I'm old enough now to be a protected class, so I don't want people accusing me of ageism, because that's not where this is coming from - but there's a type of person that clearly is on their last job of their career and knows it and I try to avoid them like the plague, I've seen it too many times.
Yup (and it's not ageism).
I'm young and stupid but forced by circumstance to practice a certain degree of respect for my own stupidity.
My philosophy is, "I write code like I expect it to outlive me".
Because sloppy work --AI generated or otherwise-- has a tendency to come back to haunt you.
The code isn’t for you. It’s for them.
Of course, there’s also a chance you’ll be them. :)
By the time the system starts to experience strain under the weight of its technical debt two years later, the original tech lead/architect of the project has already added it to his resume as another bullet point, found a new job at 20% higher comp, and no longer has to ever look at that code, ever again.
Now it's the next asshole's problem. Good luck!
[0] Freeman & Pryce 2009 for the "internal quality" vs. "external quality" dichotomy
They care a lot about prestige. Or at least did before AI. Don’t know what their current hiring practices look like.
Comfort yourself with the fact that you did not have to sell your soul, sit through endless woke sexual harassment videos where you are taught that the white man is the source of all evil, and in endless management meetings.
> sit through endless woke sexual harassment videos where you are taught that the white man is the source of all evil,
In big tech I had fewer trainings than any other org in my career, because they knew time was money.
I might be lucky (in a sense I am, but in another sense "all" I've done is work boring normal jobs and have low expenses), so maybe my path is not perfectly reproducible, but that's kind of the point of temptation: it has to be tempting. And quick, easy, sure money is the bait. You'll never even be held accountable. The only cost is looking around at the bad things in the world and knowing it wouldn't have been there without you.
Personally, the only reason I have to continue working these days is to give my kids a better future, so creating a hellscape for them to inherit would defeat the purpose.
Just study and get another job.
There’s always been a percentage of luck getting offers from big tech companies, but it’s way more luck than than merit it has ever been.
Sometimes the grass really is greener - company culture can be actually incredibly toxic and compensation very below market, but when surrounded by people who normalize it most folks will project that experience out to the rest.
I just approve PRs, because I have to. I don't know what else to do. I can barely keep an eye on all my code.
Actively looking, but job market is rough in Northern Europe. I quit caring about quality in any capacity here, the company has clearly chosen its direction, against my very vocal complaints.
My last interview, with what I thought was a great company, failed when I didn't understand what NLP was when they asked me about it.
> NLP? > Natural Language Programming, it's the future. Claude, GPT, etc.
I laughed, he didn't, looked offended and said it was a serious question. I had thought it was a joke, said "oh you mean LLMs". I tried to answer seriously, of course, but that was my third round technical interview and I didn't get a call back.
Just getting a paycheck and producing mediocre work until I get something new. (Senior engineer, 10 YOE, patents, 3 years at a unicorn).
Also considering becoming an electrician.
No one cares at best, or I'm callously told "keep up or fall behind" at worst. When that's not even the problem, it just, sucks now. There's no joy in anything I do professionally.
Can I ask where you went? I'm seriously looking for an exit, I just don't know what yet. Maybe a trade, in Scandinavia the pay is actually comparable, I just don't want to go back to school.
I never had a better time "professionally" (albeit no income yet!) so far in my whole life! Apparently it's truly like the best of times and the worst of times to be building software, if you have the luck and the luxury to be able to work only for yourself than it's really a great time to be alive.
It can feel that way with all the hype but I very much doubt that is really true. I see an industry that is rapidly dividing into two camps - "move fast and break things" and "this actually needs to work". Writing everything with agents and merging while barely even checking what is in the PR has become standard practice in the former but it will get you laughed out of the room in the latter.
For the latter, the product looks nice and polished on the outside but makes “steaming pile of crap” a gross understatement.
Often, the lack of meaningfully challenging demands being put on you is punishing on its own. It can feel like a relief for a week or month or year, but if you catch a glimpse of that being your whole future, you can come to recognize yourself as being in a mind-eroding secular purgatory.
This anguish is especially common among on highly capable people, high achievers, and those used to some kind of ambition. And by accident of its history, there's a lot of those people in this industry and some of them are going nuts now.
I went nuts for years, until I sold off my interest in my dream partnership.
10 years of heaven. All the benefits and none of the downsides of my internal colleagues. Then 14 years of bureaucracy aimed at predictability over progress, which was infinitely more difficult for me to dodge as an external player.
Compensation for my interest was very objectively valued, with the rate of stalled progress priced in. Which made complete sense, while also being its own madness.
I walked away from so much value, but I don't regret it for a minute.
Pretty much this. I know it sounds melodramatic but it literally feels like rotting.
I don't solve anything anymore. I don't get any spark of fixing bugs. I don't DO ANYTHING, and it's fucking chipping away at me.
Also I'm fairly sure people are going to realise soon that if they're happy with slop, they don't actually need highly trained engineers anymore.
