The "attention" mechanism (a bit of a misnomer really) is what makes transformers more complex than many other neural nets - data isn't simply flowing through the model from layer to layer, but rather it is being copied and moved around by the attention heads. The "next word" it is generating doesn't even have to be a word it has ever seen before - it may be copying it from the prompt.