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LangChain released a tracing plugin that converts every Cursor AI agent session into a structured trace in LangSmith, including model runs, tool calls, and nested subagent work, part of a series comparing coding-agent traces.
LangChain announces a summer AMA series on the agent development lifecycle using LangSmith, covering building, deploying, monitoring, improving, and governing agents.
The developer created a self-hosted visual builder for LangChain/LangGraph agents and is requesting feedback from the community.
LangChain introduces IssueBench, a detailed evaluation suite for Engine, a continual learning agent in LangSmith that automatically improves agents based on traces.
LangChain is hosting an event today at 11am PT / 2pm ET to teach how to safely give agents their own computer.
LangChain is hosting a Summer AMA Series with practical walkthroughs and live Q&A about LangSmith.
LangChain released a tracing plugin for Codex sessions in LangSmith, enabling detailed traces of every turn including tool calls and token usage, configurable with just two blocks and a flag.
LangChain shows a 7-minute tutorial by Partner Engineer Srimanth Tangedipalli on running Deep Agents Code inside a governed NemoClaw OpenShell Sandbox with NVIDIA Nemotron 3 Ultra via Baseten.
LangChain launches OpenWiki Brains, a framework for proactive memory for AI agents that automatically builds and updates wikis from connected sources like Gmail, Notion, and git repos.
LangSmith highlights Finch Legal, a startup using AI agents for pre-litigation in personal injury law, achieving 10x growth and utilizing LangSmith for production observability.
LangChain shares a customer story where PodiumHQ's Walker Ward discusses using LangGraph and LangSmith to move AI agents from prototype to production.
Read-only agents are easier to test than write-access agents; production data write access remains an unsolved eval problem for many teams.
NVIDIA Nemotron 3 Ultra achieves benchmark-leading performance with LangChain Deep Agents harness, offering higher accuracy at lower cost than closed models without retraining.
Schneider Electric uses LangChain's LangSmith to run over 60 production AI agents across 100+ countries, serving 160,000 employees with their AI Assistant, demonstrating enterprise-scale LLMOps.
LangChain Academy launches a new course titled 'Introduction to Deep Agents', teaching what a harness is and the four core capabilities of a harness, with hands-on building using LangChain and LangSmith.
LangChain is hosting a technical webinar on July 15 about building a secure execution environment for AI agents, covering security, isolation, and observability.
At the aiDotEngineer World's Fair, Vtrivedy10 discussed how data mining from traces is a high-leverage practice for understanding AI agents, curating data at scale, and running improvement loops.
LangSmith Evaluation helps improve AI agent quality by evaluating performance with real production data.
LangChain announces new stops for its Interrupt conference in NYC (Sept 24) and London (Oct 13), focusing on AI agents and community building.
A guide on running agent evaluations using Harbor framework and LangSmith sandboxes with full trace support.