🤖🎓 Build AI Agents with LangGraph. Learn to build a startup intelligence agent in this video guide, showcasing LangGraph's stateful workflows with planning capabilities and SingleStore integration for vector storage. Watch the tutorial:

Free Complete course to learn to build AI Agents using LangGraph. Link in comment.

Neo4j + LangGraph is a deadly combination for building LLM assistants. Knowledge Graphs + Workflow orchestration = Zero hallucination.

Introduction to LangGraph in today’s class 🙌 . 🚀 It gives devs full control to design workflows. But the industry is rapidly moving toward Agent SDKs — and so are we. 😎

🔖If you’re building AI systems in 2025,there are only two tools worth learning: LangGraph and n8n⭕. 🧩The choice you make here will define how far you can actually scale. ✅Here’s everything you need to know👇.Like.RT♻️.Reply"AI" i'll send your DM fully guide🎯.Following me👤

𝐈𝐧𝐭𝐫𝐨 𝐭𝐨 𝐀𝐈 𝐀𝐠𝐞𝐧𝐭𝐬. A useful guide for those navigating the AI agent ecosystem, made by @eli_discovers🪁. The Agent ecosystem can feel like alphabet soup (RAG, MCP, A2A, AG-UI, LangGraph, Tavily…). So Eli, CopilotKit’s newest member, put together this guide for

📚🔍 Academic Deep Search Assistant. A powerful research assistant that automatically discovers and analyzes academic papers, generating comprehensive reports. Built with LangGraph to transform literature review workflows. Check out this game-changing research tool 📖

🤖📄 Just-RAG. An intelligent PDF conversation system that combines LangGraph's agentic workflows with Qdrant's vector search capabilities for enhanced document processing. Check out the implementation ⭐.

AI SDK over LangGraph.Reality✔️

Day6 starting with LangGraph. what are the use cases of it?.nodes = async Fns.n8n = UI of LangGraph. why people are moving from this to @OpenAI ?.where @claudeai , @GeminiApp is. Thanks to teachers like @Hiteshdotcom , @piyushgarg_dev and TAs like @nirudhuuu , @Aasuyadavv

📚 Thrilled to announce my new book "LangGraph in Action" is finally published!. After 8 months of work, this guide to building advanced AI agent systems is ready to help developers embrace the Agent era. From theory to practice, it covers everything you need to get started! 🦜

My dead-simple AI data science stack:. 1. Python ($0).2. Pandas ($0).3. Scikit Learn ($0).4. LangChain ($0).5. LangGraph ($0).6. OpenAI API ($1/month). You can grow into a $200,000 career by spending less than $12 this year.

Day 6 – GenAI with JavaScript 🚀.Learned about LangGraph and Langsmith . AI sdk's are bettern than the langraph and all. Loving this journey with @Hiteshdotcom & @piyushgarg_dev @ChaiCodeHQ , @nirudhuuu

Ever feel like staying updated is just scrolling through noise?. I’ve been experimenting with a local workflow I built with LangGraph to follow AI, Claude, LangGraph, cybersecurity, etc. It aims to give a curated set of insights and summaries, no hopping between a dozen sites.

🚨 NEW WORKSHOP: I'm sharing one of my best AI Projects for FREE: . How I built an AI Customer Segmentation Agent with Python:. - Scikit Learn.- K-Means.- LangChain.- LangGraph.- OpenAI. 👉Register here (500 seats):

🏗️Implementing deepagents: a technical walkthrough. A deep dive into the source code of the `deepagents` package:.- How to implement sub agents (including custom sub agents).- How to use LangGraph state as a virtual file system. Video:

#Easy同学正在独立开发 这个 LangGraph 太超前了，我一直以为它能用，今天想用时看了下，才发现它没有实现就发布了。😂

Day 6 – GenAI with JavaScript 🚀.Explored LangGraph → build AI workflows with nodes & edges. n8n? Just the UI of LangGraph 👀.Peeked into OpenAI Agent SDK → adoption is everywhere ⚡. @Hiteshdotcom @piyushgarg_dev @ChaiCodeHQ @nirudhuuu.#GenAI #AI

📚 🛠️ Agent Reliability. A practical guide to help you catch hallucainations, verify groundedness, and monitor tool usage for LangChain/LangGraph applications:.