The team at GitClear published a study on code quality for AI-generated code. Not surprisingly, AI-generated code isn’t quite up to snuff:
The data in this report contains multiple signs of eroding code quality. This is not to say that AI isn’t incredibly useful.
And:
[…] the Google data bore out the notion that a rising defect rate correlates with AI adoption.
One often overlooked issue with this stems from the fact that maintaining and servicing code doesn’t come for free. As much as Jevon’s Paradox might be true for code (and I fundamentally believe it is – by making the act of writing code cheaper, we will write more code), the downstream costs can (and likely will) become significant.
Unless managers insist on finding metrics that approximate “long-term maintenance cost, ” the AI-generated work their team produces will take the path of least resistance: expand the number of lines requiring indefinite maintenance.
