What is happening to jobs? Separating AI hype from reality
Posted by pod_krad 1 day ago
Comments
Comment by simonw 1 day ago
General agents (OpenClaw, Anthropic Copilot, ChatGPT "Work") started working even later than that.
This category of software may have a much more meaningful impact on work than the mostly-chat systems we were using from 2022-2025.
Studies that mainly focus on 2022 to end of 2025 might be missing out on a material uptick in capabilities.
Comment by overgard 1 day ago
Comment by GeoAtreides 1 day ago
Long story short, I ate dinner so I think the narrative of people over the world being hungry is way overblown.
Comment by nozzlegear 19 hours ago
Comment by pjmlp 13 hours ago
What used to be contracts for translations or asset creations for CMS projects, is now handled by the AI tooling of CMS products.
The adoption of SaaS, iPaaS and serverless, meant delivery projects could be done with smaller teams.
Now with iPaaS adoption of agentic workflows, and AI tooling to transform those serverless actions into MCP tools, the team sizes have been further reduced.
Most agencies aren't winning enough projects to justify those that land on bench.
Comment by elteto 7 hours ago
Comment by mandeepj 2 hours ago
Congrats! Probably, you have the blessing of luck as well. One of my ex-colleagues got laid off and managed to find an uplevel job within a month, but another has been looking for almost 2 years now. He showed me that most of the jobs he applied to over the past two-ish years are still open, while they rejected him by saying the usual - we are moving forward with the candidates more aligned with the position.
Comment by danshipt 1 day ago
Comment by b112 1 day ago
Well anyone can use (prior to AI) a simple linter and learning to code isn't that big a deal. It's learning the pitfalls, the traps, that's the issue. And so far Opus just seems to fall into them again and again. I guess the best way to put it, is that it's not an architect. I sees no big picture, and that's not really a surprise with (compared to a human) an incredibly small context window. When I'm on a project, or working with a codebase, I often have years of "context window". And I have a career of "don't do this" context window.
So what I wonder is, will this be resolved? Will that awareness of larger scope be solved? If that happens, we'll be in another ballpark of competency.
Some companies have massive codebases. Are these companies slowly gaining rot in those codebases, a swiss cheese effect, which eventually will result in collapse? Because I've worked where a bad hire had just this effect over time. And what I worry about isn't using Claude to speed one up, it's the DEV that uses Claude and just "meh" and submits because it passes regression + other tests, and then a manager or code reviewer uses Claude and "meh" because it's a pass too.
Comment by ekidd 1 day ago
At least on greenfield projects, Fable is more like having an endless succession of fly-by senior devs who lock themselves in an office for a week, and who come back with very reasonable code that I then need to maintain somehow.
For longer-term maintenance, I am actually slowly warming to Sonnet 4.5-era models (so October 2025, right before the Opus revolution). They need to be given clear instructions and watched carefully. But since they force a human to stay in the loop, you don't have the institutional knowledge loss I see in some Opus projects, or the code that was one-shot with no human interaction at all that's a constant temptation in Fable projects.
And yeah, the bit rot is painfully real once the humans step back too far. I've been dealing with a compelling prototype that someone built, and that stakeholders love (for good reasons). But it had to be put on a tech debt repayment plan for a couple of months.
Comment by ACCount37 1 day ago
Yes!
And that "yes" holds regardless of whether they use AI or not.
Let's not pretend tech debt accumulation is somehow an AI problem. Some of the world's biggest companies routinely ship code that reeks of years of rot and decay.
Comment by jason_oster 1 day ago
Software has always sucked [1]. "Software crisis" was coined in 1968. There has been no period of time since that it got any better. Trauma just doesn't carry the same way that triumphs do.
Perhaps people do not actually learn from their mistakes after all.
Comment by joaquieneCnix 2 hours ago
which is the way the economy runs. cascades of PR narratives and economic measures carrying over upscaled patterns of the very same causal chain that makes people forget to self-debrief.
but most people enjoy being leisurely ignorant whenever they find themselves immersed in such qualia so even the brightest just smile while standing by ...
as long as we read, we will get hyped one way or another.
the issue seems that some narratives get disproportionate "air time" ... which, IMO, is exactly because there are so many bystanders among the capable & resourceful ...
Comment by lelanthran 1 day ago
While that is true, there's a large difference you are ignoring: a company can survive this type of rot indefinitely if it takes place at a certain rate. Their customers get time to acclimatise , the processes take into account the breakage, and adapt to compensate, etc.
If the AI boosters are to be believed (2x, or 10x or even, in some cases, devs claiming 100x productivity), stuffing 2 decades of rot into the next two years could prove fatal.
Comment by gnatolf 20 hours ago
Comment by layer8 1 day ago
I’m overall skeptical as well, but the argument about tech debt is more nuanced than your comment implies.
Comment by rudiksz 2 hours ago
There's the meme in programming that goes something like this "Give a programmer two lines of code to review and he'll find 20 issues. Give a programmer 500 lines to review and he's say that it looks good". At some point you simply cannot keep pace with the amount of generated code as a human.
Comment by lenkite 1 day ago
There have already been several high-profile AI-root-cause incidents at many companies this year. I guess we can look forward to even more deterioration in the next 2 years.
Comment by asdf88990 1 day ago
This is categorically false because time and cost pressure is relative and if anything AI has exacerbated the exceptions for ROI and Turn Around time.
This along with the fact that even state of the art AI tends to generate subpar (albeit working) code extremely fast and in large volume.
You can see the effect of this already in the increased rate of production incidents recently.
This isn’t to say that AI is useless, but the tech debt it generates is unprecedented.
Comment by ozim 1 day ago
We know all managers that say "stack doesn't matter, we can swap devs". We had C/C++ dev hired to do web dev with C# and Typescript.
Guy was utterly incompatible even if he was smart but management wanted someone who is local and can come to the office and that was this guy selling point.
Comment by ballsac 1 day ago
2026? 5? 4? 3?
Heard this one way too many times.
Comment by ben_w 1 day ago
And myself I keep making comparisons between AI and the progress in 90s video games where every minor improvement got called "photo realistic" and then forgotten with the next game engine: https://archive.org/details/nextgen-issue-26
So I'm not gonna say "this is it" when the software quality really matters, and I absolutely won't speak to progress (or lack of it) outside of software.
But I will say "you can look around and easily see small businesses using AI to generate posters, quite a lot of small business software and websites are in the same category: the mistakes are real but increasingly don't matter".
Comment by qsera 1 day ago
I think it would start to matter once again. People will get fed up of AI posters and art. I think they already are...and once some threshold is crossed, the business won't dare to use AI generated assets/designs.
Turns out humans are much better at recognizing patterns in stuff that is generated ONLY using patterns from human generated content.
Comment by ben_w 1 day ago
Agreed, but will this look like a meme/fashion cycle? If so, re-prompt each year with a different look. Yes, there are still issues here, a friend found an image he was amazed was AI generated, but to me it was obviously so, so I showed him a screenshot of ChatGPT making something just it and included my prompt:
create image: hand drawing of cute springer spaniel puppy looking sideways, various geometric shapes drawn in layer behind and in front of the puppy, all done in style of 7 year old using crayons with mediocre colouring-in skills
As I said to them: yeah, the line thickness feels AI, to me, the bad colouring-in scribbles feel like just the art style it was propmpted with
it's like: it gets the big picture of the composition, and it knows how to colour in badly, but it doesn't know how to draw a dog as badly as the colouring in
> Turns out humans are much better at recognizing patterns in stuff that is generated ONLY using patterns from human generated content.We're better at recognising patterns full stop. All biological brains are, and needed to be better than the current state of the art in machine learning because if a living organism was as poor at learning patterns as the SotA in machine learning, the organism would starve to death before being able to pick up anything and eat it.
AI also has a second disadvantage, because there are so few models: the laziest of ChatGPT "thinkpiece" blog posts being everywhere is hard to miss, and 5000 fake bloggers all prompting the same model with "find biggest news story of today and write a blog post about it in a way that maximises my ad revenue" will get 5000 almost identical posts. This will remain true while each instance of the most commonly used AI fail to talk to each other in a way that at least mimics them collectively getting bored with writing the same thing 5000 times, it does not depend on e.g. quality.
Comment by satvikpendem 13 hours ago
Comment by qsera 12 hours ago
Wrong analogy. A marketing item wants you to look at it. It takes advantage of an involuntary impulse. A repetitive boring AI artwork will not trigger the impulse to look it. So it is not about "caring"....
Comment by ben_w 6 hours ago
Right now GenAI content a bad thing, cringe, a sign of low-value or lack of attention to detail. I don't want to play even a free game if I think it was made by someone else prompting an AI, and that's despite liking the output when I do the same for myself.
If AI output is normalised and becomes simply "boring" or "mundane", those negatives must have also gone away.
After that (assuming there is an "after that", I don't want to bet either way), people would, as per your argument, need to un-boring them.
Comment by ragequittah 54 minutes ago
I have bad news for you if you think the video game industry isn't widely embracing generative AI. Companies try not to say it because of the current backlash involved but I truly believe Tim Sweeney isn't wrong[1]. I think in 5 years it will be a quaint idea to be AI-vegan and it'll be similar to how people resisted smartphones (I was one of them) until they became inevitable.
[1]https://www.techspot.com/news/110410-epic-tim-sweeney-ai-lab...
Comment by ben_w 10 minutes ago
5 years is an eternity with the current rate of change of AI. Its development is already turning into an international geopolitical issue, even though the implications for mere task-level economics have yet to settle.
Even if it wasn't, 2031 (ish) happens to be roughly when a lot of long-term exponential growth trends all happen to reach points that suggest the assumptions behind them have to break, like more than 100% of electricity being made by PV etc.; the only thing I am confident of about AI is that even its current trend line on METR were to continue it becomes physically unmeasurable sooner than that.
