GoKawiilLaminar launches flow-1, an RL-trained model to detect silent AI agent failures
YC S24 startup Laminar has released flow-1, a small open-source model fine-tuned and reinforcement-learned to analyze AI agent traces for hidden errors that don't surface as crashes or failed calls. The company says flow-1 matches the detection quality of GPT-6-sol on its own benchmark while costing 23 times less to run, making full-trace analysis of production agents economically feasible. The model operates within a harness called Signals, treating each agent trace like a codebase to inspect span by span.