Software Engineers
Oftentimes I wonder what civil or mechanical engineers think about webdevs-turned-prompt-writers calling themselves "engineers".
this post was submitted on 14 May 2026
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Pissed.
Every real engineer I have ever talked to gets pissed when a key board jockey calls themselves engineer. Regardless of AI or not.
Coders arnt engineers never will be never have been. The engineer title was straight up stolen and misused by corpos and idiots to fluff up their egos. The entire term software engineer is a bullshit title for idiots who have zero respect for actual engineers or are toadies to mega corpos and sold their self respect for a bigger pay check. Prompt engineers are even worse and frankly fuck em all.
They as much engineers as a 3 year old is an engineer when building with Lincoln logs.
Things I've realized while working with AI (Claude code):
- It's fantastic for very small macros and medium length scripts. Think dev ops stuff, pre-commit hooks, transforming data. Keep it small enough to manually review and something you can run without destroying anything important. This can massively boost your codebase QoL. [Double bonus for not wasting tokens to solve the same problem over and over]
- It's decent-to-good at debugging but not consistent with fixes. It can find some utf encoding edge case that might have taken you 1hr+ but suggest the dumbest bandaid fix you've ever seen. Also very good at spinning up unit test suites for basic edge cases.
- Due to obvious training bias, it's pretty good with common libraries and cloud platform infrastructure. It could probably help with writing a complex cron call, debugging regex or fixing an IaC config. On the flip side it won't bother to use the latest package version or know your niche/new library.
- It does better with greenfield because exploring your codebase introduces a ton of bias. It might try to fit in an ugly hack when a refactor to simplify everything is way easier.
- It's absolutely garbage with UI, just throws the most disorganized HTML together that isn't reactive or reusable. OK enough for ugly internal stuff but God help anyone relying on it for that.
- This is setting up to be the biggest rug pull in history. People that buy into it heavily just to save a couple bucks on engineer payroll are going to be fucked when they start ratcheting up the token price.
All in all it can be useful when used with care but will never be a magic bullet.
Yeah, fully agree with all that.
I've got some godawful spaghetti code I don't understand fully, and it's pretty good at deciphering that and the bizarre labyrinth of code paths leading around it. But it's absolutely no guarantee of working code, and in any project larger than a simple crud app, you are going to still need programmers who know about things like memory and databases.
It often needs pointing at a solution you want, because as you pointed out, it's fond of dumb band-aids. Like yesterday when it was trying to hook into mouse wheel events and create separate threads, when all it needed was an event on the dataset I was using to load a sub-dataset.
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That’s the problem. This is one of those things that you gain momentum in, not simply experience. You can lose that momentum.
Tech bros are going to end up enslaving us to this shit.
Solution is simple, learn to code.
ha
Nah, AI isn't that good. When you don't properly review every single line twice, you get the most absurd bullshit you've ever seen.
I use Claude Code Opus daily btw.
That's the funnest part. You loose your ability to code, and you do it by using thing that isn't even that good, and you don't get anything out of it. Isn't that great?
You forgot that you'll work for less salary because "work has become much simpler, every intern can do it now!/s"
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Oh no... who could have... possibly... foreseen this...
We use it at work and I now have disabled it for all the typeahead stuff. Far too many times it guesses what I am doing incorrectly and it made using my TAB key (which inserts the propper two spaces) impossible.
The only place I still use it is for reading and identifying compiler errors. Even then it is only about 50% correct as most times it falls into the "Oh you are right, X isn't the solution. Have you tried X?" I have had few bad interns and even they were smart enough to not forget what they said in their previous sentence.
This is why I've never tossed any of the developer bookmarks
I've been training new hires how to look stuff up on stack and dictionaries to fix code that went wrong after AI mucked it up. They aren't even being trained to parachute in school.
What a sad time line we are in.
Lol! Losers. I've been programming for almost two decades and extensive use of AI hasn't compromised my skills AT ALL! These slop machines can't hope to compete with the quantity and magnitude of subtle bugs I write. My code was terrible long before I made bots have mental breakdowns trying to work with it.
AI also gives you the benefits of a middle manager. If everything works as intended you take the credit but if something breaks that's not your fault, AI made the mistake. If they try to put the blame on you just say you have 6 agents working on 6 different domains all cross-reviewing their commits and you can't be expected to review every single line of code yourself. Time to play corporate like a damned fiddle!
It really is like having your own personal trainee.
If it only could make coffee.
See this is why we need smart appliances, so AI could make you coffee.
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It feels like relying on GPS while driving around. If you know the roads well and just want some help with live traffic or somewhere you haven't been before, it's a decent tool.
If you rely on it because you don't want to think and just want to press the easy button, you're going to have a bad time sooner or later.
