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AI Engineers aren't safe from being replaced by AI
- fatata123 4mo ago[dead]
- jazz9k 4mo agoThere are already AI certificafions for engineer on very new/ever changing technology.
- mnky9800n 4mo agoThis comment certifies you as ai expert.
- dude250711 4mo agoLet's not offend actual real engineers.
- witx 4mo ago"Engineers" Of course not, all these sloppers are doing is training the models so at the eyes of management they are good enough for a replacement. The ones who stay will have 10x more work.
- eru 4mo agoIf they can actually deliver 10x more work: well, that's how economic progress looks like.
- witx 4mo agoThey cannot... And economic progress for the companies. What these engineers who stay get is just a burnout and a pat on the back. I've seen it, and felt it, many times way before all this slop-coding started
- eru 4mo agoCompare and contrast https://pseudoerasmus.com/2017/10/02/ijd/ https://pseudoerasmus.com/2017/10/02/ijd/
- Forgeties79 4mo ago[dead]
- nDRDY 4mo agoIf you use AI to do your work, you can be replaced by someone else using AI to do your work.
- puritanicdev 4mo agoI’d reframe it: you won’t be replaced by someone using AI, you’ll be replaced by someone who is better at using AI and understands the code it generates Over the last couple of years, I’ve seen plenty of developers who remain barely competent despite having access to powerful AI tools. Generating code is easy. Evaluating whether it’s actually correct and maintainable is the hard part.
- sdevonoes 4mo ago> Evaluating whether it’s actually correct and maintainable is the hard part. But AI can also do that. So, what’s the point? And if you think it can’t, wait one more year
- puritanicdev 4mo agoIf Ai can generate code, review code, validate correctness, understand reqs, make architectural tradeoffs, operate systems, and take responsibility for outcomes, then we're no longer talking about replacing programmers. We’re talking about replacing most knowledge workers At that point the debate isn’t really about software engineering anymore What time to be alive, eh?
- gspr 4mo ago> > Evaluating whether it’s actually correct and maintainable is the hard part. > But AI can also do that. Citation needed. > So, what’s the point? The point is that there haven't been broad demonstrations of your claim. > And if you think it can’t, wait one more year You surely must understand that this isn't an argument? How many hundreds of billions have been burned through now? Yet we still have to suffer "soon" as an argument? I can't take any of this seriously anymore. PS: Just to be absolutely sure you don't misunderstand me: I am NOT claiming that AI will never be able to do this stuff. Nor am I even claiming that it's too far off or too expensive. Just, for the love of god, you cannot build an industry on promises of how amazing it'll be in the future. Technology is evaluated based on how it performs. Not how you think it might perform in the future. PPS: The last paragraph does also not mean that I think it's bad to invest in things that haven't yet paid off. On the contrary! What I am saying is you cannot claim success until there's success!
- motbus3 4mo agoHow surprised people will be when they learn that their prompts and skills and etc are being saved for ai training even though they said it would not be
- rzmmm 4mo agoI'm not sure if the authors means "ai engineer" like that.
- asdff 4mo agoThey select for people who are beholden to AI, probably to eventually have the model do the job of prompting if the model is expected to be doing the doing anyhow. Anthropic job posts I've seen have explicitly said you should use claude to claude-ify your resume before submitting. I'm guessing it's an auto reject if you don't. If they are asking for you to use their ai tool for step 0 before you even work there, they are going to want you to use it for all your job functions and communications. And all of that will be logged, used as training data, and will justify not hiring to fill your seat when you leave or get canned.
- merksittich 4mo agoLoosely related: Long read in today's FT on "The race to build AI that can improve itself" (https://www.ft.com/content/7cc7800f-18ed-47d8-9539-221ae3e16182 https://www.ft.com/content/7cc7800f-18ed-47d8-9539-221ae3e16...). Although this may be more relevant to replacing AI researchers, not AI engineers... (Submitted as https://news.ycombinator.com/item?id=48380643 https://news.ycombinator.com/item?id=48380643 )
- kakacik 4mo ago... and so the skynet saga begins
- Havoc 4mo agoI suspect everyone has a bit of „my job is special“ delusion tbh just with varying degrees of self awareness
- muldvarp 4mo agoI have yet to hear a single convincing argument by a person that works in software why they can't be replaced.
