NeoHorse-1: Towards Recursive Self-Improvement via Agentic Post-Training with Routing Harness

Researchers introduced NeoHorse-1, a family of agent-native models designed for recursive self-improvement through agentic post-training with a routing harness. The system observes its own capabilities and converts that evidence into subsequent learning rounds, marking a step toward autonomous AI improvement.

Recursive self-improvement RSI requires a concrete mechanism through which an AI system observes its capabilities and converts that evidence into the next round of learning. We present NeoHorse-1, a family of agent-native models developed to explore this path through agentic post-training. Our sys