What's actually happening inside an LLM

A Large Language Model predicts the next token (a word-piece) given everything before it. Trained on vast text, it learns astonishingly rich patterns — enough to write, reason, and code.

Concepts you need to build well

• Tokens — text is chunked into tokens; you pay and are limited by tokens, not words.
• Context window — how much the model can "see" at once. Everything must fit.
• Transformers & attention — the architecture that lets models weigh relevant context.
• Temperature — controls randomness/creativity of outputs.

Takeaway: you don't need to build a transformer — but understanding tokens and context makes you a far better builder.