Half the game logic I played on Kongregate back in the heyday of Flash games is now one-to-few shot prompting on Claude even if you don't pay for it, and even if you don't pay for ChatGPT you can get assets at that scale pretty quickly. It's just, like every blog post whose headings contain emoji, every time there's a 6-7 word paragraph a little too bombastic about how important something is, every time I hear "you're absolutely right" or "delve" or "nuance" even from a human…
…the way most people prompt these models, I can tell. And humans are lazy and greedy, so even if the visual models gets as good as the finest artists and the language models as good as Nobel laureates, we're going to learn the style of whatever the default output of those models is when prompted by lazy and greedy humans. And we'll hate it, because it's a cliché, and we avoid those like the plague.
Comment by satvikpendem 3 hours ago
Comment by TeriyakiBomb 1 day ago
Comment by w4der 1 day ago
Comment by qwerpy 1 day ago
Handling highway driving with lane changes was great when it got there years ago, but just in the last year or so it has gone from a nice to have to “from now on I will never buy a car that can’t do this”.
AI has hit some milestones for replacing work as well. There’s still many more to go and maybe some of them will never get hit (much like I don’t think a coast to coast drive with zero interventions during winter conditions is ever going to happen) but there are points at which it forever meaningfully changes some field of work. I think it’s there for writing code.
Comment by ben_w 1 day ago
Half-and-half. I'm not denying that self driving cars (and LLMs) are improving, I'm comparing it against the standards set by the biggest proponents. But yes, I have heard basically the same thing you just wrote for the previous several major releases of FSD.
Where we agree is that, while you are a fan, you do explicitly give as an example of something you think it will never do, something very close to what Musk has promised:
"Ultimately you'll be able to summon your car anywhere … your car can get to you. I think that within two years, you'll be able to summon your car from across the country. It will meet you wherever your phone is … and it will just automatically charge itself along the entire journey."
- Musk, in Jan 2016: https://en.wikipedia.org/wiki/List_of_predictions_for_autono...(That said, I think Tesla's FSD will never get there, not that it's impossible. The way Musk is behaving, there's going to be a financial scheme named after him in whatever passes for a textbook in 20 years, and it won't be the positive kind of example).
Comment by qwerpy 1 day ago
I'm mentally prepared for the next US administration to exact retribution on his companies, and I expect FSD will be neutered after that. Hopefully other car companies are able to catch up. I'm more of a self-driving fan than a Tesla fan, so as long as the thing works as well as what I have now, I'll be fine with it.
Comment by ben_w 1 day ago
Yes. He was before and remains so to this day, but he did so then, too.
> I need it to safely drive my family on my daily errands or weekend trips, which I now consider solved.
This is probably unwise. As with LLMs, the statistics suggest a spikiness in the intelligence, with it being mostly good but also sometimes still making some very odd mistakes that humans would essentially never make.
As with your other comment, you know that if it gets into a crash you're responsible; while you consider this a win, I suggest waiting until the company you buy the car from (in this case Tesla) puts their money where their mouth is on quality and takes liability for crashes due to the AI upon themselves.
(The Cybercab was supposed to be sans-steering-wheel and sans-pedals, which would be a sign of that level of confidence, but the ones spotted in the wild at least sometimes seem to come with the wheel, which suggests they're still not there yet: https://www.vehiclesuggest.com/cybercab-with-steering-wheel-... https://www.carsguide.com.au/car-news/real-tesla-cybercab-sp...)
> Hopefully other car companies are able to catch up.
From the stats I've seen, they're much closer to the goal, relatively smoother/less spiky all-round driving intelligence. They may not be as impressive at their best, but when they fail the failure modes are themselves much safer.
Comment by qwerpy 17 hours ago
The usual HN nits at this point are that the data is unreliable/biased and that the way I’m using it isn’t supervised enough. I’ll admit to the latter. In my experience the mistakes tend to be navigational but I’ve seen a few of the “nearly drove through the lane closed gate” videos so I definitely keep a closer watch when there is complicated highway stuff going on. I also have my foot at the ready for when I go through the gate to my community, similar failure mode and about 1% of the time it forgets to wait for the gate to close and reopen.
I look forward to the other car companies catching up, competition and more options are good. Elon is a loose cannon, so I need alternatives if Tesla ceases to be.
Comment by ben_w 44 minutes ago
Tesla have been claiming the stats show superiority of their AI vs. humans since at least 2016: https://techcrunch.com/2016/07/06/tesla-says-drivers-using-a...
The lesson from the Datasaurus should be to ask detailed questions, e.g.:
• exposure bias: is the AI used more or less in certain conditions, on certain kinds of roads
• sharpshooter: shouldn't need to ask this one of a public company, but given regular headlines: how many crashes happen a few seconds after it switches itself off?
• driver demographics: most severe accidents by humans are due to impairment or being a new driver, is the AI actually better than an experienced-and-not-impaired driver?
• the nature of the failure modes: as a cyclist I've been hit by a car that stopped at a junction and pulled out into me, this was not fun but no serious injury; this is very different to any of the highway speed fatalities.
> Separately from the data, it is just so nice to hit a button and sit back and relax for the entirety of the drive.
No doubt. Myself, this is why I have been happy to live in a city with a good public transport network and use that instead of driving.
> I look forward to the other car companies catching up
My point is that they are in some important senses already ahead. Less optimised for the headline, more optimised for the real dream.
Comment by StilesCrisis 1 day ago
Comment by keeda 1 day ago
And this is not anecdotal, there are enough reports that an investigation is ongoing: https://autos.yahoo.com/policy-and-environment/articles/tesl...
I keep saying, FSD being marketed as FSD is going to get people killed and I can't believe more is not being done to prevent this.
Comment by sumeno 1 day ago
Comment by grim_io 1 day ago
It's not FSD until the human is no longer responsible.
This half measure bullshit is a joke.
Comment by qwerpy 1 day ago
Comment by grim_io 1 day ago
It's just absolutely crazy to me that you trust this experimental feature more than the manufacturer does.
Comment by 3ff3 15 hours ago
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Comment by Alpha3031 9 hours ago
Comment by cmenge 1 day ago
I just spoke to a fried who is a headhunter and who's been trying to automate his processes for a while (he likes to fiddle and certainly has skills, but he's not an engineer). He kept trying, but it just wasn't good enough.
Now he said with GPT Work and Sol, it worked, but the key point is: all of it suddenly worked.
The problem was one of reliability, of handling edge cases. All previous attempts / model-harness-combinations were too brittle and needed too much observation and fiddling - cheaper to do it yourself.
Now he says "I don't know why I would ever hire a recruiter [the folks doing the cold outreach] again. I can focus on the candidate screening and acquiring projects, everything else is fully automated".
This doesn't come from an engineer or an AI lab, but a technically inclined power user, and I think this is where things get interesting.
Comment by johnyzee 1 day ago
It's cool that 'regular' people can now create solutions to many small problems, and automate stuff - genuinely a step forward. Like Excel, only vastly better. But for bigger projects, real software engineers know that what LLMs do today is only a tiny part of development. And it solves it in a way that might well make the rest of the lifecycle a lot harder. It's like that saying about tools that make easy things easier and hard things impossible.
Comment by phoghed 1 day ago
Currently in a re-org justified by AI, AI changing the roles people will need to play. It’s disturbing how much content in the materials about the new org structure and roles and whatnot is clearly ai generated and contradictory. We’re laying off about half of 500 people.
Comment by a34729t 16 hours ago
It gets better: The internal AI gateway chat thingy where you can ask questions has AI autocomplete that pops up after your write more than 10 characters. What the fuck!?
Comment by Kiro 1 day ago
Comment by r_lee 1 day ago
would a great candidate get excited about an AI agent reaching out to them? or would it be the desperate or clueless one?
Comment by cmenge 14 hours ago
For all other roles the first few messages are similar: this is <role X> with key challenges a,b,c. You seem to be a good fit because of d,e,f. Would you be open to explore this? This requires relocating to <place>.
Traditionally, this was done by entry-level people. In either case, this isn't the person who will jump on a call with you.
"Desperate" and "clueless" seem very strong words here in reference to someone who gets actively approached from a recruiter.
Comment by mstaoru 1 day ago
Comment by noosphr 1 day ago
This is like microprocessors in the 80s. Sure they double in capability every 18 months but the start is so pathetic it will be 30 years before they are good enough for everyday tasks.
Comment by StilesCrisis 1 day ago
Comment by noosphr 22 hours ago
Comment by StilesCrisis 7 hours ago
Comment by noosphr 6 hours ago
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Comment by erispoe 1 day ago
Comment by cowanon77 1 day ago
Time will tell of course, and it’s early, but inflection points do exist with progress.
Comment by TeriyakiBomb 1 day ago
“But it’s different this time” - several people, several times over the last couple of years.
This is not at all a dig at you, I’m very sorry if it reads that way. My point is these things only get truly better in anecdotes. The ways in which they fail is yet to change. Just yesterday I had gpt 5.3 generate completely awful code for the Cinema 4D Python API. Also an anecdote. But for all of the people saying they are truly intelligent and truly reason, they still make obvious mistakes, write around problems, fail entirely at architectural decisions, fail at random, generate FAR too much code.
And no amount of harnesses, methodologies, loops make much of a difference. If you listen to people on the internet they say it’s all working. You listen to people on the job and they mostly say it’s creating tech debt and a review bottleneck. Also burnout, so much burnout.
I think LLMs are mediocre. I think it’s fine they’re mediocre. You can work with low expectations. But the hype cycles are so tiresome.
