alt Hacker NewsA big seal of quality because it is human written? Maybe in narrow spaces but in general, I’d put money on the average developer being significantly worse at writing code with bugs than an AI. It’s codebergs infra so their choice, but it seems like an overly simplistic solution to a complicated advancing technology, in that it is a threadbare line between “vibe-coded” and “complex agent harness with human oversight and review”.
Also, I’m actually quite happy with some of the vibe-coded apps I use. Handy is an example, which started as a vibecoded app, and is fantastic for STT/dictation. It seems like a literal baby with the bath water approach.
Replies
> I’d put money on the average developer being significantly worse at writing code with bugs than an AI.
I'd put money on the average AI-coded project being of a worse quality, simply because the number of vibe-coders with no experience now outnumbers actual coders using AI-assist around 10 to 1.
I'm literally seeing companies being pitched with B2B products written by people who had never written a program before, even as a hobby!
AI on average might write better code, but there's no way AI prompted by a shoe salesman is going to be better than code written by a person with even 2x years of experience.
I'm not saying you can't be happy with autogenerated software, especially for something like a dictation app where the main functionality amounts to a language selector (or calling into a detector) and calling TTSlibary.render(String text).play(). You could also just use an existing TTS app, but whatever works for you
For more complex software, so far it has been my experience that you get more predictable behavior (fewer edge-cases), performance, and relevant (but, to be fair, less comprehensive) documentation when someone thought about and built it
[dead]
[dead]
I’d put money on the average developer being significantly worse at writing code with bugs than an AI.
I'd take that bet if it was measured in "bugs per day" instead of "bugs per LOC". LLMs generate far fewer bugs in absolute terms, but they also generate far more code, so it probably balances out if everything is equal. I think LLMs will actually lead to more bugs just because they're usually working with poorly defined requirements (prompts) and they guess to fill in the gaps based on the averages of their training data. A lot of those guesses are wrong.
Where LLMs win though is the severity. An LLM will write buggy code in the sense that it doesn't do what you wanted it, but not so much in the sense of security or data loss bugs. They get that right more than humans because they're trained to care about that stuff. There's far more "how to write good code" content in the training data than "how to not care about security and go fast" content (because writing that would be weird!)