We recently completed validation of SIGMA Runtime v0.3.7 — a cognitive architecture for LLM identity stabilization. Across 550 cycles on GPT-5.2 (five runs × 110 cycles), the system maintained 100% persona coherence with an average 33% token reduction and 13% latency improvement.

The key finding: runtime parameters act as cognitive control levers, enabling dynamic trade-offs between semantic depth and efficiency.

Discussion welcome — especially from those working on long-horizon coherence, cognitive attractors, and multi-cycle LLM stability.