Comment by ACS_Solver 1 day ago
Then the incremental improvements did, in my experience, cross some kind of threshold in late 2025 where the things became useful. It is of course anecdotal and personal judgment. But I asked LLMs to implement a small feature in my codebase (my usual test) and finally it produced code I was happy with. They've also been able to locate and diagnose a problem based on logs. In my view it's now a markedly different level of capability than we had a year ago, though I would call the previous two years equally useless.
Comment by orangecat 1 day ago
Yes, as a product gradually improves there will always be many people for whom version X didn't work well for them and version X+1 does. It turns out that Opus 4.5 and GPT 5.1 were larger than average improvements that cross that threshold for a significant number of people.
My point is these things only get truly better in anecdotes. The ways in which they fail is yet to change.
If your claim is that there's no substantive difference between Sonnet 3.5 and Fable, then we live in very different worlds.
Comment by CuriouslyC 1 day ago
Comment by simonw 1 day ago
How does GPT-5.6 Sol or Claude Fable 5 or Claude Opus 5 do on that Cinema 4D code?
Comment by user43928 1 day ago
Why would you attempt to use GPT 5.3 to generate code today and form an opinion on that basis?
I do not think it is even still available in Codex, I believe it only has the smaller, distilled GPT 5.3 Codex Spark.
Comment by iLoveOncall 1 day ago
Even 3.7. I remember when it came out and people were claiming that that was now the model that was going to replace engineers. Cue Fable years later and people still claim that this one is the one.
Comment by ModernMech 1 day ago
Comment by simonw 1 day ago
What shape did that evidence take?
Comment by skydhash 1 day ago
The key thing is that it's easy to contrast the old way vs the new way and the evidence become obvious.
The thing with LLM tooling is that they're not reliable. I can do fine with risks, but only when there's a way to manage it so that if the disaster happens, it's practically a black swan event.
Typing more code or solving one task has never been the core problem. The core problem has always been to encode a whole system into the computer AND then provide a control interface for it. It requires both an understanding of the system you want to encode (especially how it behaves over time) and empathy to know what would be the best control interface for the users.
That understanding does not rely on the amount of code, and the best control is found through communication.
If we take the following project that you did:
https://simonwillison.net/2025/Jul/17/vibe-scraping/
An understanding of the system could be the following: A conference schedule consisting of events (time, place, speaker, description,...) stored or presented in some format. The interface would be: A web app with a mobile first UI that presents the information in an accessible manner (highlighting, filtering, exports,...).
A relatively quick (I haven't tested it), would have been to open the web inspector and extract the data using the dom API (requires knowledge of the dom api and a desktop browser), put the data into some json or a tsv file, then write a php script or a python script and then serve that. The interface could have been built with the standard elements of some css framework (bulma?).
Not saying the above is better. But the thing is that is doable from even a raspberry pi. And more it's repeatable and extensible. And the individual piece of knowledge are reusable in different situation.
Comment by StilesCrisis 1 day ago
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Comment by Kiro 1 day ago
Comment by ModernMech 7 hours ago
AnimalMuppet in their reply to my OP comment makes the point that these things haven't been around long enough to measure end-to-end productivity gains and come to a conclusion either way, and I agree with that. But we can still at least be measuring something.
For example, in my case AI has allowed me to write 10x more LOC than I usually would in a similar amount of time. But having to review it all, I've also deployed 1/4 the number of releases I normally would in the same period. By one measure I'm more productive, by another I'm less productive.
People could claim to be more productive by skipping the review. But in that case did AI make you more productive or did you lower standards? People could say they're using AI to do the review but is the impact of that being measured and has that caused more or fewer bugs? If more bugs, has the time to fix those been factored into overall productivity? In my experience it's common for people to eagerly count immediate productivity gains and discount long-term productivity sinks.
For this reason I think case studies are the best convincing thing, because they properly contextualize the usage and consider a longer-term window. They're also backwards looking instead of in-the-moment, so have the benefit of hindsight. But they're harder to come by and we probably won't see any meaningful case studies for a thing that people say happened in November.
But the very least people can be doing is just defining what they mean when they say "productivity" because otherwise everyone is talking past one another.
Comment by AnimalMuppet 1 day ago
Pro: "The evidence hasn't shown up in statistics yet; it's too new!"
Con: "And won't this destroy maintainability?"
Pro: "Show me the maintainability disasters caused by AI."
Con: "I can't yet; it's too new!"
Both sides are playing the "it's too new" card when asked for actual evidence to prove their claims. In fairness, it actually is too new for there to be much statistically-valid data, especially if the inflection point was November 2025. So both sides are trumpeting their position, neither with actual trustworthy data.
Everybody has their anecdote. Nobody has data yet.
Comment by bluefirebrand 1 day ago
Very smart people aren't immune to being worn down over time
Comment by simonw 1 day ago
Comment by TeriyakiBomb 1 day ago
Meanwhile the guy who leaned in a year ago and gave up reading the output is beginning to see work grind to a halt and throwing more agents at it is increasingly not working.
You can see these tropes all over social media near constantly.
Comment by Kiro 1 day ago
You should stop using social media as your yardstick.
Comment by TeriyakiBomb 1 hour ago
Comment by wolvesechoes 14 hours ago
Yes, don't believe people posting on HN.
Comment by simianwords 11 hours ago
Comment by wolvesechoes 7 hours ago
But in all seriousness - you can even bring up Pope himself. Don't care. Show me data, show me the leaps our software made with all this 100x productivity boost. Show me a myriad of better LLVM projects, new usable kernels, and so on. Show me sharp decline in bugs and defects in existing projects.
Keep blog posts and HN comments.
Comment by simianwords 3 hours ago
Comment by SpaceNoodled 1 day ago
Comment by iLoveOncall 1 day ago
The ones you make up in your brain don't count. I'm yet to see anyone serious reverse their claims.
Comment by simonw 1 day ago
> November was, for me and many others in tech, a great surprise. Before, A.I. coding tools were often useful, but halting and clumsy. Now, the bot can run for a full hour and make whole, designed websites and apps that may be flawed, but credible. I spent an entire session of therapy talking about it.
Max Woolf is a good one: https://minimaxir.com/2026/02/ai-agent-coding/
> The real annoying thing about Opus 4.6/Codex 5.3 is that it’s impossible to publicly say “Opus 4.5 (and the models that came after it) are an order of magnitude better than coding LLMs released just months before it” without sounding like an AI hype booster clickbaiting, but it’s the counterintuitive truth to my personal frustration. [...] A year ago, I was one of those skeptics who was very suspicious of the agentic hype.
DHH - https://newsletter.pragmaticengineer.com/p/dhhs-new-way-of-w...
> Six months ago, in an episode of the Lex Fridman podcast, David shared how he doesn’t use AI tools to write code: he types out all his code. But things have changed a lot since then.
> In this episode, we discuss his approach to building software, how it’s changed in the last six months, and why he now takes an agent-first approach, and how he barely writes any code by hand.
Linus Torvalds, two weeks ago (though I don't have evidence that he was a skeptic before) https://lore.kernel.org/linux-media/CAHk-=wi4zC+Ze8e+p3tMv8T...
> There are other questions around AI (like what the economy of it will actually look like in the end), but "is it useful" is no longer one of those questions. Anybody who doubts that clearly hasn't actually used it.
Donald Knuth! https://www-cs-faculty.stanford.edu/~knuth/papers/claude-cyc...
> Shock! Shock! I learned yesterday that an open problem I'd been working on for several weeks had just been solved by Claude Opus 4.6 - Anthropic's hybrid reasoning model that had been released three weeks earlier! It seems that I'll have to revise my opinions about "generative AI" one of these days. What a joy it is to learn not only that my conjecture has a nice solution but also to celebrate this dramatic advance in automatic deduction and creative problem solving.
Comment by iLoveOncall 23 hours ago
Comment by simonw 22 hours ago
Max Woolf and DHH are clearly experienced developers who continue to write code for money.
Linus too - 11 commits to the kernel today! https://github.com/torvalds/linux/commits?author=torvalds
Plus this very thread is full of experienced developers who are saying that "coding agents are now useful when they weren't before":
- ACS_Solver: https://news.ycombinator.com/item?id=49052570#49057367
- suzzer99: https://news.ycombinator.com/item?id=49052570#49060743
- IshKebab: https://news.ycombinator.com/item?id=49052570#49056074
- smrtinsert: https://news.ycombinator.com/item?id=49052570#49055294
- qarl2: https://news.ycombinator.com/item?id=49052570#49053318
A few bonuses:
Mitchell Hashimoto: https://mitchellh.com/writing/my-ai-adoption-journey
> While I was still a heavy AI skeptic [... through to ...] At this point I was firmly in the "no way I can go back" territory.
Steve Klabnik: https://steveklabnik.com/writing/getting-started-with-claude...
> 2025 was an interesting year in many ways. One way in which it was interesting for me is that I went from an AI hater to a pretty big user.
Nolan Lawson: https://nolanlawson.com/2026/01/24/ai-tribalism/
> 2025 was a weird year for me. If you had asked me exactly a year ago, I would have said I thought LLMs were amusing toys but inappropriate for real software development. [...] Today, I would say that about 90% of my code is authored by Claude Code.
Comment by iLoveOncall 22 hours ago
Funny coming from a guy using Linus saying "There's no doubt AI is useful today" and interpreting that as "Yeah last year AI coding agents were garbage but now they're really useful".
There's no denying AI is useful. I use AI, my project at work is all about using LLMs. They're even useful for coding, when I don't give a fuck about the quality of the output (which is almost never in a work scenario).
But to claim that there has been some magical shift late last year is simply laughable. Anyone working as a software engineer and claims that is either lying to themselves or simply bad.
Oh and don't try with the "you're not prompting it right".
Comment by simonw 21 hours ago
Or to strengthen the case for Linus, here he is on June 16th 2926 saying: https://youtu.be/YKkEe-PxW10?t=1687
> we certainly saw more junk being generated by LLMs than we saw useful code up until the like early this year
Comment by 3ff3 15 hours ago
The world needs to SEE what is coming out of all this spending. Guess what? It aint much! Thats why firms are in a hurry to review their expenditures and switch to chinese offerings.
