CEOs admit AI had no impact on employment or productivity
Posted by tcp_handshaker 1 day ago
Comments
Comment by prh8 1 day ago
Our stock price has also gone down 70% in the last few months
Naturally, we're pivoting our platform to put AI front and center
Comment by dehrmann 1 day ago
Comment by Eddy_Viscosity2 1 day ago
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Comment by rechargedaily 16 hours ago
Live results: rechargedaily.co/state-of-burnout-2026
Comment by davebren 1 day ago
Comment by flextheruler 1 day ago
Comment by grebc 1 day ago
Comment by gozucito 1 day ago
The evolution of harnesses like claude code or open cause, and metaharnesses like Ralph loops, gas town, claws, etc. Will progressively allow for gradually better results and abilities even if models stopped evolving, and if the Mythos eval numbers are to be believed, there is still no hard ceiling to be felt yet.
At the same time, small models that can run on PCs VRAM/UNIFIED RAM have like Qwen are becoming more useful.
I predict that having more and more loops within loops within loops and layers of cloud/local models of different capabilities will solve a great many limitations of LLMS today...at the cost of speed and token count.
We've never had a tool that is at the same time so unreliable and complicated as GenAI before. It will take us a minute to figure out how to use it properly.
Comment by belZaah 1 day ago
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Comment by ritcgab 1 day ago
So we are all in this "scheme".
Comment by charlie90 1 day ago
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Comment by zihotki 1 day ago
Levels: 0 - no AI, 1 - AI enabled (copilots), 2 - AI assisted (autonomous agent pipelines not on your PC) , 3 - AI measured.
Comment by cmiles8 1 day ago
The most likely outcome is an AI bubble correction that will be somewhat painful and wipe out many/most AI startups, followed by AI settling into day to day in a way that’s useful and found in many places, but not world-as-we-know-it-ending like the AI bros predict.
Comment by ua709 1 day ago
[1] https://www.electronicdesign.com/technologies/embedded/digit...
P.S. I'm not saying fuzzy logic doesn't have applications, I know rice cookers are a thing, but I think it's safe to say we have other options for controlling non-linear systems these days.
Comment by negura 1 day ago
at least according to industry analysts, the thesis at the moment is that reasoning models (which loop over their own output and backtrack if necessary) will bring fidelity close to 100% and find novel solutions not present in the training dataset. but they consume more tokens, they require more computing and the infra for it is still being built. so the outlook for those impacts is ~2030
Comment by newyankee 1 day ago
Comment by afavour 1 day ago
https://www.thecity.nyc/2026/04/06/waymo-driverless-cars-tes...
Phoenix is probably about as good a location as you could get for a self driving car. It’s not yet clear how wide their success will be outside of that niche.
Comment by cmiles8 1 day ago
Comment by acdha 1 day ago
That’s more “build part of it, say you built all of it, and wonder why they don’t come”.
Comment by civvv 1 day ago
Comment by oblio 1 day ago
So, basically the easiest robotaxi market on the planet? Call me when it works in Bucharest, Mumbai, Istanbul, Cairo, etc.
For software the last 80% of effort needed to finish the 20% remaining items is the hardest and hardware is even harder.
Comment by grebc 1 day ago
Comment by nothinkjustai 1 day ago
Comment by namr2000 1 day ago
I am sure you can find truly out-of-distribution cases where the car will make a mistake, but the data shows that this is more rare than a human driver making a mistake.
Comment by acdha 1 day ago
Comment by nothinkjustai 1 day ago
Comment by palmotea 1 day ago
Even if it doesn't result in increased productivity, AI can still take the fun out of the job (goodbye coding, hello code reviews all day).
Comment by hsuduebc2 1 day ago
Comment by grebc 1 day ago
Comment by somewhereoutth 1 day ago
Comment by cmiles8 1 day ago
Comment by beloch 1 day ago
On one side, there is the usual process of figuring out how to properly use this new tech. It is to be expected that some experimentation is necessary to figure out what applications AI boosts productivity for and what applications it doesn't. There is unusually strong evangelism pushing AI into everything, so the negatives are going to be salient and may make it hard to spot some of the successes.
On the other side is something a little bit new: Deliberate enshittification. OpenAI and others no doubt saw the power crunch coming years in advance, yet it's still happening and is, ostensibly, the reason why prices are starting to go up. This was not unexpected. It's the business model. Build to the capacity that is cheaply available while offering your customers a sweetheart deal to get them addicted, and then jack up the prices when the competition has no cheap power to build upon. The result is locked in customers and locked out competition.
On one side, you have people learning when AI is appropriate and how to use it efficiently. On the other side, you have a small number of AI companies trying to extract every last bit of value so that any productivity gains wind up in their owners' pockets. Will the gains of more appropriately applying AI be entirely wiped out by enshittification?
Comment by Simulacra 1 day ago
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Comment by cmiles8 1 day ago
Comment by plaguuuuuu 1 day ago
I just cannot see WITCH doing this without exponentiating the usual problems with outsourcing. I've seen some horrors. Can't wait for contractors wielding unprecedented chaos.
