Laminar's flow-1 finds hidden failures in agent traces at about $0.001 per trace

The RL-trained model treats a trace like a repo, grepping spans to catch quiet errors such as an agent marking work done while tests still fail, and on Laminar's own 523-trace benchmark it edges GPT-6 Sol on detection F1 (.835 vs .816) at 23x lower cost, though Claude Opus 5 still scores higher (.890). Laminar's observability platform is Apache 2.0 and self-hostable, and flow-1 runs in its Signals agent at $0.05/$0.30 per million input/output tokens (benchmark).