What Is an LLM? How Large Language Models Actually Work

An LLM (large language model) is an AI trained on a huge pile of text to guess the next word in a sentence, over and over, until it has written a full answer. That is the entire trick behind ChatGPT, Claude, Gemini, and every chatbot built on top of them.

It also explains something important if you are thinking about putting AI to work in your business. An LLM does not know your company. It knows patterns in language. Feed it nothing about your business and it will still answer, just by guessing.

How does an LLM actually work?

The model reads an enormous amount of text during training: books, websites, articles, code, forum posts. It is not memorizing pages. It is learning patterns, which word tends to follow which other words, given everything that came before it.

When you type a prompt, the model breaks it into small pieces called tokens, roughly a word or a piece of a word. Then it predicts the single most likely next token, adds it to the reply, and predicts the next one after that. It repeats this thousands of times to produce a paragraph. It is not thinking through your question. It is guessing one token at a time, extremely well.

What is a "parameter" in an LLM?

A parameter is one of the internal settings the model tunes while it trains, a tiny dial adjusted based on the text it reads. A model has billions of these dials, and together they hold everything it picked up about language.

GPT-3, one of the earlier large language models, runs on 175 billion parameters. (AWS)

More parameters generally means the model can hold more nuance and work through harder reasoning. It does not mean the model knows more about your business. That part still depends entirely on what you feed it.

Why does an LLM make things up (hallucinate)?

Because predicting the next likely word is the model's whole job, not checking facts. If it was never trained on something, like your return policy or last week's price change, it does not stop and say "I don't know." It fills the gap with whatever sounds most likely to come next, and says it with the same confidence as something true.

This is why a general LLM guesses at your business instead of answering it correctly. It never saw your FAQs, your emails, or your actual policies, so when someone asks it about you, it produces the statistically likely answer, not the real one.

Is ChatGPT an LLM?

Not exactly. ChatGPT is a product built around an LLM (OpenAI's GPT models). Claude is a product built around Anthropic's Claude models. Gemini is built around Google's models. The LLM is the part that actually generates the text. Everything else you interact with, like the chat window and the memory, gets built on top of it.

Each company trains its own model on its own data, which is a big part of why the same question gets a different answer depending which one you ask.

What does this actually mean for your business?

If you ask a generic LLM about your own company, it is guessing. It never read your pricing page, your policies, or the last hundred questions your customers asked you. That is not a flaw you can fix with a clever prompt. It is how the tool works: without training on your content, it has nothing real to draw from.

A bigger or smarter model does not fix that. What fixes it is training the model on your own content: your FAQs, your policies, the actual questions people ask you. We built exactly this for Brock Johnson's InstaClubHub community, an agent trained on the real course content and past member questions, so it answers in Brock's voice instead of guessing at it.

If you want to see what that looks like, there's a live demo where a coach pastes in their YouTube link and about a minute later is talking to an AI version of themselves, built from their last five videos.

Related reading: What Is RAG?, AI Agent vs Automation, and Why ChatGPT Gets Your Business Information Wrong.

---

Common questions about LLMs

What is an LLM in simple terms?

An LLM is an AI trained on huge amounts of text to predict the next word in a sentence. That single skill, repeated over and over, is how it writes answers, essays, and code.

What's the difference between an LLM and AI in general?

AI is the whole field, everything from a spam filter to a self-driving car. An LLM is one specific type of AI, built to work with language: reading it and generating more of it.

Do all AI chatbots run on the same LLM?

No. ChatGPT runs on OpenAI's models, Claude runs on Anthropic's models, Gemini runs on Google's models. Different companies train their own models on their own data, which is part of why they answer the same question differently.

Can an LLM learn my business on its own?

Not the parts that matter. It can guess at public information if you have a website, but it will not know your real prices, policies, or the questions your customers actually ask, unless someone feeds it that content directly.

Is a bigger LLM always better for a business?

Not for most business tasks. A bigger model can reason through harder problems, but for something like answering FAQs in your own voice, a smaller model trained on the right content usually beats a giant model that knows nothing about you.