> Current LLMs fail if what you're coding is not the most common of tasks
Succeeding on the most common tasks (which isn't exactly what you said) is identical to "they're useful".
Succeeding on the most common tasks (which isn't exactly what you said) is identical to "they're useful".
But it's also utterly failed to handle mundane tasks, like porting legacy code from one language and ecosystem to another, which is frankly surprising to me because I'd have assumed it would be perfectly suited for that task.
But the worst LLMs? One of my personal tests is "write Tetris as a web app", and the worst local LLM I've tried, started bad and then half way through switched to "write a toy ML project in python".
It’s a very useful tool, not magic.