Coherence-Tolerant Systems A Structural Approach to Alignment in Human-Machine Interaction

This work introduces Coherence-Tolerant Systems (CTS) as a structural approach to maintaining alignment between intent, context, and output in human–machine interaction.

While contemporary systems have significantly improved response generation, they often fail to preserve coherence across interactions. This leads to the accumulation of subtle misalignments, where outputs remain locally correct but become inconsistent within the broader system.

CTS addresses this limitation by shifting the focus from output optimization to alignment preservation. It proposes a staged evaluation process that stabilizes intent, verifies contextual compatibility, and prioritizes minimal solutions before response generation. This approach reduces over-engineering, prevents silent drift, and maintains structural consistency over time.

Rather than replacing human thinking, CTS supports a collaborative interaction model in which systems assist exploration while preserving human decision authority. This enables a balance between machine-assisted capability and independent judgment.

The paper outlines the conceptual foundation, structural model, core properties, and implications of CTS as a design principle for future intelligent systems. It is presented as a foundational framework and does not prescribe specific implementation architectures.