Send API — Dynamic Fan-Out (Map-Reduce) in LangGraph 🤖

Welcome to the LangGraph Series! 🌙 In this session, we’re exploring the Send API in LangGraph — a powerful feature for building dynamic fan‑out workflows and Map‑Reduce style AI pipelines. 🤖⚙️ If you want your AI workflow to dynamically create multiple parallel tasks, process them independently, and then combine the results, the Send API is a must‑learn concept. By the end of this lesson, you’ll understand: ✅ What the Send API is in LangGraph ✅ How dynamic fan‑out works in AI workflows ✅ How to build Map‑Reduce patterns using LangGraph ✅ How to send work dynamically to multiple graph nodes ✅ How to process multiple tasks in parallel ✅ How to aggregate and reduce results back into final output ✅ Real‑world use cases like summarization, research, extraction, and batch processing With hands‑on examples and clear explanations, you’ll gain the confidence to build scalable, parallel, and production‑ready AI workflows using LangGraph Send API. 🚀 💬 Don’t forget to Like, Subscribe, and Comment what you learned today — your support keeps these coding lessons going strong! ✨ Before you sleep, make sure you’ve learned something new. ✨ #LangGraph #AIAgents #SendAPI #MapReduce #LLM #LangChain #ArtificialIntelligence #Python #AIEngineering #AgenticAI #AIWorkflow #CodeBeforeYouSleep #YashJain