LLMs like GPT-4o, Claude 3.5, and Llama 3 form the reasoning core of modern AI applications. They work by predicting the next token in a sequence, but at sufficient scale this produces emergent capabilities like coding, analysis, and complex instruction-following. For founders, choosing the right LLM for each task — reasoning vs. structured output vs. cost — is a core architectural decision.