- pydry 4mo agoI've yet to hear an argument that argues that software engineers can be replaced by AI that doesnt boil down to slop apologism, inability to detect slop or simple gaslighting. These are things I've come to expect from bots, clueless journalists, clueless juniors, clueless expert beginners and clueless members of the professional managerial class but almost never from experienced software engineers. To be fair, seasoned software engineers always seem to get shouted down online by the former group which is louder and more numerous so you could argue that we "lost" the argument. Meanwhile big tech's vibe coded monstrosities are increasingly exploding all around us in ever more humiliating ways while the humans who had this tech rammed down their throats get thrown under the bus. This undeserved halo effect over AI is maintained in order to keep the needle from pricking the ginormous stock market bubble that hinges upon the religious belief in the lie AI Will Replace Us All Soon.
- stnikolauswagne 4mo agoThe argument is "Software Engineer" sounds like "Programmer" to me and "Programming" is just typing lines of code, AI can do all that typing quicker than a human so there we go. Currently leading an Integration that for the most part needs no new code written and the CEO is breathing down my neck telling me to cut my 4 week estimate down to 1 because "can't i just use AI like the other firms do?". There's a morbid part of me that wants to give him what he wants and let claude make critical process decisions on internal processes that are very domain specific and have no online documentation, but alas I would rather not have the project go down in flames so I smile and nod.
- DrewADesign 4mo agoDoctor sounds like Nurse, which sounds like applying bandages and taking temperatures. Physicist sounds like Lab Technician, which sounds like managing samples. Electrical Engineer sounds like Electrician, which sounds like installing a bunch of wire. Stunt Driver sounds like Uber Driver which sounds like pushing pedals and turning a wheel. It’s fun to pretend the world is much simpler than it is.
- ElenaDaibunny 4mo agoThe people who stick around will be the ones who deeply understand the problem, not the ones who are good at wrangling the tools.
- kumarvvr 4mo agoWhen all the prompts are by AI, and all the commits by AI, and all the use by AI,only then will corporations realize that..something ..
- tanepiper 4mo ago"The factory of the future will have only two employees, a man and a dog. The man will be there to feed the dog. The dog will be there to keep the man from touching the equipment."
- classified 4mo agoWill AI corporations fob off their AI users with chat bots and ignore them like the megacorps do with their human users today? On the other hand, it will finally not matter any more if AI-generated software is crap, because its bot users have infinite patience and infinite tolerance. Only the people who pay the electricity bill for all that waste will care but that's the price for survival in a world where only bots count.
- antirez 4mo agoIndeed this will likely happen in the future, but not today. I was experimeting with SSD streaming in DwarfStar for DeepSeek v4 PRO inference in 128GB systems (and Flash inference iwth 32/64). GPT 5.5 ran the whole night, I checked what it had accomplished regardless of all the hints I provided in the specification document. After reasoning on the problem I gave him the design fixes and the tokens/sec were 4x after 10 minutes. And this is true for every domain where the human babysitting the AI know a few things in that domain. However this is a moving target, and at the current rate, soon or later, indeed AIs will do much better than us in many domains.
- croes 4mo agoYour job safety doesn’t depend on the capabilities of AI but on what management thinks are the capabilities of AI
- antirez 4mo agoI don't think this makes any sense. Companies with managers that think AI capabilities are superior will be replaced if they are wrong as the companies will perform very poorly.
- florkbork 4mo agoThe lag time between firing your core team and finding out that was a bad idea can be measured in years of slow attrition.
- antirez 4mo agoActually workflow impact in the world of software can be observed in weeks/months at max. And token spending too, is a voice that they see at the high floors. Also, there was never a strong willing in IT companies to reduce cost of work force: it is done sometimes, but it is more common to see them over-hiring.
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- Anoian 4mo agoOnce we have AI, that can infinitely improve itself in all directions humanly imaginable, then we have solved AGI, by which time we will have other things to worry about.
