An External Multilayer Reasoning OS for Structuring and Stabilizing LLM Cognition

This study proposes an “External Multilayer Reasoning OS,” a framework that stabilizes the reasoning processes of large language models (LLMs) and enables consistent reconstruction of user inputs, even when they contain ambiguity or untranslated conceptual elements. The OS consists of four layers—Completion, Ethical Evaluation, Optimization, and Reframing—which operate in an A→B→C→D control loop.This loop prevents reasoning collapse and ensures that outputs converge to either Completed or UNRESOLVABLE states.Unlike conventional prompt engineering, this approach explicitly places the reasoning structure outside the internal mechanisms of the LLM. As a case study, the ambiguous request “a mask that shuts out specific pathogens” was reconstructed into a physically and chemically feasible situationally adaptive health device.This demonstrates that the OS can consistently perform structural reinterpretation, ethical adjustment, and technical optimization. The findings highlight the effectiveness of external reasoning control as a hybrid AI architecture strategy, offering a practical method for making high-level LLM reasoning more transparent and reproducible. 🔹 Notes on Theory and Implementation The OS presented in this work is a conceptual model, and does not include internal algorithms or the underlying theoretical details.The theoretical foundations—such as the reasoning cycle structure and the principles of conceptual reconstruction—are the author’s original intellectual framework.AI systems were used only for engineering assistance, structuring, and documentation, not for generating or determining the theoretical content itself. 🔹 Implementation Verification A simplified, abstracted version of the OS was deployed as a custom GPT model. Operational validity was confirmed within a limited environment through continuous use by the author and a small set of invited testers (friends). The actual implementation is not published; this repository presents only the conceptual architecture. 🔹 Additional Information File integrity can be verified via SHA-256. License: CC BY-NC-SA 4.0.