LangSmith
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An observability and evaluation platform for LLM and agent applications — tracing, datasets, automated evals, and production monitoring in one place.
Overview
LangSmith is where you find out whether your agent actually works. It captures full execution traces, lets you build evaluation datasets from real traffic, run automated evals in CI, and monitor quality and cost in production. For enterprises, the eval and monitoring side is the point: shipping an agent without an eval harness is how you end up in the 95% of pilots that stall. Framework-agnostic, though it pairs most tightly with LangChain and LangGraph.
Pros & Cons
Pros
- End-to-end tracing for complex agent runs
- Datasets and automated evals in CI
- Production monitoring for quality and cost
- Framework-agnostic
Cons
- Most seamless within the LangChain ecosystem
- Trace volume can drive cost at scale
- Eval design is still real work
Workflows that use LangSmith
Get a new AI workflow each week — many feature LangSmith and other tools in this category.