This doesn't seem like a well-thought-out post. I mean, I probably could have told you that from the fact that it's either pro-AI or anti-AI (in this case the latter), but this is a particularly poorly thought out post. Others here have pointed out the water-wasting red herring, but there are several other pieces of nonsense here — the general environmental doom-mongering, and labeling recursive self-improvement as "mystical", for example.
Me, I pointed Claude Opus 5 at a C codebase I've been working on for years and it immediately found five serious bugs and told me how to fix them, as well as how to use Linux system calls I wasn't familiar with to solve some other problems. And I gave it a new language for PEGs I'd written up a couple of years ago, and it wrote me a working implementation in OCaml that afternoon, fixing several bugs in my example grammars along the way and resolving a conceptual problem I'd had a roadblock on. I asked Fable 5.1 to implement a minimal proof assistant, and it wrote a clone of J-Bob in Python, which I'm studying now. Although there is a certain firehose quality to this stuff, I sure don't intend to use AI to actively de-skill my brain.
That doesn't guarantee that AI will be a beneficial innovation overall, of course! As with most innovations, it probably depends on the balance between people being able to use the innovation to gain control over their own lives, and people being able to use it to gain control over others' lives. (Barring a FOOM scenario, of course, where our prediction ability is nonexistent.)
So, I don't think a pro-AI post can be well thought out, either. It's too early and chaotic to understand what's going to happen, and it may actually be uncertain. Pro and anti are both far too simplistic.
Not criticizing or calling into question the contents of the posts or your rebuttal. Just wanted to point out this is not a Normal HN post or blog. Most blogs have the self removed to some degree or ultimately focus out of the self. This is clearly a journalistic blog, a shared diary entry sort of prose. You can see it in the first paragraph. It is basically intended to be emotive or get across the idea of getting emotions out about a topic, and ironically this is what makes it a not-bad-post.
Basically, I don’t know how well thought out it is, but the prose argues that the point isn’t for it to be an objective take, and that if it were well thought out (ie highly iterated on and more objective or factual than subjective) some personal meaning that was intended to be expressed is lost along the way.
In other words It may have not appealed to you but that’s fine - you might just be outside the target demographic. In any case I don’t think it necessarily should be more well thought out. I prefer that these pieces exist or have their place. I definitely prefer their existence to a world where every personal Blog post has to arise from fiduciary or technical concerns, instead of from the soul. This is a soulful blog. I like it.
It just seems like a lot of hate resulting from dysfunctional responses to life circumstances — admittedly, probably pretty bad life circumstances, from the sound of it. Spreading hate online, especially accompanied by lies as in this case, doesn't seem like a socially positive action from my point of view. The author should have kept it to themself and maybe talked to someone who could give them a better perspective, rather than letting their hate out into the world to multiply.
My impression was that the frontier AI coding models are kind of resetting the barriers to entry/reward ratios to before the dot com boom, when people didn't go into this career for money, and so most folks that ended up in it were the 1% kind of talents who really wanted it. Perhaps that's an elitist thing to say? I don't know. That's not to say that AI is pushing people away from computing, it's just that it's creating such massive low resistance paths to getting to the goal without the "productive friction."
p.s. and at the same time, it's such a fantastic learning tool. It distills the intuition of a whole world and is able to transmit it on demand, like in your examples. It's an interesting dichotomy.
I don't know, maybe? I think it's opened the doors to a lot of people who don't really want to program, but do want, for example, a studio appointment booking management system. Which is good; people's needs matter just as much if they don't enjoy programming. You can use it to create a pretty wide range of things, which seems like it's going to change the things that get created in hard-to-predict ways.
Structurally, though, I'm sort of pessimistic. Throughout my career as a programmer, I've earned much more money than electronic engineers whose skills are mostly very similar, and probably much of this happy situation is due to the fact that my productivity depends only on me having access to a computer with GCC and Perl or Python on it, and the internet. If I were living in rural Malawi, I probably couldn't practice my trade, because the US$200 it takes to buy a working laptop is a year's wages there, and people lack the social permission to innovate. (William Kamkwamba's astounding achievements under those circumstances deserve more recognition. Read his autobiography!) But, if I work in any developed economy, that's somewhere between 1 hour and 20 hours of my earnings, so I'm not dependent on investors to create jobs for me.
By contrast, electrical engineers mostly can't ship their designs unless an investor is willing to put up the capital to produce a batch of PCBs or chips — probably three batches or so before you get a fully working product. If you're working on a cutting-edge chip, that's several million dollars, so you're probably not going to save that up while working as an employee. This puts electrical engineers in a much worse bargaining position relative to investors. To a smaller extent, the same thing applies to machinists, auto mechanics, and many other skilled workers: they only get jobs if investors invest to create jobs for them.
The capital-intensive nature of current AI seems like it might push the negotiation equilibrium for programmers two or three orders of magnitude in favor of investors.
But it might not work out that way, and, at least at the moment, I'm finally bringing about numerous projects I'd been procrastinating on for years.
> It distills the intuition of a whole world and is able to transmit it on demand, like in your examples. It's an interesting dichotomy.
