Large Language Model (LLM)
A large language model (LLM) is a type of AI model trained on very large amounts of text to predict and generate language, which lets it answer questions, summarize, write and follow instructions.
Also called: LLM
Why it matters
LLMs are the engine behind AI assistants, AI search features and AI agents. In go-to-market work they draft and personalize messages, summarize calls and accounts, classify replies and leads, research companies and turn unstructured text, such as job posts or websites, into structured data teams can act on.
LLMs generate likely text rather than look up facts, so they can state wrong information confidently, often called hallucination. Teams get reliable results by giving the model the right context, asking for structured output, grounding answers in real source data and checking important outputs. Prompt engineering and context engineering are the practices for doing this well.
Example
A sales team gives an LLM a company's website text and a short description of its ideal customer, then asks it to return whether the company fits, a one-sentence reason and a confidence level. A person reviews a sample of the answers before the team uses the results to choose which accounts to contact.
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