buttplug.io 🍑🔌I really cannot stress enough how much of an unexpected marketing gift the term "vibe coding" has been for us.
sinister@buttplugio what the heck is vibe coding?
Patrizia@sinister @buttplugio Throwing prompts at generative AI until it does the thing you want. It's explicitly not about understanding what it does or worrying the code quality.
@patrizia @buttplugio at this rate should i even learn how to program? Its been years ive not made much progress lol
@sinister @buttplugio Only you can answer that, but I don't expect programming jobs to go away - a lot of trouble gets caused when nobody understands or cares about the code :)
Some open source projects are be plagued by users submitting AI-generated patches and security reports that are invalid, because the user didn't read, understand, or investigate what the AI spat out.
Alan Miller 
🇺🇦@patrizia @sinister @buttplugio it's been a long time since I considered myself a coder, but my feeling is that AI generated code will be acceptable for the 90% that's not edge cases. It'll have problems with the 90% of code written to deal with the edge cases.
Cassandrich@fencepost More like 10%.
Klaus Frank@fencepost @patrizia @sinister @buttplugio
But the 90% case is done in 10% of the time you spend on the code. IntelliSense and tab completion do already everything you need. AND you don't get into a situation where you're wasting hours to find a bug in a section of the code that you don't even know what it is supposed to be doing.
Frank Heijkamp@fencepost @patrizia @sinister @buttplugio Programming is mostly about proper handling of edge cases. Everything else is just straight through. The straight ends are easy, it is the corners where you spend most of your time figuring out how to make it work.
Ludovic Archivist Lagouardette@fencepost @patrizia @sinister @buttplugio that would mean that a project with 10 AI patches would have 65% chance of having a critical error that could have been caught by understanding the code, and with 30 ai patches that goes to 95%. If a human coder that understood what they were doing had a 3% error rate, 10 patches would mean a 25% chance of a critical error slipping in, and after 30 patches that would be 60%. That would be if the human didn't reflect on their previous patches and use unit tests (which people that know what they are doing do)
vampirdaddy@fencepost @patrizia @sinister @buttplugio
Debugging is 90% of the time you are spending. The first raw program text usually is the fast part, unless you work really hard on optimisation problems - which is another weak point for AI.
AI is trained to only shows the most common text in the context given - neither the most elegant, nor the fastest, most robust nor most correct program.
Myrakel@fencepost @patrizia @sinister @buttplugio
I tried it a few times now but I never(!) got a result that was usable. Maybe it's possible to let the AI write a well-known mathematical algorithm - but everything else seems to be completely non-working nonsense.
It starts with not compilable code, continues with hallucinated libraries and enumerations and ends with agreeing to be unable to solve the given problem in a working way (or just repeating the steps again and again until the user stops).
I tried it a few times now but I never(!) got a result that was usable. Maybe it's possible to let the AI write a well-known mathematical algorithm - but everything else seems to be completely non-working nonsense.
It starts with not compilable code, continues with hallucinated libraries and enumerations and ends with agreeing to be unable to solve the given problem in a working way (or just repeating the steps again and again until the user stops).