TokenRhythm releases NeoHorse-1 models trained on agent execution traces

A post says TokenRhythm has released NeoHorse-1, a model family trained further on records of agents carrying out tasks. It describes a loop in which TokenRhythm’s OpenSquilla Harness captures model-routing decisions, tool calls, failures, recoveries and outcomes. Those records feed training, and the updated model returns to OpenSquilla to generate the next round. The author argues that tool use alone does not improve AI: execution experience needs to be captured, evaluated and turned into useful training data.