Fucking snow flake anti ai nerds, like you weren't just pressing keys all day anyway, who cares if now it's just one key??
/s
this post was submitted on 23 Sep 2026
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I'd have more sympathy if he got off fucking twitter tbh
My company made my job soul-sucking to the point I was doing the bare minimum a long time ago. They didn’t even need AI for that. Just some really shitty managers.
Same!
AI code assistants currently are like that senior dev who knows everything, has experience in everything, and always likes to help everyone. But sadly he does a lot of shrooms in his spare time and sees things that aren't there. He also has quite the opinionated ideas about what good code should look like.
That implies that you just can't let him do the quality assurance. He can write code. You can ask him stuff. And he excels at debugging.
But you can't let him plan the architecture. You can ask him about his ideas and select the ones that are actually good, though.
And you definitely can't let him review his own code. Someone else has to do that.
So if they literally just let the AI do everything, there is absolutely no way anyone has a chance to ever review the result because AI code is harder to review (for now), and AI loves to repeat itself (for now).
And sure, they can tell it to write tests. But AI is dogshit at writing tests. It tends to forget the important cases, test the wrong thing, and/or obsess about completely irrelevant implementation details.
I also tried the multi-round approach with a committee of agents trying to iteratively find and fix flaws. It only works well for finding bugs, not fixing them (for now).
But while AI can't replace me, it is really nice to have as a tool - just like I have syntax highlighting in the IDE, I have a code assistant that can autocomplete a few lines of code, find out why my code misbehaves, or tell me what some library method is supposed to do. Sure, I have to still verify the results. But often, finding the bug or information was the hard part.
Coding assistants are great. Just don't let them write too much code at once. You need someone who still actually understands the codebase. That sadly can't be an AI (yet).
AI code assistants currently are like that senior dev
More like a junior dev.
I really love when I ask the AI to do something, and it gives me 40-50 lines to do it, and I tell it there's no way something like that should take that much code, and it's like oh, ya you're right, here's a 5 line version using something from from the standard sdk.
I've tried to put in its memory to not do things like that, but it keeps doing it.
I watched it remove a JSON library include from the code because it wasn't used yet, and then in the very next prompt where we needed our again, it attempted to write a basic parser from scratch...
Brilliant.
Ive had it do stuff like that completely ignoring that I already have a library in my app that should handle some sort of task. But removing it first is chefs kiss.
I guess the AI isn't iterating over its "ideas" and code yet. I come up with overcomplicated and overcomplex code too. But my natural neural network keeps reevaluating the code while I think about it, write it down, test it, and often even come back to it later after I moved on to another part of the codebase.
It looks to me like AI is using the infamous waterfall method to write code. It does the "thinking" phase and does bugfix iterations when compilation or tests fail. But never does it question the design it came up with after it wrote it down. It doesn't reevaluate whether the last round of fixes made tests work that test irrelevant implementation details. It doesn't question whether there really need to be four methods sharing 90% of their body for doing the basically the same thing only subtly different.
I hold the suspicion that AI will be as slow as humans when it becomes as reliable because what makes us reliable is the redundancy in our thinking processes. The constant reevaluation in subtly different states of mind helps to catch design flaws and silly mistakes.
Reevaluation of finalized code is probably not something you can just put into memory. You would need to modify the harness to automatically inject a new prompt triggering reevaluation of the design and implementation after each step. This would likely increase token use and execution time by an order of magnitude. And if you do it by spawning fresh agents, there would be a high chance of having the AI go in circles, switching between a few different versions of the same shitty design or implementation. So you need to keep the context, which grows each iteration. So context rot may become a real problem. The AI might deviate from the initial goal just like some human devs tend to do...
And natural neural networks learn on the job. They adapt to the codebase and industry they are working with/in. claude.md and memory text files help a lot. But they are still sometimes ignored. And I don't know why. Also, human rules are almost always somewhat fuzzy. Long lines are to be avoided - but unit tests and that one massive dict of dicts really are a lot more readable when ignoring that rule. There might be a lack of good training material on what makes code readable for humans.
That actually makes a lot of sense and goes with how ill code something larger as well.
Get a rough version working, sometimes horrible code. See how it functions. Reassess it and optimize it. Go bug hunting, which will often result in more optimizing, then finish all the error handling I probably skipped and only logged. More bug hunting, then review my code like a code review before submitting it for a code review.
Possibly motivated to do more complex problems to spend more tokens?
I can believe this. I've been put on slop duty, and had the slopmachine go all
Time to run the test to ensure everything is good. It passed. Good. Let's run the entire suite to ensure no regressions. All tests passed, yay.
And I'm here thinking, if you're gonna run the whole suite anyway, why'd you run an individual test? That's just redundant.
Even without external libraries, it routinely comes up with solutions that are at least 3-4x the complexity and LOC than how I would implement it.
It's because the average quality of code that they are trained on is like that. Most code that is written by humans is slop, and the models represent that.
Producing overly complicated solutions to uncomplicated problems
This is maybe the main reason why I don’t fuck with AI. “Oh it accesses all of the writing on the public internet!” That never inspired a lot of confidence. 99% of Internet posts are crap.
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The engineer added that employees are now pressured to ship products as fast as possible, leaving them with little time to review Claude's output or understand the code being created.
Companies have always pressured software teams to ship products as fast as possible.
What's new is the part where all of the worst coders can shit out code a lot faster and pretend like they're doing a good job. It used to take them a while to write garbage that they didn't understand or review themselves, but now they can do it so quickly that it makes the actual good coders look like they're taking a long time.
This is why you absolutely have to have documented coding and review standards. The idea that you'd ship any code that has never been reviewed by a human is horrifying.
The idea that you'd work 12 hour days is so stupid to start with. I've seen people consistently work that long and... surprise, they don't actually work that long. They work about the same as anybody else and goof off the rest of the time. I doubt you can even just press enter for that long. People just don't work that way.
AI in engineering is an accelerator. If you are producing slop software, which most teams are, then it's just going to accelerate the rate at which you can produce shitty software and bad code.
If teams are producing high-quality software, then it accelerates those teams' ability to deliver that quality.
AI in engineering is an accelerator.
Yes, and most engineers effect on the product can be graded on [-1, 1] scale. And I find that the -1s accelerates faster.
If teams are producing high-quality software
I had one of those. My seniors are getting dumber though, and we have twice as many prod bugs as a year ago. I had an outage because someone didn't properly trim an input for fucks sake recently.
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I don’t hate Claude Code or whatever. I hate the company pushing you to constantly churn out shit so you need to turn to these tools to keep up pace or get fired.
Architecture decisions or code quality? Fuck it just ship.
You have concerns about an approach? You’re the enemy to your coworker’s promotion. Get out of the way.
It’s all just so depressing. It will all come crumbling down. It’s a matter of when not if. But god I hate this ride right now.
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