The only problem I have at the moment is it's very prone to hallucinations, even now, yes frontier models astra fable with all the bells and whistles. This makes it hard to confidently use while learning because I have to be on the lookout for lies while I'm learning, which is precisely the moment I am least able to distinguish them. So instead theres just a constant low lying dread.
Nonetheless, I am able to get some value out of them. Just not all, everything requires manual effort to duplicate and check which you should probably be doing anyway as part of learning
I mentioned the minimal proof assistant I elicited last night. When Fable 5.1 thought it was done, I asked how we knew the prover was sound (which means, in the jargon, that the theorems that it proves are actually true). It checked and immediately found five different ways it could "prove" false theorems with it (and fixed them).
Then it suggested writing a fuzzer to try to flush out more soundness problems. It loves fuzzers! And usually they are an excellent cost/benefit tradeoff. However, in this case, I questioned whether a fuzzer would ever actually succeed at finding proofs of a theorem it was set to prove, even unsound proofs, and after doing some tests it admitted that the fuzzer it had proposed would have been completely useless.
Then the conversation was incorrectly flagged as me working on a malicious security attack, so I was downgraded to Opus 4.8. I switched back to Fable, renamed the file in its scratchpad, and asked it to please use the term "generative testing" instead of "fuzzing". Thanks to not using the computer-security name for generative testing, there were no further false flags.
Then, this morning, I was reading the spec it proved its program fulfilled, and asked whether a certain trivially incorrect alternative program would also fulfill the spec (a misformalization problem rather than a soundness problem). It churned away for a while, discovering that while, actually, no, that program would be rejected, a different trivially incorrect program would pass, and credited me in the docs with pointing out the issue. I pointed out that in fact the issue it had found was completely different from my stupid misreading of the spec. It fixed the doc.
Fable 5.1 isn't Mythos but it's generally considered to be a "frontier model".
So, from my point of view, the whole experience has been a constant fractal of hallucination, in which I have to constantly struggle to keep my grip (and Claude's grip) on actual reality, because it's so willing to make up surface-plausible nonsense.
Probably over twenty today in my work day alone. Its a normal part of working with agents. They do not always have the context they need, but fail to be aware of this.
Misinterpreting the results of performance testing it had just run to argue for the exact opposite of what the data it generated showed.
Stating something was current guidance (a quick read shows the document it found was from 2016, it was served the last edit date in it's API call, along with newer documents that contradict it).
Assuming what a Jira ticket said without ever reading it with it's tools and then doubling down on the contents it has assumed.
On learning specifically, it constantly gets grammar in foreign languages wrong it can write fluently when prompted correctly but when asked the sort of wrongheaded questions from flawed premises learners commonly make it is prone to making stuff up. I experienced this yesterday when asking about how danish comparisons work.
Not the GP, and this is just the free ChatGPT, not a frontier model, but just a few days ago it happily confabulated an entirely incorrect version of the plot of Iain M. Banks’s "Matter" when I asked it to analyze the novel in a certain context. Claude fared better, though it also made some mistakes. I don’t expect the models to know or recall the specifics of the plot of every novel out there, but it would be nice if they didn’t make things up.
Yeah thats the silver lining in the whole mess: For those of us who enjoy software, hardware and building things, this will be a new golden age and we can filter out all humans and elves.
I am sure many smokers in the 1950s also saw the health benefits of tobacco, that they were very happy to experience the increased energy after a smoke and could get more done as a result. I‘m pretty sure none of them felt their lungs and throats deteriorating either.
Likewise, you may not feel like AI is de-skilling your brain. But it probably is. We don‘t have the research (yet) that AI is addictive and causes brain atrophy, but all the evidence is certainly pointing that way, the same way the evidence were pointing that way about tobacco in the 1950s. My only hope is that it doesn’t take us another 2 decades to prove the obvious.
Oh, I definitely feel a strong pull toward the low-effort path of just letting the AI do everything. It's so much better than I am at writing code, after all! This code it wrote for me is beautiful! But it makes terrible mistakes constantly, and when I'm reduced to pleading with it to check whether it's made mistakes, basically there is no hope. And, of course, it would put me in the Homer Simpson position of declining to get up and walk just because there's a motorized wheelchair at hand.
>Likewise, you may not feel like AI is de-skilling your brain. But it probably is.
It is, but why is that a problem? Moving from physical labor on the farm, factory or construction site to sedentary work and lifestyles would also atrophy our muscles so now we pursue physical activities we actually enjoy like gym and sports instead of hanging on to those dangerous and strenuous physical labor jobs just to stay in shape.
Similarly, you will use the AI to churn through the repetitive mundane tasks the AI can do, and then work your brain on the activities you actually enjoy.
Now if you choose to not exercise your brain and dumb yourself down the same way sedentary people don't exercise their bodies and get obese, then I guess that's on you, but we can't force the world to technologically regress just because some people are lazy and don't exercise, the same way we haven't forced construction workers to use pickaxes instead of machinery to tear up a road just to make sure they stay in shape and don't get too fat from sitting in their air conditioned excavators.
