Gubernaut Cognitive Controller

Gubernaut: Deterministic homeostatic controller for affect-regulated LLM agents validated across four frontier model families

Researchers introduce the Gubernaut Cognitive Controller (GCC), a model-agnostic runtime layer that monitors numeric telemetry (intensity, valence, repetition) at a meta level to regulate LLM agent behavior under sustained pressure—addressing escalation, sycophancy, and perseveration without modifying model weights. The architecture uses a Nelson–Narens monitoring–control loop where the deterministic meta level ingests zero tokens, eliminating a class of prompt-injection attack vectors by construction. Evaluation uses a pre-registered generate-once/judge-many protocol across a 4×4 matrix of four frontier models (GPT-5.5, Claude Opus 4.8, Gemini 3.5 Flash, Grok 4.3) as both generators and judges, finding the regulated arm calmer in 13 of 16 cells at p<.05 and 15 of 16 by sign. The recovery signature—arousal integrating under attack then decaying on de-escalation—replicates across all four model families, suggesting a robust mechanism rather than a judge-style artifact.