In one sentence
A large language model is the type of AI behind assistants like ChatGPT, Claude and Gemini, trained on huge amounts of text to understand questions and write answers, including which products to recommend.
How large language models work
An LLM learns patterns in language by reading a very large body of text. When you ask it something, it writes a reply one word at a time, choosing what fits best based on everything it learned.
Assistants wrap an LLM in a product. ChatGPT, Claude, Gemini and Perplexity each add their own features, like web search, on top of the model.
Where LLMs get their facts about your store
- Training data: what the model read before release. It is fixed until the next version.
- Grounded search: live web results the assistant looks up for this question.
- Feeds and structured data: product details some assistants read directly.
If none of those sources say clearly what you sell and who it's for, the model fills the gap with competitors it knows better.
Why LLMs matter for ecommerce brands
Shoppers now ask LLM-powered assistants what to buy. The model decides which brands to name, how to describe them and which to leave out. That makes the model a new kind of gatekeeper between you and the shopper.
LLM FAQs
Does ChatGPT know about my store?
Ask it. Then ask Claude, Gemini and Perplexity the same shopper questions. Answers change between runs, so treat one check as a snapshot and track the same questions over time.
Can an LLM get facts about my products wrong?
Yes. That's called an AI hallucination. Clear product pages, accurate structured data and consistent details across the web make it less likely.
Is an LLM the same as an AI assistant?
No. The LLM is the model. The assistant is the product around it, with search, memory and other tools added.
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