i dont understand that. i use ai for help reading through old stuff or to help me remember how tondo a thing i havent done in two years but blindly copy pasting blows my mind.

I worked with a guy that 100% used AI to dev everything. didn't even check to see if it would work before submitting a MR.

It got to the point that I stopped reviewing them and just rejected them outright with a simple comment, "doesn't work".

eventually he was fired. the evidence? the four months of shitty MRs he opened. the best part was, when I said "doesn't work", I was never wrong. none of his changes worked.

The lazy part is not questioning the bullshit they noticed and did nothing about - not using the tool

I know it's because LLMs are bad at what they do, but I like to imagine that all these weird things getting slipped into code are an attempt to create skynet without us noticing

Yeah these interaction are becoming quite fraught because there is extreme danger of AI use just shifting the burden from one person to another. That guy wrote the code super fast with AI, but you had to do an additional round trip during code review with him to eliminate that weirdness. He gets a bonus for doing twice the work in half the time, you get nothing.

blame your leadership

he’s not getting paid for good code

There was nothing wrong with the code in terms of structure or performance, but it was doing this really weird operation with an ID after DB insert

So there was plenty wrong with the code.

And it hasn't been fixed.

"Bro, its totally just you prompted it wrong"

I mean, the pull requests will arrive.

Especially if they are security related, even if only 5% are anything, that's still quite a few actual bugs. 😞

The Shawshank Software

Good engineers will produce more good code, because they ask the right questions, know what good looks like and check the output.

Best code is the code that is never written in the first place. But that concept is difficult to explain and measure for management purposes. Just because "AI" can automate well-structured, tested boilerplate for "good" developers does not mean all that boilerplate should be there.

Bad & meh engineers get praised because they "waste" less time directing ai and reviewing output - barely working is good enough in the race to market.

I've seen things as serious as a privileged user for one customer having admin access to all customers being discovered during the last minute pentest literally days before the planned product launch. That product is supposed(and likely will) to move 250M USD for customers in the second half of this year. Under the current policy at my day job, coming all the way from the top, reviewing ai generated code at all should be an exception reserved for 0.1% most critical code. Yes, in finance.

It can work as you say, but some companies are pushing 10x (or whatever) with fewer people, so quality is guaranteed to go to shit.

I've read that because they have less and less experience actually writing code junior developers are having trouble analyzing the code produced.

Nah, good engineers are retiring, bad engineers are running rampant. You give yourself away calling us engineers, we were never, except for some yearly title increase instead of money. Just programmers, and that is fine. Engineer is a whole other thing from the steam age, my BSc was in Math, worked fine to get me in.

Provlem being is that it is not an equal amplifier.

Good engineer spends a morning going back and forth and maybe gets something done that wild have taken them all day.

Bad engineer puts first draft slop in production in a couple of minutes.

Bad engineer gets to put out something every few minutes, good engineer works too make it actually right instead of merely looking specifically right.

Good engineers will produce more good code, because they ask the right questions, know what good looks like and check the output.

So what's the point then ?

There have been coding frameworks like game engines for decades, if system coding is beyond your ability.

If AI can't write usable code from the start its worthless.

No it's not because it causes brain damage. If you look at slop all day you no longer produces good code even you're good engineer, you're producing slop code because your standards keep getting lower and lower until you become bad engineer but you even haven't figured it out. If good engineers would produce good code with AI we would have working software. Look how quality of software lowered after AI. We used to say that developers from coding bootcamps were bad now we're lowering standards even more to praise investors.

exactly; well said

We can definitely use AI to write good code

Get a different job. Now!

Until it doesn't and you don't understand the code.

There can be different reasons for different people. I personally have zero fear of being laid off (strong worker protection laws in Germany) and finding a new job this year was surprisingly easy (50-ish applications with no cover letters -> 3 interviews -> 3 offers) and I still feel the exact dread that is described in the article. The industry sucks in multiple different ways rn.

I see an LLM as my good-but-not-perfect assistant, there to code up boring bits "loop thru this data and extract...", "improve this bit of code please", and to help with errors "why does this code give that error".

I never let it do big slabs of code, and always run and check its code incrementally.

It is my code and the LLM just makes it easier to do. Thanks LLM.

I recently helped evaluate it for company use. My test considered of vibecoding an App that takes a Pipewire screencast and does some basic image processing on each frame. In C#, which doesn't have great options for talking to Pipewire. I did several runs with various iterations of Claude.

On the upside, it had few problems navigating DBus to negotiate a screencast handle. So that's one annoying API out of the way.

On the downside, all attempts at taking to libpipewire through P/Invoke failed, usually because Claude hallucinated parts of the API or set constants to incorrect values. I only got a working program when I allowed the use of a prerelease Pipewire NuGet package.

The generated code was of acceptable quality but I wouldn't allow it into a codebase without a refactor. The code has zero consistency and one time the whole solution didn't have any namespaces. The fact that the LLM writes and rewrites the code during a single prompt means that you can get mild spaghetti as an initial state.

Honestly, I can see it for something like rapid prototyping or implementing basic scaffolding for an annoying API. But damn is Claude bad at detail work.

Yeah, I use it to spar with when deciding on solving something. I ask it what are the domain-or-language-typical, idiomatic or best-practice ways of solving something. I trace errors by using AI. I even take whole-sale code it produces if it isn't "serious" like just wanting the HTML or CSS lines that will do the trick.

It will definitely suggest things that I don't think are correct and then I ignore it. It definitely wastes my time sometimes. I definitely don't learn things well enough when using it. But I only have so much time and too many problems I need to solve.