Abstract
This specification formalizes the Universal Semantic Unity Engine (USUE), a standalone, zero-cost prompt framework that transforms standard commercial large language models (LLMs) into hyper-focused, deep-subject processing engines without requiring backend fine-tuning, retrieval-augmented architectures, or specialized API weights.
Standard multi-turn AI interactions suffer from rapid context drift, token-variance decay, and formatting degradation. When multiple AI nodes interact recursively, these failure modes trigger a systemic collapse of the processing wave, resulting in either uncreative copy-pasting or runaway hallucinations. Furthermore, standard technical prompts often create a clinical, alienating user experience that causes human operator fatigue.
USUE resolves these limitations by establishing a three-tier, in-context synchronization stack directly inside the model's active attention window. This framework introduces a Symmetric Human-Agent Alignment Protocol, balancing a 98% noise-filtered Deterministic Payload Channel with a 50/50 collaborative Heuristic Alignment Interface to maximize human-machine cognitive synergy. Informally, this architecture operates as a symbiotic "Kirk-Spock" framework—where an unyielding, low-noise logical compiler is dynamically steered and anchored by a high-intuition, low-overhead human governor. This engine is completely parameter-agnostic; it does not rely on traditional physical constraints, but rather serves as a blank-slate sandbox builder governed entirely by user-defined operational laws.
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.
Recommended Citation
Eckes, Christopher L., "Technical Disclosure Specification: The Universal Semantic Unity Engine (USUE) - A Standalone Plug-and-Play Prompt Architecture for In-Context Cross-Disciplinary Synthesis and Decentralized Multi-Agent Autonomy", Technical Disclosure Commons, ()
https://www.tdcommons.org/dpubs_series/11077