Prompt engineering tells the model what to do.
Context engineering determines what it knows. LangSmith is the best tool for agentic context engineering—giving you full visibility into how context is constructed, retrieved, and consumed so your agents reason with the right information every time.
Try LangSmith free. No credit card required.
See every document retrieved, every tool result injected, and every prompt template rendered. Understand the exact context your AI agent received before each decision—the foundation of good context engineering.
Run offline evals to compare context engine configurations: RAG strategies, summarization approaches, injection patterns. Follow context engineering best practices by measuring what actually improves agent accuracy.
Track context quality metrics in live deployments. Surface regressions early, understand how context patterns shift over time, and apply agentic context engineering improvements continuously.
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Teams trust LangSmith to engineer and optimize the context that powers their most important agent applications
The best tool for agentic context engineering—inspect, test, and optimize how context flows through your LangChain, LangGraph, and custom AI agent systems
Trace every prompt, retrieved document, tool output, and system message that makes it into the context window. Understand what your agent actually saw before each decision—not just what you intended to send. The best context engineering practices start with full visibility.
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Built for Enterprise
LangSmith meets the demanding security, performance, and collaboration requirements of large organizations building AI applications at scale.
Role-based access control with org-level permissions and project isolation to meet your security and compliance requirements.
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Self-hosting options to maintain full control over your AI data and meet strict compliance requirements.
Prompt engineering changes instructions. Context engineering changes what the model knows. LangSmith is purpose-built for agentic context engineering—trace every document, tool result, and message that shapes each decision.
Benchmark context engineering techniques against each other. Compare RAG strategies, summarization approaches, and context engine configurations to find what actually improves AI agent output quality.
Native integration with LangChain and LangGraph means context engineering for agents is first-class. Trace context pipelines, evaluate retrieval quality, and follow context engineering best practices without any extra configuration.
"Working with LangSmith on the Elastic AI Assistant had a significant positive impact on the overall pace and quality of our development and shipping experience. We couldn't have delivered the product experience our customers now have without LangSmith—and we couldn't have done it at the same pace without it."
"What we really needed was a more structured way to test new approaches, something better than just shipping and seeing what happened. LangSmith gave us a more scientific, structured way to understand what was actually working, whether that meant running pairwise evaluations or digging into why accuracy jumped from 70% to 80%. Our engineers especially love the intuitive debugging experience, it's saved us a lot of time."
See how LangSmith applies context engineering best practices to your LangChain and LangGraph agents—so they reason better, hallucinate less, and stay reliable in production.