> A twenty line for loop. It overengineers most things.

Anecdote I like to tell.. I was working on a financial planning software, intentionally purely vibe coded as an experiment.

I eventually discovered AI had implemented seven duplicate copies of tax calculation functions. All of them different. All of them wrong. All of them giving different answers for same input.

Not even the most junior of newbie junior engineers would do something this crazy. But AI was happy to do it. It will solve the immediate problem, efficiently. Even if the most efficient solution is something ridiculous like this.

I have also a weird story to tell that a human did and it is as crazy as this. It happen in 2019 so no LLMs at all.

A person that was hired as an expert in our startup spent more than one week full time working on implementing his solution to the problem we were having. I checked the code after one week to see the progress and was curious how they are implementing an already crazy sounding idea. I found that the whole week was spent re-implementing in python, python's built-in "float" function. That was it, the whole code was just that.

Our problem was related to financial services and their implementation of "float" was not even correct.

Which model though? I have similar anecdotes but all with older models. The jump in capabilities in the last 6 months has been substantial.

For some definitions of efficiency.