6h • General Discussion 💬
LLMs & Core Concepts (Demystifying the basics)
Like me, you probably jumped into the automations world without understanding the basics, so I decided to do a deep dive and document my learnings:
This newsletter is part of a mini-series breaking down the main concepts behind AI in plain English.
No jargon. No tech-talk. No bore-fest.The mission: make AI accessible to everyone, so we can all make informed decisions about when — and how — to use it.
What I will cover:
1. What is an LLM? (in plain English)
2. How LLMs differ at a high level
3. What “tokens”, “context window”, and “reasoning” mean
1. What is an LLM (in plain English)?
If you use ChatGPT, Claude, Gemini, or Copilot — you’re already using an LLM.
You just might not know what it actually is.
LLM = Large Language Model
But here’s the simple explanation 👇
An LLM is basically:
> A system trained on huge amounts of text
> That predicts the next best word in a sentence
> Over and over again, very fast
That’s it.
It’s not “thinking”
It’s not “conscious”
It’s not “alive”
It’s just incredibly good at patterns.
Think of it like this: an LLM is your smartest, fastest assistant who has read most of the internet and never gets tired.
You can use it to:
✔️ Think through problems
✔️ Write emails & content
✔️ Brainstorm ideas
✔️ Summarise documents
✔️ Create plans
✔️ Automate thinking
The difference between “AI feels confusing” and “AI feels powerful” often comes down to ONE thing:
Understanding what you’re talking to. And how to talk to it.
for the second and third topic read the rest of the newsletter below:
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LLMs & Core Concepts (Demystifying the basics)
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