Launch HN: Laminar (YC S24) – We trained a model to catch silent agent failures
AI summary
Editorial policyLaminar released flow-1, a model trained with reinforcement learning to detect errors in AI agent traces, achieving detection quality comparable to GPT-6-sol at 23% of the cost.
Key points
- •Laminar, which has been building open-source observability tools for AI agents since 2024, released flow-1, a model trained using reinforcement learning.
- •On the company's benchmark, flow-1 maintains error detection quality comparable to GPT-6-sol while reducing costs to one twenty-third.
- •This cost reduction makes it possible to analyze all production agent traces without sampling.