LangChain Blog

Agent Protocol: Interoperability for LLM agents

LangGraph is a multi-agent framework. This means not only interacting with other LangGraph agents, but all other types of agents as well, regardless of how

3 min read

Featured

Launching Long-Term Memory Support in LangGraph

2 min read

Announcing LangChain v0.3

2 min read

How Podium optimized agent behavior and reduced engineering intervention by 90% with LangSmith

Case Studies 5 min read

LangGraph v0.2: Increased customization with new checkpointer libraries

4 min read

LangSmith: Redesigned product homepage and Resource Tags for better organization

LangSmith's homepage is now organized into Observability, Evaluation, and Prompt Engineering. Learn why we organized the homepage like this. Plus, see our latest Resource Tags updates.

4 min read

How Dun & Bradstreet’s ChatD&B™ uses LangChain and LangSmith to deliver trusted, data-driven AI insights

Learn how Dun & Bradstreet, a leading financial data analytics company, empowers global clients with business data — from credit risk to ownership structures — to make better decisions using their AI assistant, Chat D&B. See how LangChain and LangSmith have helped Dun & Bradstreet on their journey.

Case Studies 4 min read

Promptim: an experimental library for prompt optimization

Promptim is an experimental prompt optimization library to help you systematically improve your AI systems. Promptim automates the process of improving prompts on specific tasks.

3 min read

Introducing Prompt Canvas: a Novel UX for Developing Prompts

Use Prompt Canvas in LangSmith to collaborate with an AI agent to build and optimize your prompts.

3 min read

Composio’s SWE agent advances open-source on SweBench with a 48.6% score using LangGraph and LangSmith

We are excited to launch SWE-Kit, an open-source headless IDE with AI-native coding toolkits for AI agents, as part of Composio's agent tooling

6 min read

SCIPE - Systematic Chain Improvement and Problem Evaluation

Editor's Note: we're EXTREMELY excited to highlight this research from Ankush Garg and Shreya Shankar from Berkeley. At LangChain, two of

6 min read

How Chaos Labs built a multi-agent system for resolution in prediction markets

Editor's Note: one of the most common use cases we've seen for LangGraph is complex research agents. This guest blog post

4 min read

LangGraph Platform: 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.

By LangChain 4 min read

Communication is all you need

“What we’ve got here is failure to communicate” - Cool Hand Luke (1967) Communication is the hardest part of life. It’s also the

In the Loop 7 min read

LangChain's Second Birthday

Reflections on how LangChain has evolved — including our products, ecosystem, and community — over the past two years, and where we're headed next.

Harrison Chase 6 min read

Memory for agents

At Sequoia’s AI Ascent conference in March, I talked about three limitations for agents: planning, UX, and memory. Check out that talk here. In

In the Loop 5 min read

How Rexera’s AI agents drive quality control with LangGraph

See how Rexera migrated to LangGraph to create a robust quality control agent for real estate workflows, significantly improving their LLM response accuracy.

Case Studies 4 min read