De-skilling is too broad though. Or maybe not broad enough. I've been using GPS sat nav since it came out, in the Tomtom days. I don't know how to get around to places without a gps to spoon-feed me instructions. My ability to multiply two digit numbers in my head has totally atrophied since my younger years. I also don't know how to ride a horse or grow corn though. Or how to milk a cow or goat. Yet somehow I'm still (for now) able to put food on the table. I can tell you subtle differences between the output of Fable vs Opus, or Sol and Astra. I'm real good at Linux, and it made my career, but honestly Claude is better at it than I am, and it's relentless. I get tired and distracted easily. When people lose one of their senses, the other ones sharpen. Maybe. I have a couple of practices I do to sharpen my mind on memory and recall and cognition. You're right on the brain atrophy, but like the gym replaced manual labor, we should do the same for our minds.
Well, for example, in one afternoon, I have a parsing engine to understand, which is 9 pages of code. I thought I knew OCaml, having written a few interpreters in it, but I didn't know the {foo| |foo} multiline string syntax, I didn't know about Printf.ksprintf, I didn't know about Buffer.create, I didn't know about String.escaped, I must have once known about List.exists and List.rev_append and forgotten, I'd never thought of pattern-matching Array.to_list Sys.argv as a way to parse a command line, I didn't know about Sys.file_exists, and now I also have to think about what the parse result should look like and how to use it. And Claude correctly pointed out that the way I had thought about handling things like heredocs (or {foo| |foo} strings) would violate the preconditions for using the Packrat parsing algorithm, and suggested that I use the alternative approach of parameterized productions as in OMeta, which I need to think over.
I think that was the same day I prototyped an approach to using Service Workers from localhost as a platform for persistent mobile apps that don't show up in the app list but also don't rely on the TLS CA system for their security. Which involved learning a lot of stuff about the Service Worker lifecycle and localStorage and IndexedDB that I didn't know before.
I love how well this comment captures the experience of engaging with LLMs as a way to deliberately challenge and expand knowledge.
When I see people worry about LLMs atrophying their mental abilities I assume they haven't thought very hard about ways to lean into using them to expand their mental capabilities.
I have been prototyping some network proxies in a largely "vibe coded" fashion and it has been a mixed experience.
It has definitely accelerated my learning: through the process of writing rigorous plans, I have learned so much about network programming... the intricacies of HTTP2, how to design a fast MITM proxy, performance pitfalls in SSL...
These are things I studiously avoided learning for a decade, now demystified, mostly through Claude patiently rendering many figures and diagrams.
And with Fable, I was able to ship a working Envoy Rust extension in a one-shot.
On the other hand, my grasp on the details is tenuous. Every so often the agent can't progress and I am stuck for ideas, hitting different prompts like they were slot machines. I forget how to solve problems by myself.
I can feel myself becoming supine and dependent on something I know is going to become more expensive, a dependency AI vendors will seek to exploit. It has happened quickly. I do not really consent; it is forced on me by my employer.
One thing I may try this week is typing in all the code myself. With the level of back and forth that I've been happy with so far, Claude Pro seems to only be able to produce about 1000 lines of code a day in two or three five-hour sessions. I can totally type 1000 lines of code in a couple of hours if no problem-solving is needed. So maybe I'll look at Claude's code, switch screens to my editor, and type until I don't know what to type, and repeat.
Obviously there are higher-level design issues that I might not notice while engaging with the code at the byte-by-byte level, but I won't have the embarrassing problem I had a couple of weeks ago where duck.ai wrote me a CPU in Verilog, and after I tested it, I tried to write something in Verilog myself and couldn't even figure out how to write a syntactically correct XOR-gate module. (Verilator's parse errors are not designed as a Verilog tutorial, it turns out.)
I assume that they don’t have time to do that, and are lamenting the fact that exercising those capabilities is no longer on the critical path to getting paid work done.
I'm guessing you've written a well-thought-out, clearly expressed blog post about this that I would absolutely love to read, if only I knew where it was.
> I pointed Claude Opus 5 at a C codebase I've been working on for years and it immediately found five serious bugs
These 'serious' bugs aren't important if you've been working on this code base for years and only now they pop up. I suspect - although I'm guessing - that probably a hobby project.
Frankly speaking, although this comment is very dismissive about the opinion blog article - assertively stating that this isn't a well-thought-out post - it seems to me that the personal anekdote is irrelevant and that the blog post in question still fully stands.
It's definitely been a hobby project so far, but suddenly its quality has improved a great deal, which I think greatly improves its chances of graduating to being a daily driver.
You’d have to live there, in the presence of a data centre for AI which actually wastes water. The numbers people throw around on social media are absurd. I’m pretty sure they do not take into account the circular reuse of water for cooling, and just look at flow rates passing over chips.
While we're talking about Americans using anything but the metric system (https://news.ycombinator.com/item?id=49746745), how many golf courses' worth of water is Google's 10.9 billion "gallons" a year?
> As a historical U.S. benchmark, an average 18-hole facility had about 80.7 irrigated turf acres and used approximately 152.5 acre-feet/year—about 49.7 million gallons (188 million litres) annually.
So about 220.
But it's still, ahem, a drop in the bucket compared to the California almond industry.
A while back I satirically suggested https://simonwillison.net/2026/Jul/17/spot-birds-not-golf/ that if hyperscalers wanted to relieve the pressure over data center water use they could buy up a few dozen country clubs and turn them into parks.
