Plenty of accomplished devs are getting good results and accomplishing tasks with unheard-of speed using AI, so if you're still not, that's a PEBKAC. You are not using the tools correctly. Figure it out before you complain.
Plenty of accomplished devs are getting good results and accomplishing tasks with unheard-of speed using AI, so if you're still not, that's a PEBKAC. You are not using the tools correctly. Figure it out before you complain.
Absolutist rubbish.
> "But even those open source projects with significant user bases that forbid the use of AI [...] will be eclipsed by those that support it in terms of features, capability, and security."
As is this. If a language model is relevant to a project, open source or otherwise, is of course heavily dependent on its nature (ethics, use case, deployment, working environment/culture, et cetera).
So the issue isn’t LLM productivity but unrealistic expectations that skyrocketed in the last years? Makes sense.
> Plenty of accomplished devs are getting good results and accomplishing tasks with unheard-of speed using AI
I don’t see any major business impact.
???
>You are not using the tools correctly.
Stop being deluded, man.
When this crap collapses into itself you will be in tears back asking for the knowledge you failed to get without the fancy Clippys.
Now, stop that fancy Megahal chatbot and learn to do things by hand.
Yes, model collapse is gonna suck. But LLMs are not just left to self-train, they are guided by human researchers who are going to find ways to groom and direct the models to avoid collapse. They can make billions by shipping better models, so why wouldn't they invest a lot of effort in that?
And I'm fully convinced that what I do will not just be a little bit better than what AI Al makes. It will trounce it in all quality criteria. But of course, coincidentally with the rise of AI assistance, software quality has completely disappeared from the conversation. I wonder why.
The lifespan of software can easily be ten or more years.
If it takes a few more months to write by hand to ensure correctness and proper abstraction, what does that save over the lifetime of the codebase?
You should’ve started with this. Take a really deep breath, take your phone, find closest park, go slowly there (don’t prompt LLM on the way), find a green patch on the ground (it’s called grass) and touch it.
Strange, I don’t see any punchcards inside of my computers, but for some reason I still see code behind anything that LLM does.