The faster you accept that having your dev team "vibe coding" is a terrible idea, the faster you’ll wake up from the fantasy and start moving in the right direction. 

Vibe coding feels great — until it doesn’t.
The problem? LLMs (Large Language Models) are basically confident improv artists. Their so-called “neural networks” generate variations in their answers, and at some point — for reasons we won't psychoanalyze here — their output quality starts to decay. If you’re lucky, that decay follows a nice logarithmic curve. If not, it just collapses and leaves you debugging cosmic spaghetti. 

So, here’s our solution: 

Don’t use A.I. to write code directly.
Use A.I. to write the scripts that write your code — exactly the way you like it.
Sounds complicated? It’s not. It’s just engineering — the boring, beautiful kind. 

This approach stands on the shoulders of two giants: 
Generic Programming and Metaprogramming. 

• Generic Programming is all about writing algorithms and data structures that can adapt to any data type. It’s reusability meets minimalism. 
• Metaprogramming is the dark art of writing programs that write or modify other programs. It treats source code like clay and makes automation possible. 



With the context-awareness of modern LLMs, these two ideas become superpowers.
They allow us to automate not just the generation of code — but the generation of elegant, testable, repeatable architecture, with AI as a tool, not a crutch. 

Let’s build systems where creativity lives above the code — not tangled inside it.