LangSmith

LangSmith is LangChain's observability platform for AI agents and language models. It shows exactly what your agents do, step by step, so you can spot where they go wrong. You can trace any agent stack with SDKs for Python, TypeScript, Go, and Java. Beyond tracing, it scores agent performance and helps you ship agents to production. Tools include an LLM gateway, safe sandboxes, no-code agent builders, and deployment features. The free Developer tier fits solo projects, side builds, and first experiments.

Key Features

1. Step-by-Step Tracing

See every action your agent takes, with inputs, outputs, and timing for each single step.

2. Evaluation

Score agent runs against your own criteria and track quality trends over weeks and months.

3. Any Agent Stack

Trace agents built with any framework, not just LangChain, using the open Python, TypeScript, Go, or Java SDKs.

4. LLM Gateway

Call models across providers through one LangSmith key with spend limits and policies enforced centrally.

5. Safe Sandboxes

Run agent-generated code in isolated secure sandboxes so experiments cannot harm your production systems at all.

6. Deployment Tools

Ship and scale agents in production with hosting, versioning, and monitoring all built in natively.

Frequently Asked Questions (FAQ)

What is LangSmith for?

Understanding, testing, and improving AI agents before and after they reach production.

Do I need LangChain to use it?

No. The SDKs trace agents built with any framework or none at all.

Is there a free plan?

Yes. The Developer tier is free, with one seat and 5,000 traces a month.

What is LangSmith Engine?

An in-platform agent that studies production traces, finds recurring failures, and drafts fixes for your review.

How does evaluation work?

You define scoring criteria, run them against traces, and watch quality over time.

Conclusion

LangSmith turns agent debugging from guesswork into evidence. When an agent fails, the trace shows you the exact step and the code that caused it. Start with the free Developer tier on a side project, add evaluations early, and scale to Plus when your team ships. Good observability is what separates demos from products that last.