Hard disagree. Usually I am wiser than the AIs but there have been times where the AI has pushed back and made me see the light on some poor design I was about to pursue
Sometimes, a rubber duck is good enough. But sometimes, you can benefit a lot from a rubber duck that can say "actually, your entire line of reasoning is wrong". Even if the latter is more frustrating.
I think the issue here is the nebulous definition of vibecoding.
You, as an experienced engineer, are doing a lot of hand holding and review of LLM-generated output, maybe even(?) using it as purely a check on your own work. There are others, though, that are essentially outsourcing the entire process to a basic, underspecified chat prompt.
Honestly, I'm not clear where the line is as far as what is reasonable, and it seems to me that no one is really addressing that question. It's easy to wave your hands and say "vibecoding is bad", without really defining what vibecoding is.
I suppose it'll be a few years before we see the true volume of technical debt catch up with the worst offenders, but even then, without the original LLM conversations associated with it, it'll be difficult to assess that in a structured way. Mind you, that doesn't even address the ever-improving models.
It's a mix. There are some projects where I let the LLM mostly run free and I focus on architecture. Even through some scary parts. Recently I picked a parallelization scheme for this and let the LLM cook. I have no idea how it implemented it, except that it (supposedly) "does it the way I asked:
dnautics · · focus · HN ↗
ACCount39 · · focus · HN ↗
dnautics · · focus · HN ↗
bjord · · focus · HN ↗
You, as an experienced engineer, are doing a lot of hand holding and review of LLM-generated output, maybe even(?) using it as purely a check on your own work. There are others, though, that are essentially outsourcing the entire process to a basic, underspecified chat prompt.
bjord · · focus · HN ↗
I suppose it'll be a few years before we see the true volume of technical debt catch up with the worst offenders, but even then, without the original LLM conversations associated with it, it'll be difficult to assess that in a structured way. Mind you, that doesn't even address the ever-improving models.
dnautics · · focus · HN ↗
<a href="https://github.com/ityonemo/bpa" rel="nofollow">https://github.com/ityonemo/bpa
For my projects that I use day to day in prod there is considerably more hand-holding and code review.