LangGraph from Scratch

There's a particular kind of magic in typing a question into a box you built yourself and watching the answer stream back, word by word. This series is the full path to that moment, from an empty folder to a deployed chatbot that streams its answers, does real math with a calculator tool, searches the web, and remembers what you told it yesterday.

It's written for a developer who can put together a basic Python function and a basic React component but has never touched FastAPI, Next.js, or LangGraph. Every new idea gets explained the first time it appears; nothing assumes you've already read the docs.

Four rules hold across all eight parts:

• Every part ends with something running. Never "trust me, this pays off later". You finish each part with a working thing you can show someone.
• You pick one LLM provider in Part 1, OpenAI or Anthropic, and every code snippet in the series comes in both flavors. Your choice sticks; the tabs remember it.
• Versions are pinned. Each part lists exactly what it was written against, so you can tell version drift from a genuine mistake.
• Errors are part of the curriculum. Each part breaks something on purpose and reads the traceback with you, because you'll meet that same error on your own at 11pm and it shouldn't win.

What you need: a laptop (macOS, Linux, or Windows all work), a terminal you're willing to type into, and about $5 of LLM credit. Part 1 walks you through getting the API key and setting a hard spending cap, so the meter is never on your mind.

By Part 8 you'll have shipped a real product: a Python backend on Fly.io, a Next.js frontend on Vercel, and a public URL you can text to a friend. More importantly, you'll know how every line of it works, because you typed all of them.