Large Language Model (LLM)
A large language model is an AI system trained on vast amounts of text to predict and generate language, and is the engine that writes the answers in AI search.
Also known as: LLM
A large language model is the AI that generates the answer. Trained on enormous volumes of text to predict the next word in context, an LLM can write fluent, coherent responses — and in an answer engine it's the component that turns retrieved passages into the final, synthesized reply.
For AEO, the key insight is that an LLM doesn't reproduce your page; it reads the passages it's given and rewrites an answer, often quoting or paraphrasing the clearest source. That's why extractable, self-contained writing wins — it's the easiest for the model to lift accurately and attribute. It's also why models can hallucinate: left without good retrieved sources, they generate plausible-sounding text from memory.
Example. When an answer engine responds to your query, an LLM is doing the writing — taking the retrieved sources and composing a reply. Your job in AEO is to make your passage the one it finds easiest to use and credit.
Relevant pillar
Related terms
- Answer EngineAn answer engine is a search system that responds to a question with a direct, synthesized answer instead of a list of links, usually citing the sources it drew from.
- Training DataTraining data is the body of text and other content an AI model learns from during training, shaping what it knows by default before any live retrieval is involved.
- TransformerThe transformer is the neural-network architecture behind modern language models, which uses an attention mechanism to weigh how words relate, enabling fluent understanding and generation of text.
- HallucinationA hallucination is when an AI model states something false or fabricated as if it were fact, usually because it generated from memory instead of grounding its answer in real sources.