---
title: "Episode 0: Why Code LLMs From Scratch"
description: "Understanding how LLMs work without a PhD in mathematics: what this series promises, what you will learn, and the one idea that ties every episode together."
url: "https://mayorana.ch/en/blog/llm-from-scratch-introduction"
language: "en"
date: "2026-09-27"
author: "Mohamed Bennekrouf"
tags:
  - "llm"
  - "ai"
  - "rust"
  - "machine-learning"
fr_version: "https://mayorana.ch/fr/blog/llm-from-scratch-introduction.md"
---

# Episode 0: Why Code LLMs From Scratch

## What this series promises

Understand how LLMs (ChatGPT, Claude, etc.) work without needing a PhD in mathematics. Each episode starts from a simple question, explains the "why" before the "how", and uses Rust examples where they help.

## Why "from scratch"?

Because reading articles is not enough. It's like cooking: watching a recipe doesn't teach you how to cook. Coding the 4 operations of attention yourself will teach you more than hours of reading.

## What you will learn

- How a word "looks at" the other words (attention)
- Why Q, K and V are kept separate (specialization)
- How meaning is turned into geometry ([embeddings](https://mayorana.ch/en/blog/embeddings-absolute-vs-contextual))
- How to reuse an existing model ([transfer learning](https://mayorana.ch/en/blog/transfer-learning-reusing-knowledge))
- How it all comes together to build a [RAG](https://mayorana.ch/en/blog/embeddings-vector-databases-rag)

## Who is this series for?

Anyone curious who can read simple code and wants to understand AI without getting lost in jargon. You don't need to be a mathematician, just patient.

## The common thread

A single idea runs through the whole series: **meaning can be represented by vectors, and those vectors can be compared by how close they are**. Everything else follows from that.