Can you confidently say that an LLM won’t be better than an average 22 year old coder within these 30 years?
It's not as out there as e.g. this article (https://www.wsj.com/articles/SB10001424052748704206804575468...) - 7 careers is probably a crazy overestimate. But it is >1.
Too many people here have spent time in elite corporations and don't realize how mediocre the bottom 50th percentile of coding talent is
Either AI shatters this charade, or we make up some new laws to restrain it and continue to pretend all is well.
However, there is no good reason in a free society that this stuff should be widely accessible. Really, it should be illegal without a clearance, or need-to-know. We don't let just anyone handle the nukes...
Skills aren't even something that dictates software spend, it seems.
I'm trying not to look at it as a potential career-ending event, but rather as another tool in my tool belt. I've been in the industry for 25 years now, and this is way more of an advancement than things like IntelliSense ever was.
No 22 years old coder is better than the open source library he's using taken straight from github, and yet he's the one who's getting paid for it.
People who claim IA will disrupt software development are just missing the big picture here: software jobs are already unrecognizable from what it was just 20 years ago. AI is just another tool, and as long as execs won't bother use the tool by themselves, then they'll pay developers to do it instead.
Over the past decades, writing code has become more and more efficient (better programming languages, better tooling, then enormous open source libraries) yet the number of developers kept increasing, it's Jevons paradox[1] in its purest form. So if past tells us anything, is that AI is going to create many new software developer jobs! (because the amount of people able to ship significant value to a customer is going to skyrocket, and customers' needs are a renewable resource).
I feel like the software developer version of an investment banking Managing Director asking my analyst to build me a pitch deck an hour before the meeting.
Compare that to Gpt 4o which gives me a massive chunk of unsorted gibberish that I have to pore through and organize myself.
Besides, most IBD MDs don't know if they're getting correct numbers either :).
What is hard is gather requirements, dealing with unexpected production issues, scaling, security, fixing obscure bugs and integration with other systems.
The coding part is about 10% of my job and the easiest part by far.
LLMs cannot decide what to work on, or manage large bodies of work/code easily. They do not understand the risk of making a change and deploying it to production, or play nicely in autonomous settings. There is going to be a massive amount of work that goes into solving these problems. Followed by a massive amount of work to solve the next set of problems. Software/ML engineers will have work to do for as long as these problems remain unsolved.