Creator of LowTech AI

If you’ve encountered text written by a computer in the past year (you definitely have), it was probably generated by a large language model, AKA an LLM.

LLMs are the AI technology behind Gmail autocomplete, ChatGPT, and 

, but what does that term actually mean? As these systems get more integrated with our work and lives, it’s worthwhile to understand the basics. Here’s the absolute bare necessities you should know.

First off, let’s go through the meaning of each word in “Large Language Models.”


Jack O'Brien

If you do work that’s on a computer, LLMs will be a part of your life. I think it's important to learn the basics.

What’s a Large Language Model?

Using ChatGPT effectively is an acquired skill. Without prior experience and learned intuition, your AI generated responses will probably be improperly formatted, way too long, a bit cold in tone, or simply not what you were hoping for.

I have a good deal of experience working with opaque software systems, so I was lucky to pick up the basics of AI prompting fairly quickly (though I’m still far from an expert prompter). You need to be extremely specific. You need to be concise. You need to explain your thought process and your desired output. Lots of people have said that AI prompting today is like learning how to use Google in 2001, and I think there’s truth to that idea. We’re still learning how to correctly poke the machine.

 people have used ChatGPT, and I’m fairly certain the vast majority of them don’t know how to use it to the best of its ability (enter 1000+ Twitter threads and LinkedIn posts on how “you’re not using ChatGPT correctly”). AI chatbots open up infinite possibilities to explore virtually all documented human knowledge and experience, but a small uninteresting subset of that potential is what most people see today.

AI users don’t really care about the prompt, they care about the value generated from the prompt and the AI model. Signaling that value is more important during the discovery and use of a prompt than understanding the underlying template.

Prompt Engineering

What’s a Large Language Model?

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