This whole thread actually prompted me to look into electrician work, especially in renewables that we have here in Norway.
I might fix my burnout and go to school to get my 2 year qualification. AI can't rewire a hydro dam.
?!!?
No way. Are you sure? What kind of work? Here there’s still a lot of care needed to navigate the LLM work, like knowing when to make it quit, rewrite, refactor, follow your outline.
It feels magic but when I watch people who don’t know what they are doing trying to make something new (not almost a clone of an existing product), they get pretty frustrated.
https://en.wikipedia.org/wiki/The_Right_to_Be_Lazy
https://en.wikipedia.org/wiki/In_Praise_of_Idleness_and_Othe...
I can't believe how much mental justification needs to be made by otherwise highly intelligent people (Bertrand Russel wrote In Praise of Idleness) to defend the right to not work.
No, I fully reject any notion of life value coming from work, and those who hold your view are basically jailors to those who don't want our identity defined by work.
I would gladly not work and learn cello and physics independently if that were a real possibility, but it's not, and it won't be within my lifetime.
I had a job in a system that required jobs to survive that genuinely didn't bother me. I actually quite enjoyed it most of the time. Now it's permanently dead and I need something else, or I am homeless and starve to death.
> No, I fully reject any notion of life value coming from work, and those who hold your view are basically jailors to those who don't want our identity defined by work.
Fuck off.
Without massive scale weapon-grade NLP coming out of AI PR depts and targeting unwitting programmers, the LLM psychosis wouldn't happen.
Ahem Maybe you should write a shim for the stack you're using to broker domains.
Med school interests me, but I'm a woman in my late 20s who would like to have children, and if I started down the med school road now I wouldn't be done with training until my late 30s, where PA and nursing school don't have that problem. Medical physics is kind of in the middle.
Understand completely. I'm a little older than you but the high chance of giving up a family was the first thing on the negative column when I was deciding paths.
Sometimes, not enough to believe you that you can do it better. And even if you could, to believe that it's overall worth it to work in that way.
It seems too early to make any conclusion like that. We've still only been doing agentic coding for a year and capability significantly improved during that time. I don't think anybody on either side of this debate can have actual empirical evidence to support conclusions about where it lands longer term.
The main argument I see is that it probably pays to be slightly conservative because the cost of being wrong by maintaining too much oversight and shipping slightly less code is better than the cost of ending up with an entirely unmaintainable system. In some cases it will be more than "slightly less" but in almost all complex pre-existing systems, you are rate limited by a lot of other factors outside of code production, so the effective difference just isn't that high.
And it's debatable how much better they will get quickly. Verifiable rewards for maintainability of software is, I think, possible but very hard.
I also see devs, seniors as well, that have a different experience. At least that's what they say. I stay open to the possibility that I'm doing or seeing it 'wrong', but I'm far from convinced. I do like to experiment like you wrote in a later comment, things may change, and even now I do find it can be very powerful, for the right tasks.
It still applies to all things LLms can do from law to code to art to ideas.
They can do it - and very acceptably - but only to the untrained eye.
Obviously there are mission critical systems where it matters, but if “your code can be A/B tested” or “slowly rolled out”, chances are, it doesn’t matter.
Tech debt is still tech debt, even if there exist models that can wade through, because it's going to require increasingly sophisticated models navigating increasingly large context windows and increasingly speculative workspace operations to keep making progress on it.
Vendors like Anthropic and OpenAI are laying a pit trap when they demonstrate how their models can independently code their whole platform as it becomes increasingly byzantine and inscrutable because not only do they benefit from internal/prerelease models but they have effectively unlimited spend because all that spending acts as a lure to draw you into their trap.
For everybody else, design still matters. People are just working really hard to make you forget.
There are legitimate FAANG-like companies that have general guidelines about “when to use Fable/GLM/DS” and etc. to keep the costs down. And I think it’ll continue that way.
https://www.cnbc.com/2026/10/11/ai-software-developer-jobs.h...
Doesn't matter as much. The cost of "maintenance" is going down, from what I can see internally, from other companies, and every story i'm reading from other organizations as well. Token budgets are changing, but model quality and effectiveness are going up as well.
> We've also been hearing for years that LLMs are going to automate away software development entirely, but software job postings are steadily rising.
I think this has been contested from day 1. SE jobs might be automated, but jobs might increase, if there's possibility of starting new companies / new investments / etc.
The analogy would be math people with AI vs. non-math people with AI trying to solve some problems. I cannot solve the problems because I have no idea how to prompt it to go specific way. But it doesn’t matter how dirty your scratchpad was, because you got to the solution.
> I don't see it happening on projects that have a minimum bar for security/reliability and long-term maintenance
I don’t get this, because this is currently, right now, at this second, happening across huge projects. My point was that maintainability is less of an issue than before. Also, frankly, over years, I’ve seen bad code that AI wouldn’t even write. So there can be a case that the maintainability/code quality isn’t even going down as the models get better.
