LangChain shares how Clay scales agent evals to 300M+ runs per month
LangChain · x · 2026-08-29
LangChain discusses how Clay achieved scaling agent evaluations to over 300 million runs per month. Key topics include their four-quadrant eval framework, the challenges of closing the production-to-eval loop, and how data lakes and long context capabilities have transformed what agents can do with data. This case study offers engineering insights for large-scale agent evaluation.
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