Morph Reflexes – Multi-head classifiers for agent traces

Morph Reflexes is a project that introduces lightweight, multi-head classifiers to detect common behavioral failures in production AI agents—such as looping or reasoning leakage—by extracting semantic signals from agent traces. It is designed for engineers and teams deploying agents at scale who need a fast, cost-effective alternative to using expensive frontier models for turn-by-turn monitoring. The project is interesting because it offers a practical, scalable solution for real-time agent observability and safety without the latency or cost of large language model judges.