Laminar's RL-Trained Error Detector: How Reinforcement Learning Finds Bugs in Agent Traces Without Human Labels
Agent observability has a labeling problem. When an agent clicks the wrong button or cites the wrong document, every API call returns 200. The trace looks clean. The error is semantic, not syntactic. You need a human to read the entire execution log and decide whether the agent actually did what it…
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- 2026-10-23 00:07 · DEV Community — Machine Learning
Laminar's RL-Trained Error Detector: How Reinforcement Learning Finds Bugs in Agent Traces Without Human Labels