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Launch HN: Laminar (YC S24) – RL-trained model that finds errors in agent traces
Laminar (YC S24) released flow-1, an RL-trained model that analyzes agent traces to detect errors, claiming GPT-6-sol-level detection quality at 23x lower cost on its own benchmark. It runs in a harness called Signals, accepts general prompts, returns findings as JSON with user-defined schemas, and clusters recurring events so developers can build eval datasets and fix failures. Laminar is Apache 2.0 and self-hostable, with revenue from a managed cloud.
Read the full story on news.ycombinator.com
What to doDevelopers building agents who want full-trace error analysis without sampling can try flow-1 via Laminar or self-host the open-source platform.
- Source
- news.ycombinator.com