Visualizing the Nomos Dual-Core Architecture. Stochastic LLM vector particles (Yang / Intent Core) explore speculative solution manifolds while deterministic Go AST gravity wells (Yin / Substrate Core) confine drift within mathematical invariants, preventing chaotic hallucination.
The compiled Go engine (Substrate Core / Yin) runs the immutable physical totem, enforcing mathematical AST invariants, Phase Discipline, and transactional 2PC state. Above it, LLM cognitive reasoning (Intent Core / Yang) explores speculative candidate solutions within strict bounding potentials.
Unconstrained stochastic models exhibit Brownian drift: expanding token entropy, hallucinated cyclic imports, and multi-turn complexity spirals. By applying inverse potential wells at the AST boundary, Nomos dampens chaotic oscillations into deterministic attractor states.
Autonomous AI engineering requires continuous empirical proof. Explore benchmark telemetry tracking multi-agent sprint convergence, token burn velocity, and zero-defect machine verification under high-density workload conditions.