AI Engineering with LangChain for JavaScript Developers

About this course

In this course, you'll start from a blank TypeScript project and end with a working AI Engineering Copilot — an agent system that takes a feature request, searches the web, reads your codebase, writes multi-file code changes, gets your approval, and opens a GitHub pull request. Fully automated. Fully understandable.

Every concept is introduced with a minimal standalone example before it's wired into the Copilot, so you always know what you're building and why.

What makes this course different:- Everything is in TypeScript — no Python detour required- You build one real system across the entire course, adding one capability per section- You learn LangChain and LangGraph by using them for something that actually matters- The Copilot you build is a realistic, production-inspired system — not a toy demo

What you'll build, section by section:- LLM Mechanics — first LLM calls, streaming, structured output, reasoning models, and LangSmith tracing- LangChain Agent Architecture — create

Agent, tool definitions, state schemas, middleware, and human-in-the-loop patterns- Engineering Researcher — a ReAct agent with Tavily web search and documentation lookup- Repo Intelligence Layer — file tools that let agents read, list, and search your codebase- RAG Over Codebase — embed your code with OpenAI, store it in Chroma, and query it semantically- Planning Engine — clarify ambiguous requests and generate structured engineering plans- Multi-File Code Generation — produce and render diffs across multiple files- LangGraph Fundamentals — StateGraph, nodes, edges, cycles, parallelism with the Send API, Command, and checkpointers- Assembling the Copilot — wire all agents into one LangGraph graph with parallelism

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