The Universal Intelligence Manual: A Technical Framework for AI Mastery (3.0)

Abstract

Existing pedagogical models for Artificial Intelligence are often embedded within high-premium commercial ecosystems, contributing to a secondary form of digital divide in which advanced AI literacy is frequently mediated by cost and access barriers. To address this, this paper introduces the Universal Intelligence Manual, a modular, zero-cost technical framework designed to expand accessibility in AI-assisted learning and reasoning practices. Grounded in the Adaptive Cognitive Echo Modeling (ACEM) protocol, the manual proposes a structured architecture for human-AI interaction across multiple platforms, including Grok, ChatGPT, and Midjourney. By integrating Mental Health and Psychosocial Support (MHPSS) principles alongside World Health Organization (WHO) mental health guidelines, the framework emphasizes cognitive sustainability and aims to reduce the risk of mental fatigue during advanced technical engagement. This work further presents a structured deconstruction of prompt engineering into core cognitive components, reframing AI interaction as a function of logical anchoring and structured intent rather than credential-based access. In doing so, it positions the framework as a conceptual Technical Commons, emphasizing that AI literacy can be understood through cognitive structure rather than financial capacity. In summary, this research proposes a low-barrier, structured approach to AI-assisted cognition intended to support equitable access to AI literacy across diverse resource environments, including low-bandwidth and rural contexts, by prioritizing cognitive frameworks over infrastructural dependence.

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