StatePlane: A Cognitive State Plane for Long-Horizon AI Systems Under Bounded Context

Researchers introduce StatePlane, a model-agnostic cognitive state management system that enables AI systems to maintain coherent reasoning over long interaction horizons without expanding context windows or retraining models. The system uses episodic, semantic, and procedural memory mechanisms inspired by cognitive psychology to overcome current limitations in large language models.

• →StatePlane addresses fundamental context window limitations in both large and small language models without requiring model retraining.
• →The system implements cognitive psychology principles including episodic segmentation, selective encoding, and adaptive forgetting.
• →It provides security mechanisms including write-path anti-poisoning and enterprise integration pathways.
• →The approach demonstrates that long-horizon AI intelligence can be achieved through better memory management rather than larger models.
• →Six domain-specific benchmarks were developed to evaluate the framework's effectiveness across different use cases.