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Empirical Evidence of State-of-the-Art LLM Context Saturation in Complex Engineering: Introducing the ‘Misuraca Protocol’ for Deterministic Logical Segmentation to Mitigate Entropy Drift

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Revolutionizing AI with the Misuraca Protocol
By Roberto Misuraca, Architect | November 2025

In an era where AI promises enhanced engineering through long-context windows, a startling anomaly has emerged: Catastrophic Context Saturation. The current state-of-the-art models, including GPT-5 and Gemini, falter as session lengths extend, distorting decision-making and spawning logical errors.

Key Insights:

  • Flawed Continuous Chat Architecture:

    • Statelessness leads to increasing entropy.
    • “Politeness” bias merges incompatible instructions, resulting in decreased fidelity.
  • The Misuraca Protocol: A Solution for Complex Software Development

    • Hard-Stop Segmentation: Modules must not exceed specific logical limits.
    • Context Distillation: AI instances reset, ensuring clarity with each phase.
    • Chess Logic: Treat constraints as fixed rules for unyielding accuracy.

This repository serves as a critical proof for AI researchers to challenge the prevailing “Context Window” dogma.

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