I feel this post. I am tired of "directing" agents when in reality it feels more like trying to herd a group of toddlers.
Sure they can mostly write better code than a toddler but this constant nudging and reminding and reiterating and stopping them from using the token budget of the whole company for a one off script. It gets tiring and I feel like I am losing brain power while doing it. Maybe it's faster but explosive diarrhea is also a faster way to produce shit.
> Maybe it's faster but explosive diarrhea is also a faster way to produce shit.
i'm in the midst of a very large global roll out of a new system including about 24 separate erp integrations. My team's system is dependent on another system coming online first then we go then the integrations come online then a massive data migration happens and ends with all the associated testing. So like a huge number of dependencies and I'm second in line. Today we get word that the first system is having issues with a vendor and will not come online as scheduled (our dry run deployment is tomorrow and spans all next week as each dependency gets their turn. Week after next is PROD.
We're not heavily integrated into that first system but we are in spots and so there's a reason why they go first. Writing around that system is feasible but we're looking around 5k lines which isn't a lot but there's still testing and sign off. My offshore team is in bed, meanwhile they, and onshore, all have other shit to do anyway so pulling them just puts everything else behind.
I tasked an agents to make the changes as soon as i woke up to the news, they got it mostly right. It took two rounds of fixes with some offshore testers who stayed up late but the PR got in and merged. We just did (literally like 5min ago) a validation run against our target system and we're green for tomorrow. I told the testers to goto bed and then i pulled up HN and opened a coke.
There's no way in hell that would have happened without the coding agents we had on tap. So, yeah, i find a lot of value in the rate at which AI can work on code even if it's not perfect every time.
True, it would not have happened back in the day. But oftentimes what would happen is that sane, sensible leadership would have a talk about delays on the critical path and adjust the schedule accordingly.
Maybe not as satisfying to people who enjoy being heroes. But it would not have been an automatic disaster.
I don't want to deny that. I mean I am using it. And if works well it's great. If it doesn't though it's exhausting. And if it produces bad code, it can do that at a speed that is overwhelming.
AI builds like 95% for me than i play around with it for a bit for the last 5%.
I'm still a lot faster for certain things with AI but its weird. Instead of just being annoyed about some weird bug, i'm annoyed about an LLM which can do everything and then falls over itself on weird issues.
It feels weird true but it still also relevant faster?
I never liked telling people what to do or watching people do something. Using AI is exclusively like telling someone to do something who is either super smart or dumb as a brick and you never know which persona you will. The only thing you can be sure of is that it will produce whatever it produces very fast with 100% confidence. Also I care for code style, consistency and overall maintainability because I don't want to be locked into using LLMs and I can only really do that when I proof read everything. I don't want a huge project that will take a full rewrite for a human to understand it.
I think the main problem is a conflict of objectives. AI companies need you to use more tokens so they are not going to improve that. They are optimizing the models to get as close as possible to the point in which people would stop using them because they are useless but without crossing that line.
Proof of this is the amount of unnecessary tasks that Claude does just as an excuse for not doing a good job doing the tasks that we ask it to do
Conflict of objectives is fine, it's not like we have a single provider of models vying for us to spend our money on. Something like collusion and price fixing across the industry would be a bit different.
I review all the agentic code and commit it myself. I also write some features manually, especially when I want to really make sure that I don't screw up. E.g. for authentication or for observability.
I also found that slowing down your development (just by a bit!) on purpose helps. Do not rush into implementing your new idea and give yourself at least a couple of days to think it through.
I feel like humans don't switch between being an idiot and a genius quite as fast as LLMs do. But yeah I have been thinking about my future and I am not sure I am cut out for the role of manager.
I’ve had a pet theory for a long time that society loses it’s collective mind every 10ish years or so, usually starting with a good reason, but the outcome is mass stupidity followed by mass forgetting leading to a new cycle. War on terror, GFC, crypto, covid, now AI. Although the cycle does seem to be shortening.
Also we’re just so damn stupid to learn from history, or even just people 10 years older than us, that we repeat the cycle.
And there I guess is where saying a new sucker is born every minute is from.
I have a more sympathetic view, I thought covid could have been much worse. Of course there were silly moments like the existential panic from a toilerpaper shortage but it seems like the vast majority of people acted responsibly and kept their heads over the long haul. In the meantime, we developed revolutionary vaccines that solved the problem.
There's the lingering societal PTSD to consider, but I think most of the challenge in the aftermath are latent issues that preexisted covid and it just brought them to the surface. I think our world a couple decades from now will be stronger than it would have been in a universe where covid never happened, and actually has a better chance at dealing with the next covid-level threat. Perhaps that is this, in a way.
Covid proved that a healthy looking society is not always so healthy, and I think it works in reverse too. The outcome of the upcoming election will tell us something about how far we have to go.
This might be Australia specific, but I think a lot of the movement restrictions were unnecessary. And long term damaging to not just adults but there’s a whole cohort of kids/teenagers who just missed out on certain things and we’re patting ourselves on the back we survived?
The places that needed restrictions such as hospitals & nursing homes still got covid by & large. We didn’t necessarily need to close down the whole show.
I’ve had my jabs, also had covid multiple times. I’m not a disbeliever, I just think the collective reaction was completely OTT.