I hate to break it to you - but wake up. You are not living in reality.
Comment by wolvesechoes 14 hours ago
Oh yes, dev celebs that rely on constant validation through social media. Very reliable source of data.
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Jason Turner gave an excellent talk at last year's CppCon explain how he thinks tools can be used to make generative AI coding assistance safer and more productive. https://www.youtube.com/watch?v=xCuRUjxT5L8
Comment by r_lee 1 day ago
it's useful for scaffolding but after that I'm not sure how you could rely on it without being in the loop and directing how the code should be like
Comment by bluefirebrand 20 hours ago
Of course it doesn't seem that way to you. Preachers view themselves as spreading the good word, they don't see how annoying it is being preached at
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Comment by ben_w 1 day ago
Now it is.
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Comment by simonw 1 day ago
I believe Aider avoided adding that for safety concerns. Claude Code demonstrated that throwing safety to the wing somehow kind of worked out.
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Comment by simonw 1 day ago
Things are allowed to get better more than once!
The idea that "yeah, you said technology had improved in the past, and now you're saying it has improved again" is a gotcha just seems incoherent to me.
Comment by nozzlegear 18 hours ago
> The debate over whether AI is taking people’s jobs may or may not last forever. If AI takes a lot of people’s jobs, the debate will end because one side will have clearly won. But if AI doesn’t take a lot of people’s jobs, then the debate will never be resolved, because there will be a bunch of people who will still go around saying that it’s about to take everyone’s job. Sometimes those people will find some subset of workers whose employment prospects are looking weaker than others, and claim that this is the beginning of the great AI job destruction wave. And who will be able to prove them wrong?
Comment by nomel 11 minutes ago
Or, more likely, since software touches every single industry of man, you're seeing AI slowly able to handle different types of work. People in the types of work that early models struggled with are now enabled. Their goal post didn't change. The internet is not one entity.
The last people to say that their work will be impacted are those that work in areas with the most novel ideas/innovation, and/or working on things where libraries/examples don't exist.
For example, I work in test/manufacturing, mostly with robots. The whole industry is proprietary. There are basically no open source libraries/code for this stuff, so claude is still pretty terrible at it, but, with Opus 5, it is able to now do some of the work!
Comment by jcranmer 1 day ago
Or, put differently: if a study comes out next year saying they don't see major impacts from AI in 2026, will you admit your viewpoint as being wrong, or is your response going to be "no, there was a massive inflection point in September 2026 that completely invalidates the paper"?
Comment by codinhood 1 day ago
But this didn't seem to concern them. The study said X, therefore it applies to today.
I'm just not sure it's worth it to argue with others about it at this point. Not that I'm 100% all behind AI coding, but I'm just shocked people are still this resistant.
Comment by dolebirchwood 1 day ago
This is the correct response. Let closed-minded people do their thing. Makes them less competitive against you. There's nothing for you to gain by trying to help them understand what they are missing.
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No idea if it's true, but when I observe my fellow human, it sure seems to be.
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Comment by nomel 4 minutes ago
And even then, within a single group, you'll have multiple thresholds, of "this really helps make my coding more productive" to "I no longer type code, just review" to eventually "I'm no longer employed".
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Comment by user43928 1 day ago
I have had good results in that area with GPT 5.5 in the past.
On the subscription plan I don't use anything but xhigh effort and Fable, 5.6 Sol, or now also Opus 5.
Is that the class of model that struggles with Docker for you?
Comment by ModernMech 1 day ago
So whereas before my debugging time would have been spent in Rust docs looking up traits and such, these days I feel more like an AI therapist trying to figure out why it's not feeling up to task on any particular day. It can be anything from regular service outages to geopolitics that on any given day my workflow is fucked up.
In my before-AI workflow, I was never restricted from compiling Rust code because of concerns that Cargo is a national security threat. So you really have to broadly scope the notion of "reliability" with these AI tools; it's much larger than whether it can give a good output but whether it can do so consistently enough to depend on.
Comment by throwaway7783 1 day ago
Comment by Forgeties79 1 day ago
This just reads like another variation of “it’s the user not the tool,” which is just endless runway for always blaming people and never acknowledging the limitations of LLM’s.
I’d be curious to hear how the recipients of your work enabled by the “productivity multiplier” feel about the quality.
Comment by throwaway7783 5 hours ago
We actually have trendlines on user reported bugs, and I am happy to report they show a significant downtrend.
Comment by inglor_cz 1 day ago
I would say that as of July 2026, with the right scaffolding, you can get reasonably good output out of a LLM, or better a combination of LLMs. For example, it pays off to prepare an implementation plan with one LLM and then let another LLM check it for flaws, then again. After several iterations like this, you will have a plan better than whatever you could come up with yourself.
It often is the user and not the tool. LLMs are complicated, have nontrivial failure modes, and the user needs to steer them carefully. They might be the most complicated tools on the planet right now.
Anecdotally, the recipients of my work have become visibly more happy in the last months. LLMs are great at diagnosing subtle problems which tend to appear at Friday night only, and this is the sort of problem that bugs actual people the most.
Comment by Forgeties79 1 day ago
Totally agree, I don’t think I said or implied otherwise.
And yes can it can be the user and often even is, but when it comes to any LLM conversation I’ve been a part of it seems people think the only answer is “you’re using it wrong.” Evangelists swear it’s a 100x multiplier and anything counter to that means you’re either a Luddite who is blinded by politics or are too dumb to use the tool.
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Comment by simonw 1 day ago
One example: everything I do is properly tested and documented now, even the most trivial of changes. Previously I would have weighed those tradeoffs and sometimes decided not to bother with the tests because they weren't worth the time.
Comment by janussunaj 1 day ago
No offense, but that says much more about the way you approach programming than about the quality of LLM outputs.
In my experience, LLMs are the ultimate corner-cutting tool. With LLMs, I now succumb to the temptation to cut corners, build something I haven't properly researched and don't fully understand, prioritize shipping quantity over quality.
Without LLMs, I have to understand the domain and the tools and ultimately my full solution (with all its warts and limitations). When I really care about the project and consider it "my baby", LLMs are out of the picture.
Comment by simonw 1 day ago
Not having to type in and then iterate on the code manually has a material effect on those time calculations.
I absolutely agree that you need to understand the domain and code and tools. That's what I want to spend my human time on - not typing in the code and sweating over every line of syntax.
Comment by janussunaj 22 hours ago
However, I completely disagree with your characterization of LLM coding as saving you "typing in the code and sweating over every line of syntax".
Claude will happily architect complex layers of OOP, multithreading, SIMD (a "personal favorite" of both Claude and ChatGPT).
If you don't immerse yourself in the details, you will never know if you made the correct engineering trade-offs, let alone whether the various "optimizations" and clever solutions by the LLM actually work.
I think you're referring more to product strategy trade-offs than engineering trade-offs here; so yeah, getting something you don't understand out the door is often the fastest path to sales. This is also how we get so much low quality and unnecessary software out there (it was true before LLM coding, just amplified now).
I think a reasonable tradeoff, in theory, would be: use the LLM to help you explore the space of solution, then dive into the details and choose the path that feels right. However, I highly doubt most people do that. It's also easy to let the LLM's first solution influence your understanding of the problem, so that you will never truly explore novel solutions that fall outside of the most likely token sequence prediction.
Oh and LLMs when properly constrained can also do pretty good "auto-complete on steroids", which can definitely save you typing a lot of boilerplate. If that's how you use them, then your characterization is correct.
Comment by simonw 20 hours ago
Oh absolutely. One of my favorite prompting patterns is "suggest options for X", followed by serval rounds back and forth to discuss tradeoffs and maybe introduce new ideas into the mix.
I also use LLMs to build exploratory prototypes. I'm working on a project today which I've had different coding agents build a total of four times already. Those explorations gave me the confidence to dictate a finished solution that I'm sure will work well against all sorts of future cases.
Comment by pjmlp 12 hours ago
What they care about isn't software delivery, is physical goods or services that aren't related to software, for them software is a cost center.
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I've been saying this for years.
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Of course don’t let me assume, maybe you have a higher quality disproof for the Jacobian conjecture you could share with the class.
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If model scaling holds out, we're "early-ish" in terms of the reliability and performance of these systems, just based on utilization of the compute from the planned capex. If we hit hard diminishing returns and we don't find architectural/data workarounds, that would put a wrinkle in things, but I suspect that the AI we have now is capable of helping us find those workarounds and keep things moving.
Comment by 3ff3 14 hours ago
lol.
Anthropic and OAI have unreleased powerful models with no limits - they have yet to pull out a 10-d chess move. Wake up bro. There is no AGI coming.
Comment by CuriouslyC 8 hours ago
Comment by majormajor 1 day ago
But it seems more correlated with hype-cycle-stage than anything else. Right now a lot of founders seem to be convincing a lot of VCs that they can make $LOTS by replacing/changing $BIG_INDUSTRY/$BIG_PRODUCT with an agent-first blah blah replacement, and then using that money to hire more people to manage/execute/coordinate the coding agents...
Last year, by comparison, there seemed to be a mood of "software will stay the same but will require less people" while right now there's a lot of hype around "we can build different types of software or build it in different ways" and those early-stage things are in growth-mode. That guarantees nothing about how many people they'd need in the future, or their success at all, ofc.
The news that I'm getting from contacts in non-startup-land is a bit different - still layoff threats. Still pressure to use AI tools more. Mixed confidence on whether or not longer-running "agent" modes are that much more effective-without-breaking-things in legacy code if not used with care.
