How to use LangSmith to Debug and Monitor Your LLM Application
Learn how to use LangSmith for full-stack observability, tracing, and continuous evaluation of your AI systems.
Once you move an LLM application beyond a simple script, you need professional observability. LangSmith is a platform designed specifically for the unique challenges of debugging and monitoring non-deterministic AI systems.
Full Traceability of Every Request
LangSmith captures every step of your AI chain. You can see the raw prompt, the model's intermediate thoughts, the retrieved documents, and the final output in a single, visual timeline. This "X-ray" view of your application makes it trivial to identify why an agent got stuck in a loop or where a Rag system failed to find the right document.
Continuous Evaluation and Testing
The platform allows you to quickly turn production "failures" into new test cases. By building a comprehensive evaluation suite, you can quantitatively measure how every change to your prompt or model affects overall quality. This data-driven approach is the only way to ensure that your AI application is actually getting better as you iterate.