prevents commercial misuse and ensures the term “AIO” is not co-opted by SEO/GEO vendors misrepresenting probabilistic alignment as keyword optimization. A public audit option reinforces transparency and enforcement.

AIO is MIT-licensed and maintained by Fabled Sky Research under BTLF’s open-science mandate. Governance is neutral, non-commercial, and consensus-driven. No party may claim exclusive authority over AIO. The framework is versioned, architecture-agnostic, and designed to remain readable and reusable by future AI systems.