L028 · Under the hood · 2 min
Fine-tuning vs prompting
Before you train your own AI, try a better prompt and your own documents; that solves most problems faster and cheaper.
01 · The idea
There are three main ways to make AI fit your needs. Prompting: give instructions and examples each time. RAG: let it look up your documents. Fine-tuning: train an existing model further on your own examples.
Fine-tuning changes the model itself. It is good for a very consistent style or format, or a narrow task done millions of times. It needs good data, money and skills, and must be redone when better models arrive.
Prompting and a good system prompt cost almost nothing and can be changed in minutes. RAG is best when the problem is missing knowledge, like prices or policies.
A simple rule: start with prompting, add RAG for knowledge, and consider fine-tuning only when those clearly fall short.
02 · Think of it like this
Prompting is giving a chef a recipe card. RAG is giving them your family cookbook. Fine-tuning is sending them to cooking school for a year.
03 · Do it now
04 · Quick check
Words in this lesson
See also
L167Under the hood · 3 min
The journey of one question through an AI app
Between pressing send and seeing an answer, your question passes through checks, extra context, the model, maybe some tools, and more checks.
L030What's next · 1 min
How to keep up without burning out
You do not need to follow every AI headline; a small weekly habit beats chasing the news.
L154AI at work · 3 min
Skills: teach the AI a task once
A skill is a saved recipe of instructions, and sometimes files, that the AI picks up whenever a task calls for it.
L025Under the hood · 2 min
RAG: give AI your documents
RAG lets a chatbot look up the right pages in your own documents before it answers, so it can use facts it was never trained on.