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Comment by jarek-foksa 12 hours ago
There is nothing special about the OpenClaw thing other than the enormous astroturfing campaign that benefited various "crypto" influencers and other scammers. Anyone who endorses it is either manipulated or trying to manipulate you.
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Comment by AbsurdCensor 1 day ago
Maybe the future will change that for very specific things, but I think people should be learning and preparing for that, which isn’t any different than what everyone has been told in every job market since the start of the Industrial Revolution.
Comment by simonw 1 day ago
I'm nervous that the studies which show that so far don't seem to be taking the 2026 improvements in coding and general agents into account.
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Comment by simonw 1 day ago
It's genuine concern. I do not want to live in a dystopia where AI results in mass unemployment. That would suck, even for the people who manage to stay employed.
Comment by Avicebron 1 day ago
> What the heck would I be "stealth-marketing" here?
Cynically, "thought-leaderishness".
I've been spending a lot of my time these days outlining why we can't "just make an agent for it" to CEOs who read blogs like yours. They can't distinguish a production system from a quick HTML tool from a guy whose job doesn't depend on it working.
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Comment by simonw 1 day ago
> I think this is going to have a huge impact on society. My priority is trying to direct that impact in a positive direction.
> It’s easy to fall into a cynical trap of thinking there’s nothing good here at all, and everything generative AI is either actively harmful or a waste of time. [...]
> I’m going to continue exploring and sharing genuinely positive applications of this technology. It’s not going to be un-invented, so I think our priority should be figuring out the most constructive possible ways to use it.
That's been my focus ever since: try and use whatever influence I have to nudge things in a positive direction, and help people figure out how they can use this technology in a way that is beneficial both to them and to other people.
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Comment by underlipton 1 day ago
1) I hesitate to believe that losses were disproportionately technical roles as opposed to administrative.
2) Over-hired by what metric? It's well known that hiring never fully recovered after the GFC; was the recruitment post-pandemic just bringing us to parity with where we had been 20 years earlier?
Not to say that I disagree with your following point. The AI overspending and the layoff cost-cutting are not in a direct causal relationship; both are rather symptoms of a common corporate pathology.
Comment by AbsurdCensor 21 hours ago
Comment by weatherlite 1 day ago
Mostly an impact on software development - I'm not seeing broad automation and layoffs in industries like law, finance etc. It will gradually happen but due to issues with memory, reliability and long term planning of LLMs there are real barriers. Even in software development - while it has completely transformed the field I don't think many people still believe we won't need devs in 2027 or that their amount will shrink by 50%.
Comment by simonw 1 day ago
My ideal version of all of this is that nobody loses their job and everyone gets to take on more ambitious projects.
I'm not quite naïve enough to assume I'm right about that though!
Comment by steve_adams_86 1 day ago
Likewise. I find the types of problems I need to tackle and the challenges they represent are actually quite exhausting, too. And the agents unblock me relentlessly so I’m constantly pressed to do relatively difficult things. Either that or code review. I’m hoping it’ll only be an adjustment phase but this is the most challenging my career has been in over a decade.
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Everything impressive has happened in the last six months.
Comment by ares623 1 day ago
"Move fast like a blur so people can't see that you have no clothes"
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Comment by raincole 1 day ago
[0]: well...
Comment by jdlshore 1 day ago
All the reports of productivity since then are self-reported, or using questionable measures such as SLOC and PRs, so it’s reasonable to say that productivity improvements are still unknown.
Unfortunately, METR hasn’t been able to replicate the study because they couldn’t find enough willing participants.
Comment by wolvesechoes 14 hours ago
Key thing was not that they were X% slower, but that they were slower while being convinced they are faster. Of course, any analogies with the current hype cycle are completely unfounded.
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Comment by ofjcihen 1 day ago
This has led to many of them instilling dollar limits or demanding proof of increased productivity (not just output) with the implication being if you don’t provide value with it it’s getting taken away.
So that is to say, if they aren’t happy with the price now, how will they feel when it goes up again compared to just keeping a certain headcount?
Comment by andrekandre 1 day ago
> So that is to say, if they aren’t happy with the price now, how will they feel when it goes up again compared to just keeping a certain headcount?
that got me thinking: how are companies expensing ai costs? as personnel expenses or r&d etc?Comment by b112 1 day ago
Comment by fuzztester 1 day ago
They should have done that from the beginning - demanding proof of increased productivity - if that was their goal. otherwise they were not using their brains well enough.
And you doubly don't want to work with them, first because they confused output with productivity at first. and second, because they're parroting the productivity metric.
You only need one guess for whose pockets the productivity benefits go into.
10 . 9 . 8 . 7 . 6 ...
Comment by b112 1 day ago
This cost him an extra $40, in today's dollars. No, I'm not joking. That thing ate gas like a dry camel drinks water.
This is what Fabel5 feels like. Crazy expensive. 10 minutes work pulled almost $80 is usage credits yesterday. I'd be exceptionally skeptical too, on costs, if I still had the DEV I had last week, but they were also eating that kind of cash on a very-improved, but still used as a linter.
For $200+/hr, or ~$400k/year, I'd want to see a tripling of output at least. In a lot of US markets, you can hire 3 junior devs for that.
Yes, there are cheaper options. Opus, etc. But it's really over-priced, and frankly I think the real gold now is making open models fully functional. Anyone predicating their business upon tie-in with the big boys is just going to fail, hard.
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It was much more inefficient, because it's easier to find bugs after compiling or running the code. But it is perfectly possible.
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Comment by IshKebab 1 day ago
Sorry when have you ever had to write code without being able to compile it? Tools have never been that limited.
Comment by mmcnl 1 day ago
Comment by twister2920 1 day ago
sigh
reset the clock everyone!
Comment by kh_hk 1 day ago
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Comment by iLoveOncall 1 day ago
https://simonwillison.net/2025/Jul/17/vibe-scraping/ July 2025
https://simonwillison.net/2025/Jul/6/macos-app-built-entirel... July 2025
https://simonwillison.net/2025/Jun/12/agentic-coding-recomme... June 2025
https://simonwillison.net/2025/May/23/honey-badger/ May 2025
And many more.
Not to mention that people have been using Cursor since way earlier than November 2025, with (self-reported, as always) success.
Can't wait for your Summer 2027 comment where you'll claim that coding agents really only became usable in November 2026.
Comment by simonw 1 day ago
They read to me like an accurate report on the progress of these models and tools.
In May 2025 Claude Code could help me debug a WordPress installation.
In July 2025 I reported on someone managing to get it to build them a macOS app. I got that working for myself in February 2026 https://simonwillison.net/2026/Feb/25/present/
Also in July 2025 I was successfully using one of the earliest async cloud environments - Codex Cloud - to scrape websites.
By October 2025 the most recent Claude could one-shot a simple Datasette plugin.
What changed in November 2025 was that the level of hand-holding needed to get good results dropped to the point that it was no longer credible to deny their utility.
> Can't wait for your Summer 2027 comment where you'll claim that coding agents really only became usable in November 2026.
Oh! I think I see what happened here. I said this:
> coding agents (Claude Code, OpenAI Codex) only started working really well in late November
"Working really well" and "only became usable" are not the same thing.
Comment by Chance-Device 1 day ago
In their world AI never has an impact on jobs, just like AI can never be an equivalent to a human, and the goalposts move every time a goal is scored.
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Comment by zahlman 1 day ago
> I find that productivity follows a Pareto distribution (80:20 rule) and that AI is a sharper tool in that it enables the already productive to be proportionally more productive and this effect increases as the intelligence of AI increases. So 80:20 becomes a 90:10, 95:5, 99:1 etc.
> Big caveat to the productivity claim is that it’s concentrated in lesser experienced engineers and vanishes or goes negative with highly experienced engineers.... LLMs move your baseline towards the mean. If you are below average it improves and if you are above it hinders.
Comment by cjbgkagh 1 day ago
Another aspect is that once the easier work is complete then the remaining residual is the difficult work, and this changes the relative productivity to the point where a junior developer may not be able to make any further progress at all.
Overly bureaucratic companies tend to generate easier work for themselves to the point that this work dominates their total workload. If we are to measure productivity by opening and closing Jira tickets then I would expect the junior developers to get a much bigger ‘productivity’ benefit from AI than senior developers.
Comment by DanielHB 1 day ago
Most ways of measuring productivity across an economy (in macro sense) takes into account only the transfer of capital. Meaning someone paying for something. So in this case it will be measurably zeo in most macro-economics studies.
Comment by torginus 1 day ago
- I didn't make money, since I got paid for my time
- Anthropic didn't make money, since the amount I paid them for AI is tiny
This sounds wrong to me.
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Comment by icantevenhold 1 day ago
They say the internet is for porn but it’s really to sell/buy stuff
Edit: even with LLMs the “killer” application is to make it easier to buy things xD
Comment by jvanderbot 1 day ago
1. For junior engineers a 50% increase might be less than a 10% increase for senior engineers. So the % comments are consistent with the pareto argument. Diminishing returns _can produce_ a pareto tradeoff.
2. Saying gains are "concentrated" to junior engineers can also be a function of the work assigned to junior engineers. A senior engineer might get 1000% boost over jr doing the same jr work. The problem is the reverse - the hard things are concentrated around the oldest engineers, and now "hard" can also mean "not easily claude'd"
Comment by bicx 1 day ago
If my tasks were things like squeezing 3% more efficiency out of an algorithm, that might be different. Although, even then, my PM (!) used Claude to boost the efficiency of one of our more complex Postgres queries by up to 5x, in ways I honestly would not thought of doing. It was quite humbling. A former engineer here used pgMustard on the same query a couple years ago and claimed it was as fast as it could get.
I can’t speak for the kind of work done in the higher echelons of big tech, but for us, there isn’t much that Claude can’t help with.
Comment by jvanderbot 1 day ago
The system-sweeping features I still would ask to review, but you can't argue with a DB query just getting faster.
