Comments URL: https://news.ycombinator.com/item?id=50220869

Points: 1

# Comments: 0

Comments URL: https://news.ycombinator.com/item?id=50033431

Points: 4

# Comments: 0

What made you think so, if I may ask? The rant? The amount of text I wrote?

Feel free to look at my own posting history. You'll see that I was posting some very verbose comments here even before the first LLMs appeared on the scene... A sign of autism maybe, but no, not a bot.

EDIT: Removed what could be interpreted as a personal attack.

I'm also running local models on my gaming laptop, but just out of curiosity, for testing how far local models are coming along. Despite my negative experiences (below) I still think the technology is cool, and it's even cooler I can run it on my not very cutting edge laptop. I give local models a set of tasks and see how far along each new one comes.

Rant:

For work, I've mostly given up on using LLMs for large features, in all cases I've tried in the last 2 years, the time it takes to clean up their output is about the same I would have spent writing and debugging the feature myself. There's only a single major feature I've shipped that was mostly written by an LLM, and that was back in May. All other major tasks I've tried, even somewhat trivial ones, led to unusable code, filled with comment slop and workarounds, and hidden bugs.

This is probably due to the sheer amount of legacy code our app has, but even trying to develop more or less self-contained components was very difficult.

I do use LLMs daily, but mostly through a chat interface, as a somewhat faster alternative to web search and as an alternative to copying and pasting from StackOverflow for minor problems.

Most of my current job is now going over PRs submitted by my team members, that are mostly all AI-generated, and cleaning them up. The amount of junk inserted into the code by current SOTA models is astonishing, especially during rounds of bug fixes, probably due to context rot. Hundreds of useless variables and small wrapper functions on top of wrapper functions. Hundreds of comments that are essentially word salad, or worse, the LLM talking to the user through the comment instead of through the chat, essentially saying in a comment "I was a good subservient model, and did what you wanted! This function now returns an error, see?". Repeated hundreds of times. Not to mention actual bugs that the inane and lazy unit tests it adds never catch.

I'm far less lenient on AI output than on if the same dev wrote the code herself. Thankfully, people in my team cooperate with me and fix my comments, and so far we have no pressure from management to move faster.

/Rant

Nitpick: Title seems to be missing a word: "Are you USING a subscribed LLM or a locally open-source model". Or else it's targeting LLM which are reading this forum. If so, there aren't any responding, all responses seem to be from humans...

Comments URL: https://news.ycombinator.com/item?id=49970770

Points: 2

# Comments: 1

Comments URL: https://news.ycombinator.com/item?id=49671538

Points: 4

# Comments: 0

Comments URL: https://news.ycombinator.com/item?id=49562145

Points: 1

# Comments: 0

Comments URL: https://news.ycombinator.com/item?id=49560970

Points: 2

# Comments: 0

Comments URL: https://news.ycombinator.com/item?id=49398120

Points: 1

# Comments: 0

Comments URL: https://news.ycombinator.com/item?id=49387423

Points: 2

# Comments: 0

Just today I reviewed a patch made by a teammate using Claude for a not very significant bug, where in addition to fixing it (in a very roundabout way), it introduced 2 new very subtle bugs, and refactored a large portion of another function that was unrelated to the code, and made several observations and comments which were subtly wrong and out of touch with the rest of the code.

I ended up rejecting the PR and writing my own very small local patch for the bug.

Other people in the team use Claude to help them review my own PRs, and it sometimes finds minor issues, although there was only a single time it found a major issue.

My own use of LLMs is mostly to develop large features, which I then thoroughly review myself.

Comments URL: https://news.ycombinator.com/item?id=48701016

Points: 3

# Comments: 0

Comments URL: https://news.ycombinator.com/item?id=48682353

Points: 4

# Comments: 2

I also had the same reaction to Crime and Punishment as the OP did.

Comments URL: https://news.ycombinator.com/item?id=48485919

Points: 3

# Comments: 0

Comments URL: https://news.ycombinator.com/item?id=48034118

Points: 4

# Comments: 6

Comments URL: https://news.ycombinator.com/item?id=47707208

Points: 2

# Comments: 0