Model updates

Official news, first rumor reports and substantive progress. Each entry keeps the information published at that time.

• Laminar releases flow-1, an RL-trained model for finding failures in agent traces

  Laminar released flow-1, a model for understanding agent traces, trained with reinforcement learning to identify hard-to-spot failures and explain why they happened. On Laminar's benchmark, it matches GPT-6-sol in detection quality while being 23x cheaper, per the company. The goal is to make it affordable to investigate all production traces continuously instead of sampling. flow-1 runs inside the company's Signals agent, which treats the trace as a repo and each span as a file.

  OfficialOfficial updateOct 2Source: LaminarPart of flow-1

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