Comment by bojan 1 day ago
Would you be kind to describe what test set-up do you have that a PM felt safe enough to deploy the changed query without the fear they'll break something?
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Comment by saghm 13 hours ago
The same techniques that were used to try to prevent regressions before we had LLMs still work for LLM-generated code, provided that you actually use them. If you have an insufficient test suite and a lax policy around who reviews code before merging, you're going to have a bad time even if you only have your seniors writing the code by hand.
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Comment by suzzer99 1 day ago
I finally got a real feature to develop and started using Codex a couple weeks ago. Before that, I was just using ChatGPT for small things. For the most part, I was doing a lot of monkey-patching and deep troubleshooting that I didn't think Codex would be good at.
I was wrong. I had no idea how smart these tools are.
I now realize, as the tech lead on a large project with me, 2 front-end developers, a full-stack-ish developer, a tester, two product people, and a PM - that I could do this entire project more efficiently with just me and the tester.
I'm doing SQL for the first time in 20 years, which would have slowed me down in the past, but not now. It used to take me an hour to program a new feature and two hours to get it to look right, if I had to do the CSS myself. Now I can do that w/o anyone's help. Writing tests used to take as long as writing the code. Maybe it still does, but that's an hour instead of a day. And it's so much less painful. There's no satisfaction of the aha moment when writing tests. It's just a slog.
We're a very small shop that usually only has 1-2 devs on a project. So we're not set up to do big projects, we aren't doing agile, and it's just a mess. We waste probably 80% of our effort just communicating.
The product team was needed/useful in the beginning to define the broad scope of the project and lay down the UI/UX patterns. But now it's like pulling teeth to get them interested in our internal client's ever-evolving wishlist. I can handle that, and always come to the product team with very specific asks when I need UI design help. Just give me the tester, who's so thorough it's annoying, to catch the weird edge cases I hadn't thought of.
I'm not saying I'm God's gift at any of these things, just that I'm reasonably competent at them. It's kind of terrifying what a seasoned full-stack dev with a decent feel for UX and the ability to manage stakeholders can do with this.
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The high-performers on the other hand are ripping through tasks at such a speed that they now have time to focus on quality and processes, so in the end you get a really well polished piece of software. However this is starting to change for the worse as the PMs are realizing what's happening and cramming more and more stuff in the sprints.
The amazing part is not the above though - it's that one needs not be an SME anymore. One of our customers asked us to make an Android application with some features of our product, which were not trivial to port. Even though we never did anything like that before, a small team was able to release it in a couple of months mostly bug-free. Without AI this would have taken at least half a year, or more. It is quite shocking to hear the status updates going from "we need this thing implemented and I have no idea what it even means" to "it's done and works" the next day.
Comment by Turfie 1 day ago
Terrence Tao is living proof, that it cannot hinder even the most elite.
There's always something you can do with it.
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Comment by Shacklz 1 day ago
In an enterprise, everyone gets to use LLMs. Everyone can create slop. In an enterprise environment, this can lead to weird situations where the senior has to put in extra efforts to contain the slop of others... so I can kind of see where the "hinders seniors" is coming from.
Comment by californical 1 day ago
I think it’s those who still care about quality (which seems to be decreasing in the industry overall) trying to keep the whole thing running, in a sea of people who think going really really fast and not understanding their code is fine because LLMs can make sense of it and clean it up later.
Just look at the condition of open source contributions recently
Comment by cjbgkagh 1 day ago
Comment by mk89 1 day ago
There are so many regulations EE companies follow and offer that no startup owner or worker could ever deal with. The moment your company shifts to that sort of work, you're automatically not anymore a startup (by definition).
Only if you get super smart robots that can manage a lot of bureaucracy etc. Starting from multicloud/region deployments, local regulations, accounting, taxes, laws, etc. Which is what companies like SAP (but not only them) do basically.
But if that happens we are all in a situation that we don't need companies anymore (the way we know them).
Comment by cjbgkagh 1 day ago
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Comment by fathermarz 1 day ago
What I found was pretty brutal. Companies asking for 4 years of agentic AI experience… pardon?
Then it hit me.
Oh they are all making shit up now and have no bar that anyone can hit because they are believing in the hype without understanding the fundamentals.
GREAT. Even as I climb the AI-Native ranks, I apparently am unqualified for any AI-Native job.
Comment by caminante 1 day ago
You just have to get past the recruiter/talent acquisition where everyone else is getting auto-rejected. You should be doing that anyway.
Comment by aakresearch 1 day ago
Comment by caminante 1 day ago
In practice, skipping the line is THE approach. How many times do you hear people say to fill out online job postings? Never. It's just scaring off good/bad candidates and bums who dont have an employee referral.
It's not even cynical to say a lot of postings are performatory compliance steps when they've already got internal candidates lined up.
Comment by andai 1 day ago
Of course, there's not much overlap between that and the way it works now. But then again, I have the same feeling about last year and this year... (e.g. Anthropic just deleted almost their entire system prompt because the models have common sense now.)
That being said, I think there's still value, even today, in playing around with the older models from time the time. (Or with very small recent models, which have similar limitations.)
Some of the habits that teaches you — i.e. careful context management and well crafted examples — do translate well to the modern environment, and give you performance gains and cost savings even with newer models. (In a word, whenever possible, show, don't tell.)
I also lament the loss of the base/text models, which were extraordinarily interesting and fun to play with. But that's a separate discussion :)
Comment by fipar 1 day ago
I guess maybe they were all trying to hire Gosling and his colleagues? …
Comment by IshKebab 1 day ago
They're basically writing down a wish list. They don't expect to get it or necessarily even care that much about some of the points.
Also "X years of experience" isn't really asking for literal years. It's a proxy for skill. They mean "as good as the average person who has been doing this for X years". If you're really good at it and can demonstrate it, that's good enough.
Comment by dijksterhuis 1 day ago
it's often HR / hiring managers throwing some numbers into a text document based on what they've heard is important for the role, not what you'll actually need for the job.
similarly, something like "has previous experience with kubernetes" doesn't usually translate to "knows absolutely everything there is to know about kubernetes". it means "you've used it at least once, ideally more, but can at least talk about when / how you used it / what problems it solved and could probably get up to speed on it fairly quickly when you join and/or in the time before you join" (kinda writing this last bit about an interesting job posting i saw that i've been talking myself down on and i really ought to be doing the opposite).
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Comment by FrustratedMonky 1 day ago
Even when Java 1.0 came out, HR was asking for 4-5 years of experience.
Seems like a decades long problem with people writing the job descriptions don't actually know what the job is.
Comment by overgard 1 day ago
Comment by georgemcbay 1 day ago
Not that I am trying to excuse it, but this is not a new thing, nor specific to AI.
Job listings that ask for X years of experience where X years is sometimes literally longer than the technology has even existed has been a staple complaint of developers over my entire career, and I'm old af.
Comment by dinfinity 1 day ago
Sebastián Ramírez seeing a job requiring 4 years of experience with FastAPI, the library he created 1.5 years before that posting.
Comment by gerdesj 1 day ago
So, leave college/uni with your "Desmond" (1) in comparative pornography in Feb 2026, buy a PC/Apple and by now you will be writing Windows Entra 2027 on your own.
Profit!
(1) Tutu - geddit!
Comment by yread 1 day ago
Comment by AndrewKemendo 22 hours ago
People forget that prompt engineering all started with midjourney and diffusion vision tools way back.
Comment by fuzztester 1 day ago
This has been almost a meme on hacker news for some time. You can google it via hn dot algolia dot com by using the right keywords.
Of course, i exaggerated it a bit, just like a lot of startups and vcs pimp their stuff, just that they do it much more, and they do it for money, while my mine was for fun. ha ha ha.
Comment by fuzztester 1 day ago
Literally some minutes later, i scrolled down below my above comment.
And saw this one.
https://news.ycombinator.com/item?id=49053201
Which doesn't validate mine, but agrees with what I said.
Except that it was posted about one hour before mine.
go figure.
Comment by fuzztester 1 day ago
Comment by dahart 1 day ago
Also, what is “AI exposure” in 2015? LLMs hadn’t been invented yet. I did just read some of the cited paper. Essentially the quintiles boil down to use of computers, not really use of AI as we know it today. I know LLMs aren’t all AI, but the thing that’s missing is the distinction between “AI” that can play chess and LLMs that can actually do your job, which have only existed for maybe a year.
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(shame x is the easist way I have to post two images quickly)
dots seem to fit bls pretty well. Just to bound the effect of the spike, that is a +10% jump, so over a 3 year window it would produce a +3% bump. If they do a backwards only, it'd lag by up to 3 years. So, it's plausible/feasible, maybe not definitive.
Comment by chewbacha 1 day ago
This intuitively makes sense and generally agrees with my experience. LLMs move your baseline towards the mean. If you are below average it improves and if you are above it hinders.
But also in my experience, my memory retention of the work done with an LLM is worse than doing it myself self. This leads me to believe that the lesser experienced engineers are not gaining experience!
My tinfoil hat says that this is what tech CEOs want. They want workers that are low skilled and can be paid less.
Comment by VladVladikoff 1 day ago
My company is small, but my opinion at the moment is the opposite. Low skill workers don’t notice the flaws of what LLMs produce, I am no longer interested in hiring any juniors, as all they do is copy and paste LLM output without thinking, which anyone could do. It is the senior engineers who are most valuable to me these days.
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Comment by chewbacha 1 day ago
Which I happen to agree with.
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Comment by HarHarVeryFunny 1 day ago
I think it's useful to divide companies doing software development, as well as specific jobs within a company, into two groups:
1) Companies where software is the product - where what you are working on is directly what is making the company money, and differentiating what they sell from what other companies are selling. These are the jobs you want, and where you will be valued.
