Why You Should Learn How AI Actually Works

AI is a fascinating technology. I still remember the first time I tried the Davinci model in 2020 from OpenAI, and I was flabbergasted by how it could artificially write blocks of meaningful text.

Since then a lot has changed. We had ChatGPT in 2022, GPT-4 in 2023, Claude Code in 2025, OpenClaw in 2026, to now whatever is the current track of AI Engineer.

I was born in 2003, by the time I got to university all the biggest technological revolutions of the last decade – the internet, the iPhone, cloud were past their inflection point. But AI is different, it’s the only General-purpose technologies that I’ve witnessed from the launch of ChatGPT to becoming fastest growing consumer technology ever created.

Broken Fundamentals

I am much more AI-pilled than 99% of people out there and been part of this ecosystem since its infancy (building a GPT wrapper in 23, AI gateway 24-26). But I was so busy with the next ‘shiny’ thing in AI that I never took out time to learn the fundamentals until now.

The problem with this approach chasing the next shiny thing is that you are building a skyscraper with a broken foundation.

Why Learn The Basics of AI?

Fair question. For most technology you can simply use it without understanding how it works. I don’t need to understand how airplanes work, or how their microwave heats food, and the same goes for 90% of all the consumer technology out there.

Here’s why I believe understanding AI matters:

1. There’s so much junk out there with AI; for you to decide what’s useful you need the taste that can be developed once you understand the basics of this technology.

2. If you are a builder, a good way you develop new ideas is by being at the frontier of technology, understand what it’s capable of doing. Being on the frontier allows you to see the blindspots and build tools to solve them. In return capture value to build wealth. Unless you know how LLMs work, you won’t be able to understand what you can do with them, to mine gold or sell shovels.

3. AI is a force multiplier. People who fully embrace a new technology aren’t 5x more productive than the old way of working — they’re 100x. But here’s the paradox: AI, like any technology, isn’t perfect. It makes errors. And the only way to reliably spot those errors is to understand the fundamentals. Do you have an intuition for why image models used to mangle human hands, and how frontier labs fixed it? Or why models struggle to count the R’s in “strawberry”? The basics are what let you answer questions like these.

4. The learning cost is lowest early. It’s easier to grow along with new technology when it’s early. like reading Darwin’s “On the Origin of Species” is better to understand evolution than reading CRISPR. Paying that learning cost while the AI is still young lets you hill climb faster.

What’s Next

This is an exciting time to build. Like every technology wave before it, this is my attempt to document what I’m learning in the open — sharing notes, and along the way meeting new people, running into new ideas, and earning some distribution.

I’ll post once a week: fundamentals, what’s new, and whatever I can’t stop thinking about. Next up: how LLMs work at a fundamental level.