The Mechanics of Next Word Prediction

The Travcoding team — Solo episode

A plain-language walk through how large language models guess the next token — what they actually learn, where they fail, and why that matters for business use.

“The model isn't thinking ahead. It is scoring words based on patterns it saw in text. The business risk is treating that scoring as understanding.”

Shownotes

• What 'next word prediction' actually means inside a trained model
• How training data shapes what the model can and cannot say
• The difference between memorisation, pattern matching and reasoning
• Why output quality depends more on prompt design than model size