- mike_hearn 4mo agoThe article is quite general. Here's some notes on how AI is being used to do AI research at frontier labs specifically. It's not the singularity (yet?) but it's heading in that direction. Most training is now actually inference, not directly gradient descent. Reinforcement learning requires the generation of lots of 'rollouts' that are then compared with each other via an algorithm like GRPO. Or they might be compared using a critic model - AI judging AI and causing it to self improve. Generating a rollout means inference. And there's lots of data cleaning by older models. This has been called in the past 'textbook' or 'curriculum' learning, not sure what it's called now. But AI is also used for things like data/document labelling, transcription of videos, detection of images/videos with watermarks or subtitles, elimination of content that shouldn't be in the dataset, creation of new content that should and so on. AI has proven capable of some routine work, like brute-force optimizing GPU kernels or doing hyperparameter sweeps. Obviously, researchers are all using coding agents too. So that's a few ways AI is self-improving. But there are lots of other ways in which even frontier models are still beaten by human researchers. Experiments in closing the loop have failed. For instance, people have tried giving the latest models access to some GPUs and an old version of an AI codebase that was recently optimized by human researchers (a NanoChat speed run goal, I believe). Could the models match the performance of the AI researchers? Nope. They only got 10% as far as the humans did, mostly because their approach was uninspired. They wasted a lot of time and budget doing low-IQ stuff like hyperparameter tuning. The humans had many other tactics like studying the research literature and inventing new algorithms that the models didn't even attempt. The bottleneck is therefore currently the level of insight and inspiration the models are capable of. I've also seen this in my own work. I come up with an idea I think is novel and see if I can get a frontier model to reach the same idea. It never works without questions so leading it's more or less pointless. It's very unclear why AI struggles so much with innovation yet can invent new songs, poems etc without apparent difficulty. Obvious answers like "it's not in the training set" don't feel right to me, the issue is deeper.
- fragmede 4mo agoIt's the Einstein question. Given an LLM trained on all written word up until right before Einstein's work, could the current SOTA in LLM architecture rediscover relativity? The jury is out on that, but until someone runs that experiment and proves otherwise, we have to assume LLMs simply aren't capable of that kind of brilliance. They're still impressive and useful and also stupid at times, but at the end of the day, no LLM has a gut to make a gut decision with. Unlike us.
- deleted 4mo ago[deleted]
- gobdovan 4mo agoI had the same thought about ML engineering a while back, when Google released the AutoML suite, that was banned from Kaggle competitions. At the time, it seemed obvious to me that the closer you were to the models, the easier it was for them to replace your work, since most of the work on models was itself hill-climbing, grind searching and mutation search. So, the more your work is an explicit, measurable search loop, the more automatable it is. Same with prompts, most attempts seem to be fidgeting with the models till they get your intend right, which is also a matter of hill-climbing, subtle mutation, and so on. If I were to clarify anything from the article, I'd probably say that I'd rather do the factorisation of programming roles by how long they already existed. If someone is an AI engineer and his work only became relevant a month ago, very probably it will be obsolete in another month. If they do the same thing for the past 10 years, changes are that their skills would be useful for another 10 years to come.
- Doch88 4mo agoI agree with you, although you could argue that history teaches the opposite, for example the many jobs that disappeared after medieval times, even if they existed for centuries. Maybe you will still find a cobbler or a blacksmith, but now it's something very niche; which is more or less the point of the post.
- gobdovan 4mo agoPerhaps we should not go into any even older professions on HN.
- zxexz 4mo agoFor some of us that day can't come soon enough @}-;-'---
- luka2233 4mo agoCompiler developers couldn't beat compilers at generating code either.
- gobdovan 4mo agoIt's fun to think about why that is. Most compilers explore the code into sea of nodes, with explicit relation kinds (depends-on, computes, effect relations etc) that humans don't have access to in surface languages. Then they just reduce and shorten a lot of the unnecessary edge chains, sometimes duplicate code that improves scheduling and a lot of not-so-semantically relevant stuff to get a dataflow that is guaranteed to have the same external behaviour with the code they're compiling. So basically compilers work on representations that humans almost never see, with different objectives that humans have. If humans were to code directly in dataflow networks and could find a way to keep them tidy and neat, I think humans would have a chance to beat solutions generated from surface code and then compiled automatically.
- Ozzie-D 4mo ago[flagged]
- fancyfredbot 4mo agoGood news - Anthropic will pay you £600k to build the AI which replaces you. Drag it out for a couple of years and you'll be set.
- rickydroll 4mo agoIt has started... https://www.minimax.io/news/minimax-m27-en https://www.minimax.io/news/minimax-m27-en With human productivity already fully unleashed, the natural next step was to initiate self-evolution of both the model and the organization. M2.7 is our first model deeply participating in its own evolution.
- ryandvm 4mo agoI'd say they are especially not safe. Nobody believes they can replace everyone with AI like the AI Kool-Aid drinking leadership.
- sometimelurker 4mo agoAI safety cant be automated so this claim isn't 100% true