2) Companies where software is only a component of the product, regarded as non-critical, or not product related at all - just internal IT systems. These are NOT the jobs you want!
In a type 1) job the company (unless it is run by idiots) recognizes that better developers = better product = more profits. They will seek out experienced skilled developers and pay them what the market demands.
In a type 2) job you are not regarded as a profit-generating asset, but rather as overhead - an expense to be minimized. The company will be looking for the cheapest, least experienced people they think can do the job. Maybe they will outsource, and/or nowadays try to use LLMs as a way to avoid needing to hire better quality developers. The development work may still in fact be demanding and require skilled developers to be done well, but if the company mindset is that developers are an expense not an asset, then they will try to get the job done with the cheapest labor regardless.
So, yeah, if at all possible don't work on things like IT systems or on products where it is not blindingly obvious to management that software quality is directly related to profitability.
Comment by mistrial9 1 day ago
Comment by driverdan 1 day ago
If anything, it now requires more skill to maximize. If you have strong product and engineering experience you can get even more out of an LLM than one of those skills alone.
Comment by gcanyon 1 day ago
Do you think this is more because you are less close to the work? Or because there is simply more work being done/more to remember, so you're remembering a similar amount, but a smaller fraction?
Or both, or something else?
Comment by chewbacha 1 day ago
This is also born out in the research which has demonstrated reduced retention of content when authoring was facilitated by an LLM. Over the long term, I believe this is widen a chasm between experienced and inexperienced engineers.
While not all CEOs will feel this way, it will not surprise me that knowledge workers will be treated as disposable, even if their work is invaluable. If they can hire a junior escort for the AI they will. That junior will also be scale goated when things go wrong.
Comment by conqrr 1 day ago
Comment by spiresofagartha 1 day ago
Maybe it's only me and my inexperience, but only reviewing doesn't make me as "in" as doing it myself.
Comment by bloaf 1 day ago
In my workplace, we're going to decline to renew some software subscriptions because a non-programmer vibe-coded their replacement in a week.
The impacts are here, they're just not evenly distributed yet.
Comment by lelanthran 1 day ago
That's gonna turn out well :-)
Maybe they only need it to work for the next 6 months of enhancements...
Comment by tossandthrow 1 day ago
But I think it is most productive to assume that it does not.
I am a very capable developer, and I convince myself anymore.
Comment by nicce 1 day ago
Interesting to see the impact in the long term when battle tested software gets replaced with vibecoded variants by non-programmers. Does it increase data breaches or quality actually goes up?
Comment by bloaf 1 day ago
But in reality, a lot of corporate software exists just because there are plenty of companies who are afraid of owning code. They don't want to maintain any in-house coding skills, and therefore are willing to buy literally any vaguely-relevant CRUD app that the manager heard about at the conference. I don't think replacing that class of software with vibe coded alternatives will be any worse, because the bar is starting on the floor.
There are entire software categories that consist entirely of code that is only one or two evolutionary steps away from some engineer's spreadsheet originally written in 1995. One fine example I work with has changed its backend database 3 times in the past 4 years. Their most recent decision to use mongodb came with the questionable decision to store json as a raw string literals complete with bizarre escaping inside a database literally designed to store json-shaped-objects.
I don't think Opus could store data that poorly, even if the end user prompting it didn't know what they were doing.
Comment by fyredge 1 day ago
Comment by sethammons 1 day ago
Over lunch, Claude made a minimal toolbar app that lets me adjust down the brightness.
Often, you don't need battle tested. And you don't need a bunch of features.
The ai could have shipped my video feed somewhere I suppose, if I were unable to read its code.
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Comment by layer8 1 day ago
This is curious to me, as at my workplace we never had such subscriptions for small- to mid-size stuff and always built the corresponding tooling in-house.
Comment by bojan 1 day ago
Comment by danaris 1 day ago
And there probably always will be.
When the choices are "hand all of our highly sensitive internal data over to one of several other companies, all of which have questionable financials and very cozy relationships with adtech" or "invest in a whole bunch of expensive GPU servers plus internal talent to run our own models", vs "keep on doing what we've been doing, which is still working just fine", why would a non-tech Fortune 500 company choose either of the former options?
Comment by ballsac 1 day ago
Yeah, sure you are. Report back when it happens.
Comment by bloaf 1 day ago
Comment by coffeefirst 1 day ago
(Replacing overpriced garbageware with something I scraped together in 3 days is my jam. But the specifics matter a lot.)
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Comment by egr 1 day ago
Is instrument spec sheet management focused on storage and presentation, and occasionally updating values such as service interval, calibration dates etc ? If so I also find this plausible.
Both use cases are focused in terms of use case complexity (especially if your company is focusing on your requirements only as opposed to software vendors covering variations), low in complexity in terms of involved parties, and inter-system boundary crossings.
Very interesting. The spec management is probably the higher risk use case, but I assume you have proper engineering review and a tight test strategy to control this aspect.
Comment by ballsac 1 day ago
Comment by zkmon 1 day ago
And then he also says that a certain model is too dangerous to release.
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Comment by sethammons 1 day ago
Software developers have always been in the job of automation and replacing human work. Capitalism means investors reap (the majority of) the benefit.
Comment by chrsw 1 day ago
I doubt we're unique. Chat bots are useful. But it will take years, possibly decades for work to transform to due to AI. Probably longer for everyday life. The diffusion of new technology, even something as profound as AI, has to fight the friction and realities of the real world. Always has.
Comment by aintnolove 1 day ago
But AI is becoming much more pervasive than websites. And the level of friction isn't as high as you might think, because people are already constantly on phones. It's only a matter of time before MS Copilot gets so good that even the least tech-savvy people start asking AI to do their work. That same HVAC service owner can tell AI "there's a big emergency at Bob's Burgers in Brentwood, get 2 of my guys there ASAP. We can reschedule a visit if needed".
These are not trillion token operations either. It will be affordable to do this. And generic office commands like "schedule this", "contact X about Y" are 3-5 years away from being super usable. And that's mainly because there's a lot of gruntwork for enabling agents to access the right data.
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Comment by keeda 1 day ago
1. Most of the productivity studies in Figure 3 about are from the 2023-2024 era. (Which is why as some comments note, Copilot is actually way up there in the numbers. Note that this was from the era of spicy autocomplete and long before coding agents exploded on the scene.)
2. AI adoption at work is actually very low: even though 50%+ of Americans currently self-report (major caveat) using AI at least weekly, they use it for only 6% of work hours. (You can play with the charts here to see this [0]) This is what the recent Google study [1] called "broad but shallow use."
Notably, the same surveys find time savings of 2% of working hours, so a whopping 30%+ productivity boost per hour of AI used. And this is across industries. Despite being self-reported, it does line up with many of the other controlled studies (see TFA and [2, 3]). Some economists suggest that even with this low level of adoption, we may already be seeing the impact on labor productivity at national-level aggregate statistics! [2, 3]
As I said in another thread, my concern is that the impact on jobs is only beginning because 6% of work hours is a very low number. However given how useful people are finding it based on self-reported, micro- and macro-level numbers, adoption is only going to up, both in breadth (more people) and depth (more tasks). I fear the impact will happen gradually, as adoption inches up... and then suddenly.
[0] https://www.genaiadoptiontracker.com/
[1] https://blog.google/innovation-and-ai/technology/research/un... (discussion: https://news.ycombinator.com/item?id=49020335)
[2] https://www.stlouisfed.org/on-the-economy/2025/nov/state-gen...
[3] https://aleximas.substack.com/p/what-is-the-impact-of-ai-on-...
Comment by newsomix9xl 1 day ago
If AI means job cuts and not using AI means job cuts but no one really tracks AI impact that means performative adoption of AI is safest, and real gains are to be sandbagged as innate magic hand waving.
At my work I'm one of the few who says "I made this with Claude" and the near impossibility of using AI with internal email etc for security reasons means AI use is one-shot wonder oriented (for me, in my experience).
If AI usage was incentived with actual bonuses and praise it might go over better. So far I haven't seen that. Its just implicit threats.
Comment by agumonkey 1 day ago
Comment by tossandthrow 1 day ago
What we should fear is the startups.
Legal startup demonstrates they can do legal work at a fraction of the price. New generation of banks can underwrite at a fraction of the cost, or new insurance companies can insure much cheaper.
This will force the incumbents to reduce head count and use Ai.
Comment by agumonkey 1 day ago
Comment by asdf88990 1 day ago
Once the talk of “we will be laying off people based on productivity in upcoming months” starts; probable go kamakazi.
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Comment by dspillett 1 day ago
* I don't get on with remote work, which came as a massive surprise to me in 2020 (until then I really didn't think I was a people person!). The flexibility to work away when needed is lovely, I've had that for a couple of decades and made good use of it for things like when I needed to look after ill parents for a time or just needed to be somewhere quieter than the office to concentrate, but near full-time remote working screws with my mental health. I go into the office and while there are other that do I'm still effectively remote as the other people there are not directly on my team. This is becoming much worse as we have been bought by a larger concern so instead of ~35 UK based people we are now 350+ spread between the UK, various bits of the US, and a large concern in India.
* The ridiculous over-complication of everything. People architecting to be the next Amazon before they even have three customers or tens of users. Everything being split into services, actually adding performance and management issues for a great many far-from-Amamzon-scale use cases, because that is what you are supposed to do not because it is the right tool for the job, etc. Even people who genuinely agree with me do it for CV-fodder. It just winds me up.
* A bunch of smaller things, but they are insignificant compared to those two.
