“Recommendation: Start with LangSmith alone”
“Particularly strong at agent tracing, debugging, dataset-based experiments, trajectory inspection, human annotation, and production monitoring.”
“LangSmith fully supports evaluating agents against datasets, tracking dataset versions, and comparing different versions of an agent.”
“In fact, LangSmith is designed to support the full agent evaluation lifecycle, from offline regression testing to production monitoring.”
“Dataset and experiment management.”
“Version-to-version regression testing.”
“Custom and LLM-as-judge evaluators.”
“Production evaluation.”
“Particularly strong at evaluation workflows, reusable scorers, versioned datasets, experiment comparisons, and CI quality gates.”
“Particularly strong at evaluation workflows, reusable scorers, versioned datasets, experiment comparisons, and CI quality gates.”
“Code-based and LLM-based scoring.”
“Step-level agent evaluation.”
“Multiple trials to measure nondeterminism.”
“Dataset and scorer versioning.”
“Experiment comparisons and CI/CD release gates.”
“Using both introduces additional operational overhead:”