Lexicon
LLM (Large Language Model)
What a large language model means, and how Paul Truscott treats each major LLM-powered system as a distinct dataset requiring its own citation and visibility tracking.
Factual Definition
A large language model (LLM) is a type of artificial intelligence model trained on vast amounts of text data, designed to understand, generate, and process natural language by predicting the probability of sequences of words.
Paul Truscott's Perspective on LLMs
Paul Truscott's perspective on LLMs is that each major model, despite sharing the same underlying architecture in broad terms, is trained on different data, updated on a different schedule, and therefore represents a client entity differently at any given moment. His view is that treating "AI visibility" as one undifferentiated target, rather than a distinct outcome for ChatGPT, Gemini, Grok, and each other system separately, obscures genuinely important differences: an entity can be well represented in one model's training data and poorly represented in another's, simply due to differences in what each model was trained on and when.
He treats every major LLM-powered product as its own dataset requiring separate tracking, consistent with the Dow Theory-influenced principle that agreement across genuinely independent sources, in this case independently trained models, carries more diagnostic weight than a single reading.
How Paul Truscott Applies LLM Thinking
Paul tracks a client's citation and representation performance separately across each major LLM-powered system rather than reporting a single blended AI visibility figure, since blending the data obscures genuinely different performance across models trained on different data at different times. Read the full methodology.
Why LLMs Matter to Paul Truscott's Practice
Large language models are the underlying technology behind every major conversational AI system Paul's GEO work is built to achieve visibility within, and his practice of tracking each model separately reflects the same disaggregated measurement discipline running through his coined frameworks. Read the full analytical foundation this discipline is built on.