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# What is an LLM and what is it for?
- URL: https://jonathancanales.com/en/what-is-an-llm-and-what-is-it-for/
- Published: 2026-09-30T15:00:00.000Z
- Updated: 2026-10-19T01:02:50.000Z
- Description: If you've used ChatGPT, Claude or Gemini, you've already met an LLM; nobody just introduced you properly. LLM stands for Large Language Model. It's the software “brain” behind almost all the AI you hear about today.
- Author: Jonathan Canales
- Tags: AI for business, #pair-llm, #en

What is an LLM and what is it for?

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If you've used ChatGPT, Claude or Gemini, you've already met an LLM; nobody just introduced you properly. LLM stands for **Large Language Model**. It's the software “brain” behind almost all the AI you hear about today.

The short version: an LLM is a program that read an absurd amount of text and learned, statistically, what comes next in a sentence. Sounds simple. What's surprising is how much that single trick can do.

💡

In one line: an LLM doesn't “know” things the way a person does. It's a text-prediction machine trained so well that it often looks like it understands.

## What does “large language model” actually mean?

Let's take the name apart:

- Large: it has billions of internal “settings” (parameters), tuned by reading much of the public internet, books and code. Training one costs millions of dollars in computing power.
- Language: its raw material is language; it reads and writes. Newer models also handle images and audio, but language is still the core.
- Model: it's not a database or an encyclopedia; it's a mathematical representation of patterns in language and in the world described by those texts.

There are also **SLMs** (Small Language Models): the compact edition. They fit on a laptop or a phone, they're cheaper and more private, just less capable. Hence the “LLM / SLM” in the drawing.

## How does it work? Little pieces and predictions

An LLM doesn't read whole words: it chops text into pieces called **tokens**. A token can be a word, half a word or a punctuation mark. “The cat drinks…” becomes a row of tiles, and the model calculates the most likely next tile: “milk”.

![Whiteboard-style doodle: the sentence 'The cat drinks...' chopped into tokens feeds a brain, which predicts 'milk?'](https://jonathancanales.com/content/images/2026/10/doodle-tokens-prediction-g.png)

And that's all it does. Every answer ChatGPT gives you is that same move (predict the next token) repeated hundreds of times a second. It's your phone's autocomplete, but after reading half the library.

So don't be surprised when it gets something wrong with total confidence: it's not “thinking” like you; it's completing patterns. That's called **hallucinating**, and it's the golden reason to double-check numbers, dates and quotes before using what it writes.

## A brain with senses… and hands

![Whiteboard-style doodle: a brain labeled LLM/SLM takes in reading, sight, hearing and thinking, and acts through tools, data and agents](https://jonathancanales.com/content/images/2026/10/doodle-llm-slm-brain-g.png)

The drawing sums up today's models well. On one side, they no longer just read: they can **see** images, **hear** audio and **reason**, generating intermediate steps before answering, like someone thinking out loud.

On the other side, they no longer just write: connected to the right pieces, they can use **tools** (search the web, send an email), query **data** (your catalog, your reports) and coordinate **agents** that carry out full tasks. I covered that in detail in [the post about AI agents](https://jonathancanales.com/en/from-ai-chat-to-ai-work-agents-september-2026/).

## What is it good for in a business like yours?

- Drafting and summarizing: emails, proposals, meeting notes, job descriptions.
- Answering with your information: an assistant that replies to customer questions using your documents, not its imagination.
- Translating and adapting: the same content in two languages, in your brand's tone.
- Reading for you: contracts, reports and quotes summarized into paragraphs that actually make sense.
- Coding and automating: from an Excel formula to full workflows between your systems.

🎯

Where to start: pick one repetitive task with clear rules, whose result you can check in minutes. That's where an LLM saves you time from week one.

## What an LLM doesn't do well

- Inventing with confidence: if it doesn't know, it completes the pattern anyway. Verify what matters.
- Knowing your business: by default it knows nothing about your company; you have to give it context or connect it to your data.
- Keeping secrets: don't paste sensitive client information into tools you don't control.
- Replacing your judgment: it proposes, drafts and accelerates; the decision and the responsibility stay with you.

The best mental model: a brilliant intern who read the whole library, works 24/7 and charges pennies… but occasionally states false things with a smile. Give it clear context, put it on concrete tasks and review its work. With those three rules, it's one of the most useful tools an office has ever had.

[Read the Spanish version of this article](https://jonathancanales.com/que-es-un-llm-y-para-que-sirve/)