A primer on how large language model works

Large language models (LLMs) are not simulated human minds — they are probability engines that predict the next word token based on context. Text is broken into tokens, converted into numerical vectors, processed through multiple Transformer layers, and generated one token at a time. Real-world LLM systems add retrieval, tool use, and safety controls around this core loop, while hallucinations remain an inherent reliability risk of probabilistic text generation.