Production AI Agents with JavaScript: LangChain & LangGraph

Most LangChain and Lang Graph courses are Python-first. This one is built from the ground up for Java Script & Type Script engineers who want real, shippable agentic systems—not disconnected demos.You’ll build a sequence of end-to-end projects that mirror how modern teams ship AI features: clean Type Script code, clear AP Is, JSON contracts, Lang Graph orchestration, RAG, proper vector stores, and real Next.js frontends wired to real agents.By the end, you’ll know exactly how to go from idea → design → implementation → observability → deployment in the JS ecosystem.Here’s what we’ll cover in Phase 1:Intro & Mindset How this course works, what it is / isn’t, and how to follow.Choosing models (OpenAI / Gemini / Groq / local) smartly for cost, speed & reliability.How all projects connect into a reusable “agent platform” you can extend.Foundations: LangChain, Agents & Flow Modern AI app architecture: UI → orchestration → models → tools → storage.Simple, honest definition of AI agents and real-world use cases.Chains vs agents: when a chain is enough, when an agent is worth it.Where LangChain.js fits, where Lang Graph.js fits, and how they work together.JSON-first mindset teaser: why strings lie and schemas save you.Orientation & “Hello Agent” ProjectTS/Node project setup, tsconfig, env patterns, scripts.Multi-provider setup: OpenAI, Gemini, Groq via a single provider factory.First “Hello Agent” function that runs like a clean backend primitive, not a toy script.LLM Fundamentals: JS