📣 Join us in San Francisco for LangChain Academy Live! 📣. Join LangChain Academy Instructor Lance Martin and 30 fellow learners for an in-person workshop at LangChain’s San Francisco office on August 19th at 4pm. We’ll walk through the Ambient Agents course, build an email

RT @GregKamradt: How do you build an AI memory system that is used by 10,000+ developers? William will tell you. He built @LangChainAI's La….

RT @marlene_zw: Getting ready to help host this months @LangChainAI London meetup 🇬🇧✨ . Clippy + LC Parrot 🦜will be around! Will make this….

RT @zhanghaili0610: 🦜🕸️ Open Deep Research V2：新架构！上下文工程最新实践 . 在 Open Deep Research V2 中，LangChain 团队进行了架构升级，优化了智能工作流和多智能体架构。新版本强调上下文工程的应用，提….

RT @chester_curme: 🛠️ Bedrock AgentCore tools in LangChain. It's now easy to use Bedrock AgentCore built-in tools with LangGraph agents. T….

🤖 🛡️ Cleanlab Trust Scoring. Cleanlab's powerful trust scoring system prevents AI hallucinations in customer support, seamlessly integrating with LangGraph to detect and block problematic responses before reaching users. Explore the technical implementation here:

Join @Redisinc and @LangChainAI on July 23 for a webinar to learn how LangGraph + Redis make it easy to build AI agents with real memory. In the live webinar, you'll get demos, performance tips, and hear from the engineers behind the integration. 👉 RSVP here:

🤖 Join us for an AI Agents Meetup on context engineering for agents!. LangChain's @RLanceMartin will break down common strategies for context engineering, review how some popular agents implement these approaches, and explain how LangGraph is designed to support them. RSVP:

✍️ Learn more: 👉 Go directly to Marketplace:

🚀 LangSmith and LangGraph Platform are now available on AWS Marketplace!. You can now self-host:. • LangGraph Platform – Deploy and manage long-running, stateful agents with 1-click deploys, custom API endpoints, and built-in memory. • LangSmith – The observability & evals

Open Deep Research is here 🔍 We've open sourced one of the most powerful agent use cases. Built on LangGraph, Open Deep Research:. • Uses a supervisor architecture to coordinate research sub-agents.• Supports your own LLMs, tools, and MCP servers.• Produces high-quality

📣 Join us in San Francisco for LangChain Academy Live! 📣 . Join LangChain Academy Instructor Lance Martin and fellow learners for an in-person workshop on August 19th at 4pm. We’ll walk through the Ambient Agents course, build an email agent together, answer your questions

Attending #AWSSummitNYC? Join @LangChainAI, @Redis, @Tavily and @thekonginc for a post-Summit happy hour just steps from the Javits Center. Connect with AI and cloud leaders and explore how Kong powers the API layer of the emerging AI Gateway stack—alongside Redis’ real-time.

We're hosting an Office Hours event at our San Francisco office this Wednesday. Join us for breakfast and hang out with our team for a couple of hours. Bring your questions, share your projects, and we'd love to hear your feedback! . RSVP here:

🔍🗃️ GraphRAG Chatbot Tutorial. Build a powerful GenAI chatbot combining vector search and graph knowledge with SurrealDB and LangChain. This health symptoms demo shows how GraphRAG delivers more contextual AI responses. Learn to build your own GraphRAG chatbot 🚀

🤖💼 AI Headhunter Agent. Build a powerful LinkedIn recruitment agent that automates candidate sourcing using LangGraph. Features state management, parallel processing, and real-time updates through Davia integration. Watch the full tutorial here 📺

🔄 🤖 Pipeline of Agents Pattern. A modular pattern for AI agent workflows, showcasing sequential agent chaining and state isolation through a cybersecurity implementation. Built for production with error handling and integrated tooling. Learn more here 📚

RT @masondrxy: 💡 New in @LangChainAI @GroqInc: reasoning output, effort, and flex processing (service tier) support!. These improvements al….

Read the full guide 👉

Most teams want to build agents— but it's not always clear where to start. We created a 6-step framework to help you go from idea → MVP → production. In our latest blog post, learn how to build agents grounded in real use cases, tested against real examples, and shaped by