🌟Our latest LangChain Academy course – Deep Agents with LangGraph – is now live!🌟 Many agents today follow the same simple pattern: run in a loop, call tools. That architecture works well enough, but it breaks down as tasks get more complex. Today, companies of all sizes –

🎨 AI-Powered Canvas Template Brandon from CopilotKit released a production template for AI canvas apps. Built with LangGraph for agent coordination, it delivers real-time UI-AI synchronization through a Python-Next.js stack. Watch the walkthrough: https://t.co/W0PNbDz0QF

🤖 🧠 Deep Agents Evolution A breakthrough in AI architecture enabling agents to scale from 15 to 500+ steps through advanced planning and memory systems, revolutionizing how AI handles complex tasks. Learn more about this evolution 🔍 https://t.co/BdCRwgl0di

📚🤖 Article Explainer An AI document analysis tool that breaks down complex technical articles using LangGraph's Swarm Architecture. The system uses multiple agents to provide interactive explanations and insights through natural language queries. Check it out on GitHub 🔍

📚🔍 Event Deep Research An AI system that transforms historical research into structured timelines, automatically extracting and organizing biographical data from multiple sources into chronological JSON format. Check out the project 🎯 https://t.co/hjZ4DbxS3r

🧠 LangGraph × cognee Integration cognee brings persistent memory to LangGraph agents, letting AI applications maintain context across sessions while seamlessly working with existing LangGraph features. Check out how to add memory to your agents 🔗 https://t.co/Om6FZE2gRR

Launch Week is right around the corner — and we're kicking it off in person! We'll be hosting meetups in San Francisco, Boston, and NYC to celebrate LangChain's 3rd birthday and share what's coming next during Launch Week. Come hang with the team, connect with our amazing

Sorry @AravSrinivas We just open sourced $200 @perplexity_ai email assistant - Personal AI assistant that sits in your inbox - Executes actions on 500+ apps like Gmail, Slack, Notion - Works in the background without interruptions built with @LangChainAI and @composiohq 's

In this blog piece, you’ll learn why and how we built LangGraph for production agents. Building upon feedback from the super popular LangChain framework, we aimed to find the right abstraction for AI agents, and decided that was little to no abstraction at all. Instead, we

@LangChainAI kept their early tech stack really simple, simple Python and Postgres, so they could maximize focus on the customer need. Then once things really started working, it becomes obvious which parts of the architecture need to change:

Learn how to use LangSmith to debug your AI applications. 🛠️ In this video, we’ll show you how  "Studio," our IDE for building agents, works, and how you can use it with any LangGraph agent you’ve built. You’ll also get everything you need to get started with Studio.

We're hosting an intimate evening in Boston to celebrate LangChain's 3rd birthday and share our biggest product releases of the year. If you're an AI builder and want to connect with the community (plus get an early look at what we've been working on), join us. 👉 RSVP:

🔍Unlike traditional logs (or traces), which can be hard to interpret for LLM applications, LangSmith makes it easy to explore and debug with an intuitive, purpose-built UX. 🏃Learn about the different types of runs you can create while tracing in LangSmith—and how they help you

Just added a long awaited guardrails page to the @LangChainAI docs. Get started quickly with builtin guardrails: 🛡️ PII redaction 🫅 Human in the loop Plus, build custom guardrails that hook into your agent loop (can run before or after your model). https://t.co/mJOoTHeTOp

Agents don’t just chat — they act by fetching data, sending messages, calling APIs, and updating records, which makes securing them a whole new challenge. Our latest blog post breaks down how to implement authentication and authorization for agents. 🔒In this blog post, learn

🤖 🕸️ ScrapeCraft: AI-Powered Scraping ScrapeCraft uses LangGraph to combine AI assistance with powerful web scraping. Features include bulk URL scraping, real-time data streaming, and AI-powered pipeline generation. Explore the project on GitHub! 🚀 https://t.co/FXkM2RTygd

🤖 Advanced Stock Research Agent A multi-agent system built with LangChain's DeepAgents that delivers professional stock analysis by combining real-time data, technical indicators, and financial examination. Check it out here 🔍 https://t.co/d8B5TJIASx

🤖 💻 LangCode CLI A powerful dev tool that unifies AI models for smart coding. Built with LangChain, it offers automated tasks and safe code changes through intelligent model routing and diff previews. Check it out! 🚀 https://t.co/TMBNWchi9T

✈️ 🤖 AI Travel Agent An intelligent travel assistant that integrates real-time weather, search, and travel information. Leveraging multiple APIs, it streamlines everything from weather updates to currency conversion. Explore the guide on GitHub https://t.co/JlSbRM1HoY

🌐⚡ BLAST: AI Web Browser Engine A high-performance serving engine that adds web browsing to AI applications. BLAST provides an OpenAI-compatible interface with automatic parallelization, intelligent caching, and real-time streaming support. Explore this open-source project 👉

🔍🤖 GraphQA Transform graph analysis into natural conversations with this NetworkX and LangChain-powered framework. Ask questions in plain English and let GraphQA select and execute the right algorithms, handling graphs up to 100K+ nodes. Check it out 👉