Event arc
Effective evaluation and monitoring improve AI agent reliability and deployment success.
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AI BriefWire / Thread
Evaluating Deep Agents using LangSmith on AWS
AWS published a guide on evaluating deep AI agents using LangSmith and Amazon Bedrock. The guide covers five evaluation patterns, offline testing with pytest, and online monitoring setup. This helps developers manage AI agent performance from development to production.
AWS Machine Learning Blog
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Companies involved
Amazon (AMZN)
Market lens
Better evaluation tools reduce risks and enhance AI product quality in production.
Operator take
Teams building AI agents should adopt these evaluation and monitoring practices.
Source mix
Sources in this thread (1): AWS Machine Learning Blog
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Latest signal
Evaluating Deep Agents using LangSmith on AWS
AWS published a guide on evaluating deep AI agents using LangSmith and Amazon Bedrock. The guide covers five evaluation patterns, offline testing with pytest, and online monitoring setup. This helps developers manage AI agent performance from development to production.
↓ -1.15%AMZN
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Evaluating Deep Agents using LangSmith on AWS
AWS published a guide on evaluating deep AI agents using LangSmith and Amazon Bedrock. The guide covers five evaluation patterns, offline testing with pytest, and online monitoring setup. This helps developers manage AI agent performance from development to production.
↓ -1.15%AMZN