A (simplified) 12 chapter interactive guide for curious minds
How LLM's Code
AI coding has always been front and center when it comes to tangible value propositions for language model based AI. In a few short years the tech has moved from autocompleting lines, toward agents that read a codebase, retrieve context, edit files, run tests and improve their own output in loops that can run for days. This guide gives you the mental model underneath the magic.
Future coding stack
human-led
Who is this guide for?
Curious people, AI enthusiasts, AI pessimists, actually anyone who wants to understand the machinery behind AI coding: tokenizers, embeddings, retrieval, attention, generators, agents - the list goes on and one -.