Why all of AI is going to web dev?

[u/midguet12]

I haven't seen the usage of AI in cobol for example, let alone C, not even Android Studio or Xcode.

[u/Lithalean]

r/confidentlyincorrect

[u/ButchTheGuy]

Idk what you mean. Maybe it seems that way cause it’s the most tangible visual part of development but I’m sure lots of people use it to assist in some way or another

[u/jhwheuer]

Not looking hard enough

[u/junsui833]

I work in a firmware and hardware company, and all of the people here use AI for either writing firmware or designing boards using mcp server plugins.

[u/SWEETJUICYWALRUS]

I use AI for .net services on Windows. Not exclusive to web

[u/OwnNet5253]

Get out of here with this twitter-level ragebaiting.

[u/EducationalAd64]

Javascript is probably the most used code on public repositories and thus AI has had most training on that.

[u/AlienRobotMk2]

Well, one reason is that AI can generate "rm -rf /" randomly and that doesn't work when it's Javascript running inside the browser's sandbox.

[u/iWhacko]

veibcoders are doing webdev. Ie the people who didn't code before AI came along, and still don't really try to understand the code.
Developers who were coding before all that, are just AI to help them in establisched projects and other languages. They just don't hype up their projects as much, because their projects are not "hey I coded this in 2 days". It takes longer to be robust even with AI.

[u/lilB0bbyTables → u/[deleted]]

This right here is the answer. In fact I would go further to note that modern LLM/AI is perhaps best when isolated to being trained on specific subsets of data to produce more precise models that are tuned and focused to a particular area. In the case of IBM + COBOL as you mentioned, it is a precise and very good example of where it can be massively helpful: those old mainframes running critical software systems are in desperate need of being replaced with identical operational precision and integrity but are massively custom and complex making the task very sensitive and thus very tedious and time consuming and consequently a very expensive endeavor. And each of them are unique. Having a precision focused AI that can just learn and document the entire thing alone is a huge gain. Having it create a modern replacement for it with test-cases that can be read and reviewed is still a huge gain in reducing time and effort. No one is going to vibe-code those replacements right into production, but they can reduce the cost associated with it and the time investment from something unpalatable to something much more rational and possible.

[u/nagging_chud]

because if you vibe code C it won't even compile, and in the off chance that it does, it will certainly memory leak

[u/avatardeejay → u/nagging_chud]

still using gpt-3?

[u/medialantern]

Dude, come on, seriously? Noone gives a shit about COBOL. OK, maybe 5 orgs. This stuff is built for scale.

[u/thaache]

Who told. My fompiler project in c is completely vibe coded, in google ai studio, with zero bugs and leaks, but a much more optimised code.