Phionyx: A Deterministic AI Runtime Architecture with Structured State Management and Pre-Response Governance

Short summary

Phionyx is a deterministic AI runtime architecture that treats LLM outputs as noisy sensor measurements rather than direct decisions, enforcing reproducible behavior through structured state vectors and a 46-block evaluation pipeline. It integrates pre-response safety control and a semantic time-based memory system with impact-weighted cache eviction. Experiments show ~31% computational overhead reduction vs post-hoc filtering and up to 24% improvement in high-value data retention vs LRU, though generalization to distributed deployments remains future work.

• •Treats LLM outputs as noisy sensor measurements with deterministic state evolution
• •Three-layer architecture: evaluation kernel, unified safety layer, semantic memory
• •31% overhead reduction vs post-hoc filtering; 24% better data retention vs LRU

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