LangChain Blog
Articles about LangChain Blog
How to build great out-of-the-box user experiences with Managed Deep Agents
Managed Deep Agents includes a new API for managing reactions for your distributed agents, and a system to dynamically assign emoji responses with your instrument of choice. Learn more.
How Snyk Turned an Internal Support Agent into a Customer Feature
Discover how Snyk transformed an internal support agent into Snyk Assist, a customer-facing AI feature powered by LangChain, LangGraph, and LangSmith.
Agents that can pay: building Restock with Stripe’s Link and Managed Deep Agents
Build an agent that pays for real purchases. Restock runs in Slack on Managed Deep Agents and pays with Stripe's Link over the Machine Payments Protocol.
Revamping Skills in Deep Agents
Deep Agents now lets you bind tools to skills, pin skills at runtime, and reload skills mid-thread, so agents with expansive skill repositories stay context-efficient and effective.
What’s New in Managed Deep Agents: schedules, per-run configuration, and Slack reactions
LangChain just released new capabilities in Managed Deep Agents. Agents can now schedule follow-ups, reconfigure themselves on every run, and react to Slack messages.
How to Build a Model Router in the Harness
How we built a model router into Open SWE's harness that cut median cost per coding task by 64% with no measurable drop in quality, and how to build your own.