upvote

points

by pron2 hours ago |
comments
upvoteby eloisant2 hours ago|
next
[-]
The very definition of "vibe coding" is using AI to write software and not even look at the code it produces.
reply
upvoteby tovej1 hours ago|
parent|
[-]
People use two definitions.

There's this definition of LLM generation + "no thorough review or testing"

And there's the more normative one: just LLM generation.[1][2][3]

"Not even looking at it" is very difficult as part of a definition. What if you look at it once? Or just glance at it? Is it now no longer vibe coding? What if I read a diff every ten commits? Or look at the code when something breaks?

At which point is it no longer vibe coding according to this narrower definition?

[1] https://www.collinsdictionary.com/dictionary/english/vibe-co...

[2] https://www.merriam-webster.com/dictionary/vibe%20coding

[3] https://en.wikipedia.org/wiki/Vibe_coding

reply
upvoteby tedmiston59 minutes ago|
parent|
next
[-]
we really need some more precise terms here to make that line clear: something like "black-box vibe coding" vs "gray-box vibe coding"
reply
upvoteby fragmede1 hours ago|
parent|
prev|
[-]
If you do not know the code at all, and are going off of "vibes", it's vibecoding. If you can get a deep sense of what is going on in the code based off of looking at a diff every ten commits, then that's not vibe coding (I, myself, are unable to get a sense from that little of a look).

If you actually look at the code and understand it and you'd stand by it, then it's not vibecode. If you had an LLM shit it out in 20 minutes and you don't really know what going on, it's vibecode. Which, to me, is not derogatory. I have a bunch of stuff I've vibecoded and a bunch of stuff that I've actually read the code and fixed it, either by hand or with LLM assistance. And ofc, all the code that was written by me prior to ChatGPT's launch.

reply
upvoteby chucklenorris2 hours ago|
prev|
[-]
1 is definitely false right now. I gave specs, tests, full datasets, reference code to translate to an llm and still produce garbage code/fall flat on it's face. I just spent one week translating a codebase from go to cpp and i had to throw the whole thing out because it put in some horrible bugs that it could not fix even burning 500$ worth of tokens and me babysitting it. As i said it had everything at it's disposal: tests, reference impl, lots of data to work with. I finally got my lazy ass to inplement it and lo and behold i did it in 2 days with no bugs (that i know of) and the code quality is miles better than that undigested vomit. The codebase was a protocol library for decoding network traffic that used a lot of bit twiddling, flow control, huffman table compression, mildly complicated stuff. So no - if you want working non-trivial code that you can rely on then definitely don't use a llm to do it. Use it for autocomplete, small bits of code but never let the damn thing do the thinking for you.
reply
upvoteby pron44 minutes ago|
parent|
[-]
Oh, I agree. Anthropic themselves proved that even with a full spec and thousands of human-crafted tests, unsupervised agents couldn't produce even something as relatively simple as a workable C compiler, even when the model was trained on the spec, tests, the theory, a reference implementation, and even when given a reference implementation as an oracle.

But my point was that I don't think the development of Claude Code itself isn't supervised, hence it's not really "vibe coded".

reply