That’s the thing about large scale public health interventions like that, if it works it will look like you overreacted and you still won’t know if it’s because it worked or if it was never as bad as was feared.
After being burned by the first wave, Australia locked down hard and early for subsequent waves. It was the correct thing to do.
As a result, they had relatively short periods of lockdown compared to other countries, such as the UK, which had comprehensive vaccination but dithered about going into lockdown.
Kids mostly forgot and adapted back. It is adult, mostly men, who just cant get over fear of vaccines, injury of having to do something a little uncomfortable for someone else.
I live in a relatively wealthy town and most people here had a pretty safe series of lockdowns (bit hair-raising for me as a freelancer but ehh). We are collectively massively pro-vaccine; I know only two people who loudly resisted (and one of them nearly died in hospital from COVID).
But I can tell you that our collective sense of (unusually strong) community has taken six years since the first lockdown (four and a half years since the end of mask restrictions) to truly return to what it was before.
So even in this quite cushioned place I think we didn't really return to a sense of proper ordinary community positivity for quite a long time (it helps that we had a pretty great summer). Last summer things still felt very disjointed.
Kids, young adults, I can assure you, resent what happened and how poorly we managed it.
In other towns where community was weak, a lot of damage has been done, and you can see that in how little collective spirit there is in dealing with new challenges. Even around where I live, things like reduced footfall and contribution shortages in community services have been used as a pretext to cut them entirely. We have done damage to young people by simply deleting community things we benefited from that they no longer will.
Of course kids and young adults resent it: a part of their childhood and formative years sucked ass.
But the resentment isn’t towards the handling, it’s towards the reality. It sucks covid happened and it shouldn’t have. But there’s nothing that could have been done to save their youth; it was already ruined for those years.
I mean, if the lockdown didn’t happen and instead a few million more people died, would they have preferred that? I doubt it, especially considering such a situation would inevitably result in even stricter restrictions going forward. After all, lockdown was a reaction. If you make the thing it’s reacting to even bigger, even more of a problem, then… well… the reaction will be more extreme.
Oooooh yes it is. They are so mad at how badly we handled it. And they are right to be.
> I mean, if the lockdown didn’t happen
That isn't their complaint. Their complaint is not the first one (except that in our case in the UK it was idiotically weeks late and major sporting events happened; the older ones understand how stupid that was). It's the fact that we subsequently undermined it, and then did it again. And again. And again.
Trivialising this to fear of vaccines misses the point. The lack of human communication being the new normal, cut friendships and shattered communities are the real killer here. Especially for ones that didn’t have a lot of social life or family to begin with.
The lack of human connection has been a trend for many decades now, covid just accelerated it all at once. Not like there was much choice, lots of people died, we did what we had to.
The communities that did exist were always running on fumes, basically only existing due to inertia. When the inertia was cut, even if only for a couple weeks in some places, they were done. That’s it.
The social damage has been here, and we’ve been zombie-ing our way through it. Covid just let the undead stay dead, and turns out we can’t revive it.
And the massive damage this did to children's education. I think people who didn't have a child in the school system at the time might not understand how poorly the schools functioned during that time.
My child had two intelligent and supportive parents, including a stay-at-home mother, and it was still rough. Many of her classmates just flat-out lost a year of education. There's still obvious effects on her cohort years later.
Almost every single meetup group in Northern Virginia was completely destroyed and did not grow back. I watched as dozens of local meetups, several running for many years, disappeared over night. I managed one as well and my crew held on to ours for as long as we could. We managed to keep it running online for several more years. But the social damage was done. After running the thing for 12 years, not being able to find anywhere that was willing to host us in-person again, and all of us original organizers having moved to different cities, there was nobody willing to take over.
I appreciate your optimistic view of it. What I got out of it was that Covid was a sort of dress rehearsal for a far worse outbreak that could eventually happen, and we (Americans) failed miserably.
I agree with you but I think it happens every 4 years, not every 10.
I first started noticing this in the 90’s .. comp-sci grads were entering the industry with no clue whatsoever how to do software. (Of course its gotten worse since then, but I started noticing it in the 90’s..)
Everything old was thrown away as being archaic and obsolete - only the New Cool Shit™ mattered .. except nobody had ever done anything, properly, with the New Cool Shit™ - everything was still running on the old.
(Unix was dying, everyone was learning only Microsoft tech because “that was the future” ... until it wasn’t. Now, a majority of us are running 21st century Unix workstations given us .. by Apple, of all companies, which didn’t die so easily, after all..)
People entered the market not because they were truly interested in improving the world through computerization, but because they wanted the lifestyle afforded to them by a career in “Information Technology”, a nascent term back then which simply meant “career path for the budding materialists”. Trouble is, you can’t be materialistic with computers, they are almost entirely a spiritual device, which value is determined strictly and only on the decision of value made by humans. It is humans which decide the true value of all that physical hardware after all.
I think this cyclical amnesia is driven by materialist consumerism. People who take a less material approach to technology, tend to build stuff that lasts a long time.
The reason I think it happens in cycles of 4 years, is that is the average time it takes someone to enter the academic churn, and get spit out on the other end, ready to join the work force and do big things.
Journalists fear mongering and making sure the hoi polloi know their place as powerless pawns in a game they couldn't possibly understand is a constant.
