Context Rot
Context rot is the gradual degradation of an AI system's working context over a long session, as earlier information is displaced, summarised, or silently dropped. The model does not report a gap; it fills it fluently, so the output stays confident while the grounding decays. It is not a context window size problem. Peer-reviewed research shows input length alone degrades performance even with perfect retrieval, so a larger window delays it rather than preventing it.
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On The AI Brain
Research
Context Window Does Not Equal Context
The manifesto. Why 95% of enterprise AI pilots produce no measurable return, and why the answer is not a bigger context window but a missing layer.
Research
When Context Collapses: What a Geopolitical Crisis Revealed About AI's *Missing Layer*
During the Iran-US escalation cycle, we ran frontier AI models against the same questions under different context architectures. Five failure modes emerged that no model upgrade will fix. They are pr…