Back to software, I think there are a lot of people introducing concepts they don't understand or can't maintain (either from poor quality slop or it is just too advanced for their current level of understanding). You can do a few turns like this, until you're stuck burning tokens in a loop without moving forward in a meaningful way.
I try to avoid taking the easy route myself unless I've burnt too much time stuck on some small detail. Ultimately I feel it is super important to understand what you are delivering. Whether it is writing it yourself, copying a stack overflow post, or using an LLM. Once you commit and push to prod you've got to deal with that crap.
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Its a silver lining of AI that you can easily tell whos a big baby idiot and whos actually worth engaging with.
Preach.
The AI "revolution" is the thing that finally killed my imposter syndrome as a software engineer. Not because I can write better code than AI (that's a very low bar), but from listening to all these breathless idiots talk about how they're "10x-ing my productivity!" or how "AI has replaced search for me!" or how "In 6 months no one will have to manually write code anymore!"
In 6 months no one will have to manually write code anymore
For the last 18 months
Same timeline as Tesla FSD
Fr, I've never felt more confident about my coding capabilities and I've even picked back up some old projects I had shelved indefinitely due to tha syndrome.
Now every shitty line of code I produce feels like polevaulting over 1000 other future applicants on my career path lol
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Similar for me. What i find ironic is that AI already ran into a brick wall. It's inherent statelessness by design means that AI is unlikely to be suited for anything more than isolated well defined tasks in the near future. Still usable as a tool, but without someone who is actually experienced, it will result in disaster.
and even in smaller tasks it can fucks up, especially if the person prompting it is incapable of writing the code themselves as they don't know how to properly design it and don't spot the issues. Like everything with AI, it looks impressive at first glance until you look at it for more than 10 seconds and spot the metaphorical 6th finger.
What we see currently with AI getting "better" at coding is more or less duct tape to make it work. Basically, they create the agents to bolt on the state, more layers between user and model. Iterative processes to make the answers better, etc, and to create "memory", which in essence is just an ever growing prompt managed by the agent. But in the end, this won't fix the inherent problem, so it will only do so much and is already hitting another ceiling. It introduces state decay. With the agent method its not really possible to "take away" memory, so if you gave it multiple versions of the same code (as you would if you work with AI), the AI never really forgets about old code. It can supress it through agent instructions (more duct tape), but the more there is the more it bleeds through, which can make the AI reintroduce old code or base assumptions on outdated things.
There is no fix without changing the inherent way how models work, which would introduce complexity beyond what is currently feasible in computing (and the current AI is already gobbling up all computing reaoureces as is)
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I weap for the environment and our future water and electricity availability.
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You still need to review and verify the code, actually implement it, and improve it if you use AI.
If you just blindly accept it then you're just lazy to begin with.
(X) Doubt
As a Sr. Engineer, I completely get that my situation may be wildly different from what's cited in the article.
Right now, I'm using AI "in the loop" rather than "as the loop". That's a big difference. And I'm getting my ass kicked routinely on review for dumb-ass things that I'm letting slide from AI generated output. And rightly so. Plus, models routinely lead me down sub-optimal blind alleys while dreaming up really stupid ways to fix problems. The level of (re)prompting I have to provide to suggest to get decent quality results converges on a post-grad that has encyclopedic knowledge of software engineering as it exists online, but with zero real-world experience. It's both impressive and dangerous as a replacement for software engineering.
In the mode I describe above, I'm not losing the ability to do anything. I can see how one could surrender some coding chops or familiarity with a whole language or stack, in favor of automation. But all you have to do is not do that.
I will say that as a rapid-prototyping technology, It's nothing short of miraculous. I've watched junior engineers knock together medium-weight applications, complete with browser UI/UX and decent workflow, in less than a week. This is great for showing value or putting something semi-functional in front of management and/or customers. But pivoting those prototypes into something maintainable is an utter nightmare. Depending on how beholden to AI and forever prompt-looping with "skills" and MCPs you want to be, I suppose it's possible to just keep mashing the AI button. But at some point, you're going to need to get inside there to fix security problems or bugs that elude this workflow. What then?
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I notice getting lazier. Even adding a. gitignore file I ask Claude now. It takes longer than typing it myself and costs more probably. But I don't have to do anything but wait a few seconds.
If I was paying for it, hell naw. But if my employer not only is willing to pay for it, but considers it a performance metric? I'm going to use it for fucking everything. These are the incentives they give me, I'm going to follow the incentives. Talking to Claude is what they pay me for, apparently.
But like the article says, if I don't continue practicing on my own code in my unpaid off-work hours, I imagine I'd be regressing in my skills too. I do that because I enjoy it as a hobby, but if I didn't, I could see myself and probably a lot of other people getting rugpulled by this.
I'm not using it for the incentive. I'm using it to avoid punishment. The company I work for made it mandatory to use it daily. So I'm tokenmaxxing bullshit tasks so I can focus on interesting ones, but yeah I already feel it's making me lazy because I sometimes can't be bothered to read a log anymore. We are truly fucked.
