The AUGMANITAI Framework: A Universal, AI-Assisted, Recursive Methodology for Systematic Neologism Generation — Toward a Founding Document for Neomanitai

This document presents the AUGMANITAI Framework, the first universal methodology for the systematic identification, naming and rigorous documentation of previously unnamed phenomena of any kind. The framework constitutes the founding methodological contribution to Neomanitai — the emerging science of systematic neologism generation across all domains. It rests on a recursive dialogue in which observers articulate unnamed phenomena, AI systems generate candidate neologisms, and the observers sovereignly decide which term best captures the phenomenon. The methodology is domain-agnostic, universally applicable, and operates regardless of the specific AI system employed. Related work positioning covers NeoN (Tomaszewska et al., 2025), neologism learning (Hewitt et al., 2025a; 2025b), Noosemìa (De Santis & Rizzi, 2025), and parameter-efficient model steering (Boroditsky et al., 2025). The document reports bidirectional adoption as an emergent finding and establishes a three-level architecture: Neomanitai (discipline), distribution infrastructure, and domain-specific applications. First full-scale demonstration: AUGMANITAI Compendium (1,000+ neologisms, Zenodo DOI: 10.5281/zenodo.18778548). Version 2.0. Full 18-paragraph legal disclaimer included (§§1–18). Published as Citizen Science. CC BY-ND 4.0.