this post was submitted on 30 Sep 2025
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"No Duh," say senior developers everywhere.

The article explains that vibe code often is close, but not quite, functional, requiring developers to go in and find where the problems are - resulting in a net slowdown of development rather than productivity gains.

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[–] Sibshops@lemmy.myserv.one 128 points 18 hours ago (4 children)

I mean.. At best it's a stack overflow/google replacement.

[–] timbuck2themoon@sh.itjust.works 13 points 12 hours ago (1 children)

At absolute best.

My experience is it's the bottom stack overflow answers. Making up bullshit and nonexistent commands, etc.

[–] mcv@lemmy.zip 1 points 5 hours ago

If you know what you want, its automatic code completion can save you some typing in those cases where it gets it right (for repetitive or trivial code that doesn't require much thought). It's useful if you use it sparingly and can see through its bullshit.

For junior coders, though, it could be absolute poison.

[–] Steve@startrek.website 17 points 13 hours ago (1 children)

I found that it only does well if the task is already well covered by the usual sources. Ask for anything novel and it shits the bed.

[–] snooggums@piefed.world 6 points 10 hours ago* (last edited 10 hours ago)

That's because it doesn't understand anything and is just vomiting forth output based on the code that was fed into it.

[–] Warl0k3@lemmy.world 85 points 18 hours ago* (last edited 18 hours ago) (7 children)

There's some real perks to using AI to code - it helps a ton with templatable or repetitive code, and setting up tedious tasks. I hate doing that stuff by hand so being able to pass it off to copilot is great. But we already had tools that gave us 90% of the functionality copilot adds there, so it's not super novel, and I've never had it handle anything properly complicated at all successfully (asking GPT-5 to do your dynamic SQL calls is inviting disaster, for example. Requires hours of reworking just to get close.)

[–] Feyd@programming.dev 79 points 18 hours ago (1 children)

But we already had tools that gave us 90%

More reliable ones.

[–] MaggiWuerze@feddit.org 12 points 8 hours ago

Deterministic ones

[–] Sibshops@lemmy.myserv.one 21 points 18 hours ago (2 children)

Fair, I've used it recently to translate a translations.ts file to Spanish.

But for repetitive code, I feel like it is kind of a slow down sometimes. I should have refactored instead.

[–] cam_i_am@lemmy.world 5 points 2 hours ago

This is a thing people miss. "Oh it can generate repetitive code."

OK, now who's going to maintain those thousands of lines of repetitive unit tests, let alone check them for correctness? Certainly not the developer who was too lazy to write their own tests and to think about how to refactor or abstract things to avoid the repetition.

If someone's response to a repetitive task is copy-pasting poorly-written code over and over we call them a bad engineer. If they use an AI to do the copy-paste for them that's supposed to be better somehow?

[–] pennomi@lemmy.world 11 points 17 hours ago (2 children)

Some code is boilerplate and can’t be distilled down more. It’s nice to point an AI to a database schema and say “write the Django models, admin, forms, and api for this schema, using these authentication permissions”. Yeah I’ll have to verify it’s done right, but that gets a lot of the boring typing out of the way.

[–] panda_abyss@lemmy.ca 2 points 3 hours ago

I use it for writing code to call APIs and is a huge boon.

Yeah, you have to check the results, but it’s way faster than me.

[–] Sibshops@lemmy.myserv.one 4 points 17 hours ago
[–] Flamekebab@piefed.social 6 points 15 hours ago

Similarly I find it very useful for if I've written a tool script and really don't want to write the command line interface for it.

"Here's a well-documented function - write an argparser for it"

...then I fix its rubbish assumptions and mistakes. It's probably not drastically quicker but it doesn't require as much effort from me, meaning I can go harder on the actual function (rather than keeping some effort in reserve to get over the final hump).

[–] otacon239@lemmy.world 4 points 17 hours ago

I’ve had plenty of success using it to build things like docker compose yamls and the like, but for anything functional, it does often take a few tries to get it right. I never use its raw for anything in production. Only as a leaping off point to structure things.

[–] Valmond@lemmy.world 2 points 16 hours ago

For the missing 10% : the folder with copies of the code you have already wrote doing that.

[–] MangoCats@feddit.it 1 points 16 hours ago (1 children)

(asking GPT-5 to do your dynamic SQL calls is inviting disaster, for example. Requires hours of reworking just to get close.)

Maybe it's the dynamic SQL calls themselves that are inviting disaster?

[–] Warl0k3@lemmy.world 2 points 15 hours ago* (last edited 15 hours ago) (1 children)

Dynamic SQL in of itself not an issue, but the consequences (exacerbated by SQL's inherent irrecoverability from mistakes - hope you have backups) have stigmatized its use heavily. With an understanding of good practice, a proper development environment and a close eye on the junior devs, there's no inherent issue to using it.

[–] MangoCats@feddit.it 3 points 15 hours ago

With an understanding of good practice, a proper development environment and a close eye on the junior devs, there’s no inherent issue to using it.

My feelings about C/C++ are the same. I'm still switching to Rust, because that's what the company wants.

[–] MangoCats@feddit.it -3 points 16 hours ago* (last edited 16 hours ago)

In the beginning there were manufacturer's manuals, spec sheets, etc.

Then there were magazines, like Byte, InfoWorld, Compute! that showed you a bit more than just the specs

Then there were books, including the X for Dummies series that purported to teach you theory and practice

Then there was Google / Stack Overflow and friends

Somewhere along there, where depends a lot on your age, there were school / University courses

Now we have "AI mode"

Each step along that road has offered a significant speedup, connecting ideas to theory to practice.

I agree, all the "magic bullet" AI hype is far overblown. However, with AI something I new I can do is, interactively, develop a specification and a program. Throw out the code several times while the spec gets refined, re-implemented, tried in different languages with different libraries. It's still only good for "small" projects, but less than a year ago "small" meant less than 1000 lines of code. These days I'm seeing 300 lines of specification turn into 1500-3000 lines of code and have it running successfully within half a day.

I don't know if we're going to face a Kurzweilian singularity where these things start improving themselves at exponential rates, or if we'll hit another 30 year plateau like neural nets did back in the 1990s... As things are, Claude helps me make small projects several times faster than I could ever do with Google and Stack Overflow. And you can build significant systems out of cooperating small projects.