They know what they're doing, the people who fund them know it and the people with half a working brain cell sooner or later hear someone like me and go 'oh, that explains it'.
It's much simpler than some mythical cycles - manufactured 'mass stupidity' is a conscious, deliberate, ongoing choice.
It used to be religious organizations, then it was newspapers, now its social media platforms. The playbook has been the same for thousands of years - nothing has changed.
To save everyone some time - the playbook is you're cattle, I'm shepherd. I'm master, you're slave. It's not anymore complicated.
The bit 'educated' people miss is that most people would love nothing more than to be the master (freedom they call it? American doublespeak). They dislike being slaves, not the concept of slavery.
Your comment is utterly ridiculous since all the examples you shared are examples of the evolution of society to address a corresponding problem, and none of them are about it having lost its mind. Every concept you noted is alive and well. Dinosaur minds will always struggle to adapt to a changing society.
> human resources are still a zero-sum game, and every individual feeling super busy in their agentic silo doing a thousand things at once does not, in the end, help solve the kinds of projects that require cross-functional collaboration and team work.
It's interesting how there's an increasing split of software engineers into those who're very happy with AI and leaning more into it, and those who're increasingly skeptical or dejected.
I don't know how this will play out, but I haven't seen anything like this before.
I have leaned heavily into it… and became good at “agentic thinking”, but now I’m going to reverse. I have become dumber, sloppier, lazier, more distracted. I’m less happy than before. It’s hard to escape the productivity addiction and expectations though.
I've seen this happen to multiple co-workers, in the span of months. Two were laid off so I don't know how it's going with them, and another has backed off but not fully abandoned AI code. I'm resisting it entirely because of these problems.
I find AI autocomplete and chat (asking specific questions, getting general code I can adapt, etc.) to be useful. I'm not sold on agents and agentic workflow.
When I tried using agents for something as a test it immediately started doing things instead of being part of a conversation. I want to be actively involved in the process, not sit back and let AI agents write/generate stuff that I'd have to/end up rewriting/modifying anyway when it goes against the design I have in mind.
The other thing I don't like about agents is their ability to run any command [1]. That seems like a nightmare w.r.t. the potential for leaking secrets (signing/access keys, etc.) or doing damage (deleting files, database tables, etc.).
[1] You can set the option to review every command it runs, but you're then just hand-holding the agent.
For my social circle, the distinction falls almost perfectly along the line of people who see software engineering as a craft / passion, versus those who see it as something that needs to be done to get paid.
The first group is generally disillusioned, for two reasons. First, it's an attack on their hobby. Second, they sort of can't let go: they want to own the product, they want to understand if the code is good or bad, and they spend a lot of time cleaning up after LLMs. Which, frankly, is not fun. You're no longer doing anything clever, you're just a janitor.
The second group is over the moon about it because they feel it gives them the elite powers previously only reserved for greybeards.
I don't think this is unique to coding. It's the same thing with writing. If you like writing, you probably hate LLMs. If you see writing as a boring chore that needs to be done, you are delighted to have a button you can press. Haha, take that all the influential bloggers, tech writers, etc. I can now do your job at 10x the speed.
I think it's a useful tool, but peak workflow is basically the rough existing development paradigm, if that can be defined, but let AI do the grunt work (typing, some researching) and help you understand things in your own brain, from which you make well thought out decisions and are able to validate output, later define feature requirements, debug, etc....a maintained understanding of a complex system.
The approach currently being foisted upon me is to offload almost everything to LLMs (have it write a complex tech spec -> one shot into tickets -> one shot implementation of said tickets), with humans reviewing throughout, and repeating this iteration until it 'looks good'...throwing sh*t at the wall until something sticks, basically. However, we're being expected to review at a far faster pace than one reasonably can while maintaining an understanding of the system.
Meaning, with this paradigm, humans will largely be rubber stampers and will atrophy their abilities as a result, which will seemingly result in compounding adverse effects.
TLDR in my experience the AI can help with some 'busy work' eg translating a well defined solution in my head into code. The time it takes to understand an implementation and ensure correctness will not change. LLMs cannot reliably do this. This traditionally has occurred during implementation by the implementer, and during code review by code reviewers. I don't think simply shifting the implementer's comprehension 'duties' to code reviewers provides any benefit.
To me, doesn't feel much different than when infra-as-code became popular in the 2010s
It was a huge shift in the world of system administration, gave birth to devops, and, along with the rise of containers & cloud computing, it radically altered how companies ran their infrastructure
Some people leaned into it, others didn't and a huge rift opened up between them
I used to say "automate all the things" - I still do, but I used to too
AI tools are just an acceleration of that mindset and in my world of cloud/devops/sre I'm heavily leaning into AI-driven development and daily workflow
I'm very happy with the performance and ability of AI. I think the best software ever will come out of this. It's very clear to me that AI empowers one to make "just ok" software effortlessly, and "incredibly excellent" software with the same level of effort we previously used to make "just ok" software. So there will be a lot of slop, but there will also be some real diamonds created by those who put the extra work in. The extra work might not involve manually writing or even reading much code, but it is work nonetheless.
