Evaluating Deep Agents using LangSmith on AWS
LangSmith on AWS provides five evaluation patterns for deep agents in production
“Validating AI agent behavior before production is one of the hardest problems in applied AI.”
AWS and LangChain published a joint guide combining their learnings on evaluating deep (multi-step) agents using LangSmith on AWS with Amazon Bedrock. The post introduces a structured vocabulary for agent evals—tasks, trials, graders, transcripts, outcomes—and walks through a text-to-SQL agent as a practical example. It matters because reliable agent evaluation frameworks are a critical unsolved gap between prototyping and production AI deployments.