Comment by AIorNot
10 hours ago
By far most of the code LLMs write is for crappy crud apps and webapps not pacemakers and rockets
We can capture enough reliability on what LLMs produce there by guided integration tests and UX tests along with code review and using other LLMs to review along with other strategies to prvent semantic and code drift
Do you know how much crap wordpress ,drupal and Joomla sites I have seen?
Just that work can be automated away
But Ive also worked in high end and mission critical delivery and more formal verification etc - that’s just moving the goalposts on what AI can do- it will get there eventually
Last year you all here were arguing AI Couldn’t code - now everyone has moved the goalposts to formal high end and mission critical ops- yes when money matters we humans are still needed of course - no one denying that- its the utility of the sole human developer against the onslaught of machine aided coding
This profession is changing rapidly- people are stuck in denial
> that’s just moving the goalposts on what AI can do- it will get there eventually
This is the nutshell of your argument. I’m not convinced. Technologies often hit a ceiling of utility.
Imagine a “progress curve” for every technology, x-axis time and y-axis utility. Not every progress curve is limitlessly exponential, or even linear - in fact, very few are. I would venture to guess that most technological progress actually mimics population growth curves, where a ceiling is hit based on fundamental restrictions like resource availability, and then either stabilizes or crashes.
I don’t think LLMs are the AI endgame. They definitely have utility, but I think your argument boils down to a bold prediction of limitless progress of a specific technology (LLMs), even though that’s quite rare historically.