Look on the bright side, in a couple of years they will come crawling back to us, desperate for new things to be built so their profit machines keep profiting.

Current ML techniques literally cannot replace developers for anything but the most rudimentary of tasks.

I wish we had true apprenticeships out there for development and other tech roles.

No duh, says a layman who never wrote code in his life.

If not to editorialize, what else is the text box for? :)

More code is better, obviously! Why else would a website to see a restaurant menu be 80Mb? It's all that good, excellent code.

It did solve my impostor syndrome though. Turns out a bunch of people I saw to be my betters were faking it all along.

Yeah, code bloat with LLMs is fucking monstrous. If you use them, get used to immediately scouring your code for duplications.

I don't think it's meant to be a conclusion. The article serves as a recap of several reports and studies about the effectivity of LLMs with coding, and the final quote from Bain & Company was a counterpoint to the previous ones asserting that productivity gains are minimal at best, but also that measuring productivity is a grey area.

I found that it only does well if the task is already well covered by the usual sources. Ask for anything novel and it shits the bed.

There's some real perks to using AI to code - it helps a ton with templatable or repetitive code, and setting up tedious tasks. I hate doing that stuff by hand so being able to pass it off to copilot is great. But we already had tools that gave us 90% of the functionality copilot adds there, so it's not super novel, and I've never had it handle anything properly complicated at all successfully (asking GPT-5 to do your dynamic SQL calls is inviting disaster, for example. Requires hours of reworking just to get close.)

At absolute best.

My experience is it's the bottom stack overflow answers. Making up bullshit and nonexistent commands, etc.

At least when I'm cleaning up after shit devs who used Stack Overflow, I can usually search using a fragment of their code and find where they swiped it from and get some clue what the hell they were thinking. Now that they're all using AI chatbots, there's no trace.

In the beginning there were manufacturer's manuals, spec sheets, etc.

Then there were magazines, like Byte, InfoWorld, Compute! that showed you a bit more than just the specs

Then there were books, including the X for Dummies series that purported to teach you theory and practice

Then there was Google / Stack Overflow and friends

Somewhere along there, where depends a lot on your age, there were school / University courses

Now we have "AI mode"

Each step along that road has offered a significant speedup, connecting ideas to theory to practice.

I agree, all the "magic bullet" AI hype is far overblown. However, with AI something I new I can do is, interactively, develop a specification and a program. Throw out the code several times while the spec gets refined, re-implemented, tried in different languages with different libraries. It's still only good for "small" projects, but less than a year ago "small" meant less than 1000 lines of code. These days I'm seeing 300 lines of specification turn into 1500-3000 lines of code and have it running successfully within half a day.

I don't know if we're going to face a Kurzweilian singularity where these things start improving themselves at exponential rates, or if we'll hit another 30 year plateau like neural nets did back in the 1990s... As things are, Claude helps me make small projects several times faster than I could ever do with Google and Stack Overflow. And you can build significant systems out of cooperating small projects.

Sounds like vibecoders will have to relearn the lessons of the past 40 years of software engineering.

Wait, are you blaming AI for this, or yourself?

Lmao calling nobility would imply we can't vote our senior management and it often ends up being whoever "the king" wants or one of king's children.
Wait...

I mean, originally they thought they had come upon a magic bullet. Turns out it wasn't the case, and now they're going to suffer for it.

Writing new code is easier than editing someone else's code but editing a portion is still better than writing the entire program again from start to end.

Then there is LLMs which force you to edit the entire thing from start to end.

I thought that as well and got some code from someone that left the company and asked it to comment it.

It did the obvious "x= 5 // assign 5 to x" crap comments and then it got to the actually confusing part and just skipped that mess entirely....

I've used Claude code to fix some bugs and add some new features to some of my old, small programs and websites. Not things I can't do myself, but things I can't be arsed to sit down and actually do.

It's actually gone really well, with clean and solid code. easily readable, correct, with error handling and even comments explaining things. It even took a gui stream processing program I had and wrote a server / webapp with the same functionality, and was able to extend it with a few new features I've been thinking to add.

These are not complex things, but a few of them were 20+ files big, and it manage to not only navigate the code, but understand it well enough to add features with the changes touching multiple files (model, logic, view layer for example, or refactor a too big class and update all references to use the new classes).

So it's absolutely useful and capable of writing good code.

for me it typically don't cause syntax errors, but the main thing it fucks up is what you specifically told them to do, where the output straight up does not perform the way your specification requires. If it's just some syntax errors at least the compiler can catch them, this you won't even know if you don't bother testing the output.

Eh I had it write a program that finds my PCs ip and sends it to the Unifi gateway to change a rule. Worked fine but I guess technically it is mostly using the go libraries written by someone else.

I'm honestly doubting it will get there someday, at least with the current use of LLMs. There just isn't true comprehension in them, no space for consideration in any novel dimension. If it takes incredible resources for companies to achieve sometimes-kinda-not-dogshit, I think we might need a new paradigm.