LangSmith

LangSmith is LangChain's agent engineering platform for observing, evaluating, testing, deploying, and improving LLM applications and AI agents. It helps teams understand what agents actually did by capturing traces, monitoring quality, running evaluations, and turning production behavior into actionable debugging data. The product is framework-agnostic and can be used with LangChain, LangGraph, or other agent stacks. Its core value is visibility: teams can inspect runs, compare experiments, monitor errors and latency, track costs, and build evaluation loops before and after shipping changes. LangSmith is especially useful for production AI teams because traces are often the only reliable record of what an agent saw, decided, and executed. The platform combines observability, evaluation, deployment, Fleet, Engine, and enterprise deployment options for teams that need reliability beyond prototype notebooks. For FutureStack, LangSmith belongs in Developer Tools because serious AI products need more than model access. It is best for engineering and AI teams that want to debug agents, run evals, monitor quality, and deploy workflows with measurable feedback loops.