Follow the pipeline from raw web text to a served answer — nine stations, left to right. Set how deep you want to go, and each station reveals the right lessons.
Fundamentals — The plain idea — what it is and why it exists.
Get the raw text.
Clean it and build the training set.
Turn text into vectors the model can do math on.
The forward pass through the hidden layers.
How the next token is chosen.
Teach it on all that data.
Specialize the base model.
Learn from human & AI feedback.
Run it fast for real users.