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I just tried vibe coding with Claude (programming.dev)

submitted 1 day ago by entwine@programming.dev to c/programming@programming.dev

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...and I still don't get it. I paid for a month of Pro to try it out, and it is consistently and confidently producing subtly broken junk. I had tried doing this before in the past, but gave up because it didn't work well. I thought that maybe this time it would be far along enough to be useful.

The task was relatively simple, and it involved doing some 3d math. The solutions it generated were almost write every time, but critically broken in subtle ways, and any attempt to fix the problems would either introduce new bugs, or regress with old bugs.

I spent nearly the whole day yesterday going back and forth with it, and felt like I was in a mental fog. It wasn't until I had a full night's sleep and reviewed the chat log this morning until I realized how much I was going in circles. I tried prompting a bit more today, but stopped when it kept doing the same crap.

The worst part of this is that, through out all of this, Claude was confidently responding. When I said there was a bug, it would "fix" the bug, and provide a confident explanation of what was wrong... Except it was clearly bullshit because it didn't work.

I still want to keep an open mind. Is anyone having success with these tools? Is there a special way to prompt it? Would I get better results during certain hours of the day?

For reference, I used Opus 4.6 Extended.

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[–] vga@sopuli.xyz 1 points 5 hours ago* (last edited 5 hours ago)

Maybe the only piece you’re missing is that “almost right, but critically broken in subtle ways”

Sure, but you have to note that it reaches that point in minutes. Sometimes on a task that would take humans a week. The power is not that it creates correct stuff, it's that it creates almost correct stuff 100 times faster than human. Plus the typical machine benefits: it never gets tired, demotivated, etc.

So then the challenge becomes being able to be that human, who can review stuff extremely well and rapidly, being natural in probing the stuff LLMs tend to be wrong about. Sort of like the same challenge that every tech lead had before LLMs too, but just subtly different, because LLMs don't exactly think like we do.