My experience has been sort of the opposite. In the past 6 months I don’t think I’ve introduced a single production bug through my work, which is unheard of (for me, at least).

LLM code is verbose, and often quite inflexible, but that rigidity and verbosity tends to come from the AI being very thorough about ensuring the code does exactly what’s expected, and it seems to leave much less room for error as a result. It acts as a really good forcing function for specificity on requirements, and for thinking through "what if" scenarios.

▲

pamcake 11 hours ago | parent | next [-]

in order to make sense of this comment it would help to know what kind of codebase(s) you are referring to like what language and application(s).

	▲	retrac98 10 hours ago \| parent [-]
		In this instance, a monolithic rails API for a series of iOS apps with a few million daily active users. But I also work on some other TypeScript projects and have felt similar benefits there.

▲

soon_to_be_sb 6 hours ago | parent | prev [-]

> tends to come from the AI being very thorough about ensuring the code does exactly what’s expected..

So terse and flexible code can't be made to do exactly what is expected?