Comment by Simulacra 16 hours ago
Comment by bilekas 1 day ago
Comment by cyb_ 19 hours ago
In other words, moving money/spend from non-AI projects to AI projects/cost. This includes trimming the bottom X% of performers to reallocate that money too.
In most cases, it is not about current productivity or AI doing people's jobs.
Comment by pragmatic 1 day ago
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Comment by fzeroracer 1 day ago
It's why software has become far more unstable. There's nobody around to actually maintain it.
Comment by coldtea 1 day ago
Just spin for not exactly bright small time stock holders.
Comment by antisthenes 1 day ago
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Comment by tcp_handshaker 1 day ago
Comment by ChrisArchitect 1 day ago
Some related discussions recently and months ago:
90% of CEOs Say AI Changed Nothing. The Other 10% Have a PR Team
https://news.ycombinator.com/item?id=47766164
Majority of CEOs report zero payoff from AI splurge
Comment by ofjcihen 1 day ago
Don’t get me wrong, I use these tools daily. That being said I’m having a very hard time finding where the productivity gains are.
I imagine I’m far from alone in that search and when you pair that with the constant marketing and glowing “analysis” from some of the enthusiasts about how this technology is “solving coding” or “changing the face of security” or even leading to AGI it starts to tickle that part of my brain where I keep blockchain, NFTs and copper bracelets.
So TLDR the tech is good but the hype-slaves and their masters are killing it with overpromising and under delivering.
Comment by runako 1 day ago
This is simultaneously one of the easier management KPIs for employees to hit and one of the least meaningful.
https://www.wsj.com/tech/ai/ai-work-use-performance-reviews-...
Comment by KajetK 1 day ago
Comment by ua709 1 day ago
There really are many programming jobs that are rote and I have no problem believing that an LLM based tool can learn the pattern and regurgitate with the tweak de jour. In those jobs LLMs probably do increase productivity.
But there are other programming jobs that are not rote and there is no pattern to learn because you haven't done the thing yet. LLMs aren't any more useful than a normal base library would be, and if you're already good at using a library of code, they're not a productivity booster and often, in my experience, a hinderance.
I think another point is the prompt actually forces the engineer to spend a moment to actually think about what they're doing and make some kind of plan. Pre-AI tools way too many programmers just jumped straight into problems without thinking what they were doing figuring they could code their way out of anything and ending up stuck in some cul de sac and having to back track. And if they just stopped and made a basic plan they wouldn't have that issue. Forcing engineers to make a plan, who wouldn't otherwise do so, before they start, could definitely be a productivity booster for them.
Comment by ytoawwhra92 1 day ago
So why are you using the tools? Personal curiosity? Workplace mandate?
I've made measurably more and faster progress on both professional and personal projects since adopting these tools. Sometimes assisted is less productive than unassisted, but the net gain is pretty obvious to me.
Comment by ofjcihen 1 day ago
Comment by throwaway422432 1 day ago
An AI is like delegating it to the junior programmer you don't have. You spend 5 minutes writing the spec rather than an hour coding.
It's usually something you could do yourself, and just can't get motivated to type out the code in the moment.
Comment by sph 1 day ago
Comment by ofjcihen 1 day ago
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Comment by slopinthebag 1 day ago
I use the tools, but I'm under no delusions that I'm not just being lazy. I could just do it myself, and in some cases it would take roughly the same amount of time, but I can scroll TikTok while it dutifully churns out code.
Comment by grebc 1 day ago
Comment by andrekandre 1 day ago
> for the love of all things holy why are using them if they don’t provide any benefit?
like most tech trends: fomo and hypetbf, there is some benefit there but its much more nuanced than the hype suggests (as usual)
Comment by bluefirebrand 1 day ago
I'm really struggling to understand why you would use them that much if you aren't sure they are more productive. Is it just a more enjoyable workflow for you?
I ask because I find AI assisted workflows extremely painful. Constantly pulling me out of flow, like driving in gridlock traffic.
Comment by ofjcihen 1 day ago
That and using it like a search engine feels a little like having good Google back.
Comment by nothinkjustai 1 day ago
I’m not surprised about productivity though. Efficiency gains are limited by the actual bottlenecks. And truthfully, I think people are deluding themselves a bit about how effective vibe coding is and how much faster they are actually moving when you consider developers still need to form an understanding of the codebase and its systems.
Outside of coding, is there really a use case for LLMs that has the potential to make big efficiency gains? Idk.
Comment by smalltorch 1 day ago
So I'm not actually being more productive, but I've cut my costs significantly to do the same things I could do before.
Comment by slopinthebag 1 day ago
Of course ymmv, and if you find yourself paying subscriptions for stuff you can replace with vibe coded apps, all power to you.
Comment by 10sunbee 1 day ago
Comment by lumost 1 day ago
For example, consider a commodity business for software product X. All vendors of this product had their costs reduced by a factor of 100 over night for developing new product. They could increase their profits, lower their price, or re-invest the dividend. In software, the buyer usually buys on quality - so they all re-invest.
Now they are spending the same amount on product development, for the same price tag, and earning the same profit - but they might be shipping much faster.