March 2026: LangChain Newsletter It feels like spring has sprung here, and so has a new NVIDIA integration, ticket sales for Interrupt 2026, and announcing LangSmith Fleet (formerly Agent Builder).
Evaluating Deep Agents: Our Learnings Over the past month at LangChain, we shipped four applications on top of the Deep Agents harness: * DeepAgents CLI: a coding agent * LangSmith Assist: an
Introducing End-to-End OpenTelemetry Support in LangSmith LangSmith now provides end-to-end OpenTelemetry (OTel) support for applications built on LangChain and/or LangGraph.
LangChain State of AI 2024 Report Dive into LangSmith product usage patterns that show how the AI ecosystem and the way people are building LLM apps is evolving.
Introducing OpenTelemetry support for LangSmith LangSmith now supports OpenTelemetry for distributed tracing and observability.
Easier evaluations with LangSmith SDK v0.2 We've released a v0.2 of the LangSmith SDKs with various evaluations and performance improvements.
LangGraph Platform in beta: New deployment options for scalable agent infrastructure We've rebranded our service for deploying and scaling LangGraph apps as LangGraph Platform. Learn about the multiple deployment options and what LangGraph Platform entails.
Few-shot prompting to improve tool-calling performance We ran a few experiments, which show how few-shot prompting can significantly enhance model accuracy - especially for complex tasks. Read on for how we did it (and the results).
Improving core tool interfaces and docs in LangChain See our latest improvements to our core tool interfaces that make it turn any code into a tool, handle diverse inputs, enrich tool outputs, and handle tool errors effectively.
Announcing LangGraph v0.1 & LangGraph Cloud: Running agents at scale, reliably Our new infrastructure for running agents at scale, LangGraph Cloud, is available in beta. We also have a new stable release of LangGraph.
Aligning LLM-as-a-Judge with Human Preferences Deep dive into self-improving evaluators in LangSmith, motivated by the rise of LLM-as-a-Judge evaluators plus research on few-shot learning and aligning human preferences.
How Factory used LangSmith to automate their feedback loop and improve iteration speed by 2x How Factory AI uses LangSmith to debug issues and close the product feedback loop, resulting in a 2x improvement in iteration speed.