You're also find that implementation matters when token spend starts facing real accounting.
I really wish people would become more coherent with their reasoning.
Cost of tokens is NOT a problem unless you have a codebase with hundreds of person-years of effort. Not many people do.
It may encourage more secrecy and backend style designs though.
That said, I also feel like betting on readability, maintainablility, taste, etc, being an important aspect of software, at least until code will remain some sort of human readable artifact. We'll still want to be able to understand it and perhaps occasionally add/edit by hand, make sense of it without trusting blindly what any kind of program (LLM based or not) will tell us about it, and so on.
These things are important even in a repo with zero human code. A project that's filled with tech debt will always be hard to work with no matter what latest frontier model you're using.
I think a lot of this can be automated with slop detectors that flag messy unreadable code and make agents rewrite it, but you can't say it doesn't matter.
1. We are working on different types of application and code.
2. I am in a bubble and no-one in it has experienced the standards and productivity that SOTA AI tools can achieve.
3. The advocates are in a bubble and no-one in it has experienced the standards and productivity that expert developers can achieve.
I hope the answer is 1. I fear the answer is 2. I suspect the answer is 3.
They are only as good as their training data.
I expect them to have badder taste for PHP or JS, than, say, Kotlin or Ruby.
That's be because I prefer the code the latter communities have produced over the former.
Way to come off as incredibly insecure. There's no need to randomly put people down.
That's it. Maybe you should go re-read?
The advantage I have is that I know things that are not in the training distribution. Things about our business, our product, and its internal architecture. Without this knowledge, some new features cannot be designed successfully.
Some day I expect that will change, but all the patchwork "memory" systems, all the docs etc, will never get there because at some point they just pollute context. Knowledge has to be integrated, and that is what happens during sleep for humans, during pre-training and RL for models. LLMs are terribly inefficient at learning though and degrade generally during fine-tuning.
That certainly can be true but I would challenge "generally". If you're working on something novel then it's not exactly unusual for even SOTA models to produce a first attempt that makes some very bad assumptions but then get stuck when instructed to use correct axioms instead. This looks a lot like the suduko meme - without any real insight into the problem the models end up just iterating around in circles and never finding a solution.
You probably won't see this very often if you're working on simple CRUD web applications where there are millions if not billions of lines of code in the training data set. IME you will probably see it quite frequently if you're working on - for example - software to control some kind of equipment or analyse the results of some kind of experiment where the LLM might have little if any training data about the field you're operating in.
Not any time. Your feedback loop must provide some direction so the iteration is at least heading towards an improvement. For novel applications you might not have a convenient way to do that yet.
Even with that provision there's still a possibility of incrementally updating output converging on a local maximum. That local maximum might not be a solution at all. If it is a solution then the model might still miss much better solutions that a real developer with more insight might find.
As you said yourself the models need external feedback if they don't have sufficient information to make adjustments by themselves. In some cases that feedback might be "Start again because you're hopelessly off track". Sometimes even when they start again they just get hopelessly off-track again. That can happen even if they are explicitly prompted to do something else. So even closely supervising the LLM and not using self-iterating agents isn't guaranteed to get good results for novel applications.
You're right though that in new territory you may often have domain experts who still cannot adequately define success in an automated fashion because this is literally something that hasn't been created before. So they must be a part of the loop. They cannot necessarily put into code and descriptions what "better" or "right" is for an LLM to follow. But they can recognize it when they see it. In this case, it's still best to create the tightest feedback loop you can. If the LLM is waiting 2 days for your feedback, the loop is 2 days long.
I would say that a system with some sort of binary evaluation that indicates whether it succeeded or not is receiving feedback. It could also be some kind of sliding scale - how close did it get?
Either of those might be useful for determining a good future direction to iterate in but that would surely depend on the nature of the problem and how it's possible to search for solutions. I'd still call it a feedback loop even if the evaluation wasn't enough to point in a specific direction for a further iteration though. YMMV.
For example, Li et al. (2023), Emergent World Representations, showed that a GPT model trained only to predict Othello moves developed an internal representation of the board state, without being explicitly taught the rules or board structure.
I don't really care about the code being unmaintainable. Fable 6 or whatever will take care of it, just like Opus 5.5 takes care of our Opus 4.6 slop. The code working and our feature shipping is way way more important.
I would say I am now responsible for more big-picture decisions than I was previously, with Claude taking on the role of SWE (or a team of them). Despite this, there is still way more work than people.
> The code working and our feature shipping is way way more important.
I like that we both use AI very differently (you YOLO, I don't) but can agree that these are basically the important questions. If a company or team answers them like you do, I agree with the conclusion (YOLO). To me that's still a decision to be made though, and to be made wisely. Whether to accept the code may become unmaintainable, to forwardly rely on Fable 6 and to ship above anything (or at least a lot) else.