Lesson 1 of many About 10 minutes Goal: Build an LLM Product

What Is an LLM?

Before you build anything with an LLM, you need one mental model that changes how you see everything. This lesson gives you that model.

The one-sentence truth

An LLM — Large Language Model — is a program that has read an enormous amount of human text and learned one skill: predicting what word comes next.

That is it. Everything else — coding help, creative writing, answering questions, summarising documents — is a consequence of doing that one thing extremely well, on an almost unimaginable scale.

Why does predicting words make it seem smart?

To predict what word comes next in "The capital of France is ___", the model has to have absorbed the fact that Paris is the capital of France. To predict the next line of code, it has to understand what the previous lines do.

It learned all of this by reading a significant fraction of the internet, Wikipedia, books, code repositories, and scientific papers — hundreds of billions of words. The "intelligence" is compressed pattern-matching from that data.

What "large" actually means

The "L" in LLM refers to the number of parameters — internal numbers adjusted during training to improve prediction. A small model might have 7 billion parameters. GPT-4 has an estimated 1.8 trillion.

More parameters generally means better reasoning — but also requires more compute. Your RTX 5060 (8GB VRAM) runs 7B models comfortably. Anything larger needs the cloud.

How your product will use an LLM

Every LLM product works the same way at the core:

1. Send text in — called a prompt
2. LLM generates text back — called a completion
3. Your product acts on that text — shows it, stores it, triggers something

Building LLM products is mostly about steps 1 and 3: writing effective prompts and deciding what to do with the output. That is where your value as a builder lives.