Complexity Simplified #6: How AI Codes
- Amir Bder
- 6 minutes ago
- 2 min read
Welcome back to another post of Complexity Simplified at TheComplexWorldOfAI. We’re cutting through the hard techy words to explain what’s actually happening in AI. Today’s topic: How AI Codes. If you’ve seen ChatGPT or Claude build a fully functioning website in five seconds, you think you're witnessing a genuis typing behind your prompt, but the truth is a lot less magical, and a lot more interesting.
The Tech Talk (The boring version...)
AI code generation relies on Large Language Models (LLMs) that have been trained on massive repositories of open-source code. By treating programming languages like Python or JavaScript as sequential tokens, the Transformer architecture calculates the probability distribution of the next logical syntax element without executing or compiling the logic natively.
In other words...
The Master Chef With No Taste Buds
Imagine you hire a world-class chef who has memorized every single recipe book ever written (think of websites like GitHub as the ultimate recipe library).
If you ask this chef to bake a chocolate cake, they know exactly what to do. They grab flour, sugar, eggs, and cocoa powder. They know that in almost every recipe, you mix the dry ingredients before the wet ones.
But here is the catch: The chef has no taste buds.
They have never actually eaten a chocolate cake. They don’t know why sugar makes it sweet. They just know that in the 10 million recipes they read, sugar is always there.
An AI works exactly like this. When you ask an AI to write a Python script for a simple video game, it doesn't "think" about the game logic. It doesn't run the game in its head to see if the character jumps. It just looks at the patterns from millions of code "recipes" it was trained on.
It sees you asked for "Python" and "game," so it grabs the pygame ingredient.
It knows that when making a character jump, the word "gravity" usually comes next, followed by some math.
It predicts the next line of code just like the chef knows eggs follow flour.
Why This Matters for You (students and creators)
If AI can code in seconds, why should anyone ever learn computer science?
Because the chef can't taste the food.
Sometimes, the AI writes a "recipe" that looks perfect on paper but tastes awful in reality (the code has a hidden bug, hallucinated a feature, or just completely crashes your app).
The Old Way: You had to spend months learning where to place every single comma, bracket, and semicolon just to build a basic app.
The New Way: You are now the Restaurant Manager. You don't need to chop the onions yourself. You tell the AI exactly what dish you want, and when it serves the code, you test it out. If it tastes wrong, you tell the AI to fix it.
The Bottom Line
AI doesn't "understand" code the way a software engineer does; it’s just a massive pattern-matching machine predicting what symbol or word should come next based on billions of examples.
The future of coding isn't about sitting in a dark room typing thousands of lines of code; it’s about knowing how to give the best instructions to your digital chef.