On top of all this, comes AI and agenic programming. I don't want to do it. "Think of yourself as a manager" people say, "Fuck no!" I reply as I've avoided being a manager of people all these years and don't want to manager automated people either (in case a sentient Claude instance is reading: sorry, but nothing personal, I don't want to work with humans that way either). I want to do not manage, thanks. I'm a sad git who likes the nitty-gritty bits that everyone else seems to desperately want AI to do. And then there whole "it was created with the aid of mass piracy" issue (a 17-year-old gets huge fines and in some cases prison time for copying Metallica tracks without licence, big corp copies 'king everything ignoring all licences/restrictions and gets a very light slap on the wrists) that makes me not want to be any part of it from a principals standpoint.
I'm refusing to play ball, and planning my exit. It might mean a considerable pay cut as there are very few jobs that are not largely remote, becoming significantly AI infested, or both, that I am qualified for, but I'm unhappy enough that I'm going to be fine with that. I have the mortgage paid (it is a small place, but it is all mine), no partner nor offspring who will be inconvenienced by my sudden reduction in earning potential, some savings worth speaking of, and room to dial down my expensive hobbies & tastes quite a bit, though I am relatively lucky here: most people do not have the small-but-useful financial comfort zone I've built up over the years.
If my current overlords try fire me for non-compliance before I'm ready to leave of my own volition, I'll be arguing "it is material change of role, you yourself said it was like a move to management, UK employment law says you can't force that or sack me for refusing". Of course that makes redundancy possible (we need less legacy devs, we can offer you a sidewise move to an agenic dev role or redundancy) but I've been around long enough I doubt they'll go there due to the expense (if they do, then thank-you-very-much!).
There are a few tech options I can explore that I might be qualified for, if those don't pan out then I look forward to the last decade-to-decade-ana-half of my working life in hospitality, or maybe as a hospital porter, or whatever. If I leave soon, I might latch onto a good path elsewhere before the mass displacement of dev & other tech workers is clamouring for the same things then I'll at least be a step ahead of you all there!
Comment by dzonga 1 day ago
'a.i' or to be more precise are really good at some tasks. but a job is a set of tasks. jobs are not created - only discovered. that's what the a.i labs miss. hence we see that 'a.i' is not having an impact on jobs.
I wrote a bit about it here - https://news.ycombinator.com/item?id=49048723
Comment by pjmlp 1 day ago
Agency work is now done with even smaller teams than a decade ago, thanks to the adoption of SaaS, iPaaS, serverless as main delivery technologies.
AI empowers to do even more with even less people, however there isn't enough project demand to keep everyone busy.
Comment by giantg2 1 day ago
Comment by keeda 13 hours ago
The amazing thing is that these numbers are from the time where AI coding was basically "spicy autocomplete."
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Comment by FrustratedMonky 1 day ago
Maybe the scary thing, the economy itself is suffering which is causing the unemployment, not AI.
Comment by iLoveOncall 1 day ago
Actually the first graph shows that the most exposed to AI an industry is, the LEAST affected it has been by unemployment...
Comment by FrustratedMonky 1 day ago
Comment by iririririr 1 day ago
it's all Ai. The economy is great. i mean if there was any sign the world was trading oil not in dollars, they would have moved into Venezuela and Iran by now.
Comment by rush86999 1 day ago
One missing point: careers that require communication, especially person-to-person, won't be replaced by AI. Why? Because people don't like to speak with AI when they have a hard pain point to solve. It's not about intelligence; it's about trust and relationships that AI cannot replace.
Comment by tossandthrow 1 day ago
A crucial point is that the amount of these careers might reduce dues to structural changes of the job market.
Just: yes, SaaS companies can do their work faster and can downsize. But a sizable portion of SaaS companies get to downsize entirely as their entire purpose is disrupted.
Comment by nobodywillobsrv 12 hours ago
Never have I had such poor matching and triage as I have over the last 6 months.
It's truly bizarre. I get the feeling that some of the humans left in companies are gatekeeping on some kind of guess my password game.
A common pattern is a company will reach out and see if you want to chat and then suddenly act as if you are interested and give you a weird interview before you even get a sense of it's a good match.
It feels like this might be that less competent teams are relying on less competent recruiters or AI recruiting? Just a guess. Also finding that the AI recruiters are sounding nice but doing very little work in the end.
H2H still largely unsolved. DM if anyone is also interested in h2h reco in age of ai
Comment by ChrisArchitect 1 day ago
The AI jobs apocalypse probably isn't coming anytime soon
Comment by steele 1 day ago
Comment by sensanaty 4 hours ago
https://news.ycombinator.com/item?id=48743713
---
We've just done an official evaluation at work, using extensive statistics on our gigantic monorepo in a company with ~2000 devs over the course of 2 years, everyone from hardware engineers to regular old frontend engineers. It's a highly profitable and mature public company, and has been for going on a decade at this point without missing a beat. We were given infinite access & budgets to basically any and all AI tooling we could imagine, and we have several "AI Native" teams (whatever the fuck that even means). We're doing agentic coding, we have harnesses of all kind, skills, we have many teams doing spec-driven development, designers using all the various things like Figma Make and access to tools like Devin/Factory Droid/Claude Code/Codex/etc.
This is all to say, we as a company are using AI a lot in all possible corners, but thankfully our leadership isn't schizophrenic and isn't mandating everyone hit token limits or whatever, it's more of a "Let's see what works and what doesn't" type of thing, and we measure a lot of statistics. Nobody here really cares whether LLMs are the next coming of Christ or not, as a company there are many people (even in SLT) that are indifferent to LLMs, and many who are reasonably hyped.
I wish I could link to the actual document we were all shown since it has a beautiful breakdown of the methodology and a fine-grained breakdown of the stats and the categories measured, but in the grand scheme of things, ALL the AI tooling we have implemented (at least on the engineering side of the equation) has contributed to a total of... drum roll please... 7 (seven) Percent overall productivity increase! The most productive teams saw a productivity increase of around 20%, while some teams actually saw drops in productivity into the negative percentage points. My team, none of us really give a shit about AI and we're somewhere in the 3-5% range on certain categories of tasks, which I'd say is a fairly good assessment.
Productivity here is measured in many ways, including but not limited to speed of MR review and merge times, feature/ticket/roadmap closure/delivery, rollback/revert incidence rate, how often people interact with the MR review bots and implement their suggestions/fixes, how many times people check back on AI transcriptions/meeting notes (hint: Nobody looks back on any of it, it's all just noise that gets generated and never actually referenced outside a few extremely rare cases) and many more things I'm forgetting. It is an imperfect number of course, because measuring productivity in engineering is a sisyphean task, but in my opinion it is accurate to the reality on the ground and outside of all the hype and marketing bullshit.
So, I remain thoroughly unconvinced of these personal anecdotes of people being "massively" more productive, especially once you factor in the fact that we now have a 2000EUR budget/month/dev for all the AI tooling, those productivity numbers start looking pathetic once you factor in the costs (which are only increasing as the AI companies need to start recouping the gazillions they've burned). Some teams have started begging to disable coderabbit and other similar tools in their MRs because they're producing nothing but walls of noise that makes reviewing any MR a nightmare of sludging through endless slop of useless bullshit, ours included.
Comment by tancop 1 day ago
the root of the problem is the same as most other economic problems in this world. financial capitalism is designed to reward short term profits, and shareholders create an asymmetric incentive where ceos dont really get fired for doing too many layoffs but can be fired easily for not doing enough.
Comment by mberning 1 day ago
Comment by tossandthrow 1 day ago
This is exactly the time to re organize. Not necessarily lay off, but some people might be asked to do other things or made redundant.
Comment by colesantiago 1 day ago
This is a great opportunity.
There will be new jobs.
Comment by QwenGlazer9000 1 day ago
Comment by colesantiago 16 hours ago
There will be new jobs.
Comment by exabrial 1 day ago
Most of HN recognized the "We're firing people because AI makes people efficient" as one of the stupidest sales pitches ever and the CEOs that fell for it are just poorly ran companies that outed themselves.
AI is just another cycle in technology that is genuinely useful. The companies that are going to jump the gap are those that are hiring to use this new skill. If 10 workers pre-AI yields you 10x, and post AI yields you 100x, you don't cut down to 1 worker so you can keep delivering 10x. You invest, ruthlessly train, hire, and surge forward and leave your competition in the dust.
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Comment by codingdave 1 day ago
Because AI can do some things. Not everything. Applying it to the wrong problem reduces productivity.
Comment by giantg2 1 day ago
Not really. The stats should show that factory workers as a percent of the workforce has been declining.
Thw leadership at my company has said they plan to do more with the same people rather than lay off. But they also seem to have reduced hiring and are removing certain types of roles.
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Comment by andrekandre 1 day ago
> If 10 workers pre-AI yields you 10x, and post AI yields you 100x, you don't cut down to 1 worker so you can keep delivering 10x.
in that scenario then should we be expecting to see a 10x or so boost in revenue as well?Comment by ralusek 1 day ago
Now, I don't want any additional engineers. Not only because I don't need them anymore, but because the prospect of having junior engineers using AI is absolutely terrifying to me. I can't eyeball their code to get a sense of how good of an engineer they are anymore, and I can't possibly review all of their code because of how much code AI can output now. So they're going to be outputting a ton of mostly high-quality code that could be making horrible mistakes that are much harder for me to catch now.
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Comment by ajb 1 day ago
This is the real threat today. The growth of the middle class was essentially the growth of jobs in which the workers have human capital in their skill and experience again. That experience is being slurped up by LLMs and other models.
The question is whether "LLM operator" is really going to be a profession which requires scarce skills and experience, or whether many companies will be operable with less well-rewarded workers. I think that those who think there's an obvious correct prediction here are overconfident.
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(Though I’m biased, I personally feel it’s an anti-human technology, the world would be better without it)
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Comment by JSR_FDED 1 day ago
- benefits of AI murky to slightly positive
- hiring impact limited except for junior level
The problem is that these two statements each have massive implications, so instead of treating these findings as point in time snapshots they are the whole ballgame and should be explored in depth.