Comment by echelon
8 hours ago
The maintainers can now do all the work themselves.
With the time they save using AI, they can get much more work done. So much that having other engineers learn the codebase is probably not worth it anymore.
Large scale software systems can be maintained by one or two folks now.
Edit: I'm not going to get rate limited replying to everyone, so I'll just link another comment:
No, because proper QA/QC will be the bottleneck.... AI is ill-suited to test for fit/use. I built an ANSi terminal with AI assist (rust/wasm/canvas)... it literally took longer to get the scrollback feature working with keyboard and mousewheel interactions than it took to get the basic rendering correct. And there are still a few bugs in it.
In the end, you should not just skip QA/QC and fitness testing. Many things can fit a technical spec and still be absolutely horrible. With AI assisted developmnet, imo it's that much more important to get the UX right. I don't want 10x the apps if they're all half-implemented garbage that look like garbage are hard to use and just painful to install, maintain and use.
Library creation still has a place here... and so far, getting AI code assistants to actually understand and use a given library that may be less popular has been at the very least, interresting.
Do you have anecdotes or evidence of this or is it speculative?
Those are the most mentally exhausting task. Are you sure putting this burden on single person is good?
Yeah, it should change things but also free up other energies to work on things
> So much that having other engineers learn the codebase is probably not worth it anymore.
> Large scale software systems can be maintained by one or two folks now.
No, LLMs are not so powerful yet.
Not sure if you're being sarcastic or not?