I still count myself as "dejected" overall. I'm dejected by the economic shape of AI which seems destined to keep concentrating outsized rewards to the top few who own it or have enough capital to shackle it to their will. I'm fearful that intelligence, once it becomes a commodity you can rent any time you may need it, will be socially devalued in our already anti-intellectual society. I worry that in a couple decades we may resemble the world of "The Machine Stops" (1909), where nobody really knows how things work.
Of course we already live in such a complex world, no one person has complete knowledge of the "stack" they rely on. I can write software in C or assembler but I can't design a CPU and don't really understand how one is manufactured. (I may someday study that field, but I haven't yet!) But I take solace in the fact that somebody out there, has put the time in to study each of those things and is an expert in them. At every layer and in every niche of our engineering world there are masters of their craft, and there are students learning the fundamentals to keep that knowledge alive and growing. What if in 30 or 40 years that is not the case, and there are whole corners of knowledge the modern world depends on where everybody is reduced to "I dunno how it works, but Claude said..."?
I saw this post in my RSS feeds early this morning. The post was so poorly thought out, pessimistic, and full of anti-AI myths that I unsubscribed from this blog's RSS feed. I'm surprised to see it make the front page of Hacker News.
I am using safari on an older ipad and initially thought this website was an art project. The screen was black with an unlabeled toggle button. Tapping the toggle made everything visible. A dark mode bug, I guess. The intrigue was mild yet odd.
> Spending upwards of 75% of my time directly or indirectly dealing with AI every day has absolutely robbed me of most of my enjoyment of my work. Most days feel like that Twilight Zone where you wake up and you're the same, but everyone else is different.
I think there were always two camps when it came to writing code, a strong bimodal distribution. People that care about the perceived code quality (aka the ‘craft’) and people who treat the code as a means to an end. At least I always felt this tension. And there is always an exception, and a person can shift between two camps during the same day. But would generally lean towards one. I know I do. And one is not better than the other, they could both be very smart and well meaning. And you need both for success in a for-profit business. It’s been discussed ad nauseam but one particular metaphor I like is Jesus Christ vs James Bond. James Bond would win most of the time. Most people tend to think like James Bond, and if they don’t, the organization strongly nudges them in this direction, promotions get decided and it becomes self reinforcing.
Now a new powerful tool shows up and I think it is time for the Jesus Christ camp to throw in the towel.
> half of the people you interact with have turned into meat proxies
Samuel Butler presaged this in Erewhon (1872) : "May not man himself become a sort of parasite upon the machines? An affectionate machine-tickling aphid?"
Completely off topic, but I'm absolutely fascinated by the fact that this blog's central column is built as a... <table>
Good old times. Definitely not vibe coded, though.
If you think vulnerability research simply doesn't matter, you have a lot of company in that opinion. It's something Bruce Schneier used to argue, and Marcus Ranum, and a bunch of other people that used be on closed secret vulnerability-sharing mailing lists before Bugtraq blew those cliques up. These are very old arguments.
But if you do think vulnerability research matters, and you're trying to argue that frontier models aren't a seismic change for that discipline, you have almost no company. Vulnerability researchers are overwhelmingly leaning on automation to find vulnerabilities and, just as importantly, generate the tooling required to test hypotheses.
You can feel about that however you want to feel about it. I mostly don't care, except: you can watch people like this being negatively polarized back into the bad old days of the mid-1990s, content-free CERT advisories, and vendor-controlled "responsible disclosure" by a use case that frontier models unimpeachably excel at.
It’s amazing how half the developers on earth live on a completely different planet now. There are plenty of new challenges, sure but we are far past the point where we can have a debate about “is it useful?”
And yet we continue to do so. I understand the feeling of loss some people may be facing. And there are definitely some really bad practices - like nakedly spewing claudspeak at your colleagues instead of communicating. Or raising a PR you don’t understand. There are asymmetries we haven’t learned to navigate. But we aren’t returning to a world where it doesn’t dominate our discipline so it’s best to find opportunities.
The question most of us are asking isn’t “is it useful”, but “is it worth it”. Engaging with these tools involves no small amount of self-debasement and long term degradation of skills; do I want to sacrifice myself on the altar of productivity?
For me the answer is still absolutely resolutely “no”.
Because AI removes you from analytical thinking, and the brain is a muscle. The less you think, the less you are able to think.
Programming is inherently analytical and logic-driven. It’s a great brain exercise, even if the code has no value. When you use AI, you lose that exercise. What replaces it isn’t the same.
I mean, consider. I can solve a crossword, or I can ask AI to solve the crossword. AI will do it perfectly, and faster too. But which one is better for my brain? What was my goal with solving the crossword, anyway? On the surface it was to find a solution to the crossword. But, maybe, deeper down, the goal was to improve myself in some way.
People conflate the improvement of products with the improvement of self. Maybe it’s a result of our consumerist mindset. But the truth is the product can improve greatly, and you can be making it, while you yourself degrade.
We write better and better code, at a faster rate, but are we better programmers than before? Maybe, maybe not. I’m leaning maybe not.
It’s not new or unique. The assembly line is the same. Sure, I can build better furniture faster at the factory than by hand. But what is the goal here? Is it to make the best furniture, or to become the best carpenter?