This company is working on terrible assumptions. They spent years hunting for the best engineers in the country (or so they pretend to anyway) and suddenly decided that
- we are average at best and it is better and faster than most of us (it's not)
- software engineers don't like to write code anyway (we do, at least when the challenge is interesting)
- it will forever be more affordable than properly qualified engineers (oh boy it won't)
- a PM with Claude is as qualified as us to bring features to production (talk about tech stack suicide)
- etc.
They either have drunk the propaganda koolaid and betting everything on this lie, or are so arrogant they think we can succeed where the largest AI investors in the world utterly failed (see GitHub that can't even get 3 nines of availability since the switched to full-ai-code).
The thing that scares me (and why I've stopped using it): my brain automatically reaches for the shortcut whenever I would have to do deep thinking/planning.
I have ADD, so getting my brain to focus and work on a task is not an easy feat to begin with. Now I've found myself multiple times a day unable to will myself to think about a problem but rather deferred to Claude. It's seriously fucked up.
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Hot take: they had no ability to code in the first place.
I've worked on a cloded codebase. It's not... uh, good.
I just don't get it, even the purportedly best models screw things up so much that I can't just leave them to the job without reviewing and fixing the mess they made... And I'm also drowning in pull requests that turn out to be broken as it proudly has "co authored by Claude" in it... Like it manages to pass their test case but it's so messed up that it's either explicitly causing problems, or had a bunch of unrelated changes randomly.
I feel like I'm being gaslit as I keep reading that there are developers that feel they successfully offloaded the task of coding.
Closest I got was a chore that had a perfect criteria "address all warnings from the build". Then let it go and iterate. Then after 50 rounds each round saying "ok should be done now, everything is taken care of, just need to do a final check". It burned though most of my monthly quota doing this task before succeeding. Then I look at the proposed change... And it just added directives to the top of every file telling the tools to disable all the warnings... This was the best opus 4.6 could do...
Now sure, I can have it tear through a short boiler plate and it notice a pattern I'm doing and tab through it. But I haven't see this "vibe" approach working at all...
I feel like I'm being gaslit as I keep reading that there are developers that feel they successfully offloaded the task of coding.
That's because you are being gaslit.
The people making those claims are either a) not developers in the first place, with no awareness of just how shit the "products" they're pushing are, b) paid astroturfers trying to prop up AI, or c) former actual developers who've become addicted to the speed that's possible with AI who are downplaying how crappy their own code quality has become because they have no familiarity with their codebase anymore and have forgotten how to do so much as a for loop.
All these people claiming 10x or 100x gains, and everything they're making is garbage no one should or would touch with a ten-foot pole.
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For those unable to code without AI:
What even is your contribution outside of a glorified typing monkey that can parse code but is unable to write it?
It's like a paramedic not being trained at all for a medical emergency response but sent there regardless to just stand and observe the patient while writing notes about the sounds they make while dying.
So this is going to invoke a multitude of downvotes, but here goes.
I will give you an example. I can read a bit of python code, not the advanced stuff, but enough to understand to a large degree what the code does. Last week, I had the need to add a button to Netbox that will download a multitude of device configs that are being rendered via config templates. This use case helps a whole department apply configs, without having to create them by hand.
I knew Netbox has a very powerful plugins ecosystem. The way the base code is written grants the capability of adding any type of plugin you might need in your unique environment. I used Claude to create this plugin for me. I wrote a very specific spec file, told it to utilise the already built pynetbox plugin and ensure it uses nothing fancy that is not sustainable. It created the plugin, helped me with pip installing it, and I deployed it on my dev environment where I tested it extensively.
My alternative to using claude: Asking our internal development team to write something like this. I would need to wait 3 weeks to even get a spot on their meeting for the request, just to then be told their backlog is full with customer code and they won't be able to help. This plugin will help our support team with fewer calls, because the configs are accurately built according to the source of truth (Netbox) and will need less human input. So in the greater scheme of the company, that is a net positive.
What I will do when Netbox updates, is update my dev environment, install the plugin, and test it. If something broke, I will troubleshoot it, of course I will be using Claude with error logs etc, then update the plugin code to work on the new netbox. Is this ideal? Probably not. Is it the only way to get this done? Maybe not either. Is it all I can do at this very moment? Yes.
My specialist fields are the lower levels. Hardware, hypervisors and setting up VMs + System Software. I need code from time to time to get something functional done. I don't write whole systems with Claude, that is just ridiculously naive. But small pieces of functional code that solves a single small problem, I honestly don't understand the problem with that.
My 2c.
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I want to become a software entomologist, you know, so I can study all their bugs.
Being able to call out a middle manager that if these tools are really so great he can just open the PR himself is pretty awesome though.
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