If it’s to make the best furniture, the best product, then I’ve won. If it’s to become the best carpenter, then I’ve lost heavily.
The bigger challenge is that the mechanics of the day to day work have entirely changed. Mechanically, using C is similar to using JS. You’re tying and compiling and checking results, whatever. With an Agent what you actually do is completely different. Even as technologies have changed in the past and people have learned more, your mechanical day to day work would look similar, just with different tools. Not so with AI.
So it should be utterly unsurprising that many people are going through a bit of an existential crisis around this. Because what you actually sat down and enjoyed doing, what motivated you, may be entirely gone now.
And on top of that, there’s an extreme amount of pressure to do more in less time, which is by definition stressful. And do much more context switching.
> And yet, despite having found literally thousands of new vulnerabilities (only a fraction of which were reported to Open Source projects, by the way), I don't think that we're any safer than before.
I’m not sure I follow. There are dozens of zero day, full RCE/privilege escalation linux vulnerabilities that have been found and fixed due to the use of LLMs. Some of which existed for decades. Unclear how that doesn’t make us safer than before.
I agree that everyone's lost their minds, but so has this guy.
LLMs are actually producing a lot of pretty good stuff, can debug things that would have taken an entire team a week, and the people running AI companies are also generally like the most boring supervillains imaginable. All true.
It is also completely screwing up the global economy, and most people barely understand what it is and what's happening.
It's also not going to collapse anytime soon as a technology despite what the economy does, and it's going to get a lot worse before it gets better. Everyone who's extreme on it on either end is generally wrong.
Probably the concentration of a too-big-to-fail percentage of capital into a single digit number of tech companies, many of whom are engaging in circular financing deals between one another while also ransacking the entire consumer electronics space.
something like 25% of the current American GDP growth is because we're shoveling money into AI companies that have no idea how they're going to pay it back beyond selling subscriptions to chat bots, much of the world will take a hit on that crash
I've been coding for 22 years, 14 years professionally, so I appreciate AI coding.
It was annoying before when I had a very clear idea of what I wanted and yet it still took a whole week to implement.
Now, with AI coding, I can implement any decent sized feature, exactly how I want, in a few hours and it's all polished and ready, all edge cases handled.
Everything it's generating looks almost exactly like what I would have written, just written faster.
Personally, I feel avenged by AI because I had been saying for years that you don't really need static typing once you reach a certain level, getting types right isn't the most difficult problem and isn't a significant source of bugs. Everyone was gaslighting me about this... Yet now everyone can verify themselves because AI has reached this level I was speaking of.
Now anyone who coded with a frontier model on both TypeScript and JavaScript can see that it makes no difference at all. I can't remember ever seeing Claude mistake the type of a variable with either language... And TBH, I find Vanilla JavaScript from AI to be more succinct, not over-engineered like Typescript. Which is a point I'd been trying to make for years about incentives and actual patterns of usage (as opposed to theoretical benefits).
> So no, I'm not going to set ethics aside and then actively offer myself up as tribute to self-amputate my brain. I'm sorry if everybody else can't get rid of the brain slugs, but at this point I'm just looking to get off this ride.
Same. I quit, aside from two contracts I'll serve until they run out, I'll be studying Electrical Engineering. Even if AI takes over that space... good luck constructing a robot with the dexterity required to pull cables.
To anyone in IT... go and study for some qualification in tasks not easily doable for a machine. The trades are going to be a goldmine especially with all the boomers retiring. Or buy some ranch in the midst of nowhere and farm artisanal chickens, cattle or goats.
(For legal reasons, the latter was a joke. Farming is extremely risky, requires a lot of upfront cash, a lot of what used to be generational knowledge, but it seems to attract a lot of IT people, especially for whatever reason the goat farming)
> Google’s water use in The Dalles has nearly tripled in the past five years, and the company’s data centers now consume more than a quarter of all the water used in the city.
> That’s according to records released this week after the city settled a lawsuit against The Oregonian/OregonLive and agreed to hand over data on Google’s water consumption. The company’s water use is poised to continue soaring in the years ahead, as Google has plans for two more data centers along the Columbia River.
> Google is contemplating two new server farms on the site of a former aluminum smelter in The Dalles, where it already has an enormous campus of data centers on its property along the Columbia River.
> Google says it needs more water to cool its data centers, but neither the company nor the city will say how much more – only that The Dalles can’t meet Google’s needs without expanding its water system. The deal calls for Google to pay for the upgrade.
> Even so, the proposed water pact has attracted scrutiny and skepticism in The Dalles, a riverfront city of about 15,000 approximately 80 miles east of Portland.
> Residents and nearby farmers are concerned about the city’s long-term water supply amid an ongoing drought. They complain they don’t know enough about Google’s actual water use.
----
It is possible to do some cooling with closed cycle, though more than a few data centers have been built with open cycle cooling in places were the water table is precarious or in parts of the country under drought conditions.
Unless a data center construction discloses its water use and shows that it isn't using a lot, then people are assuming its using as much as it can (and up to the water rights or capacity that it has). ... Which isn't an unreasonable assumption to make.
> Google’s data centers gulped down nearly 550 million gallons of water in The Dalles in 2025. That’s nearly 40% of all the water consumed in the entire city and a huge jump from the year before.
> The city expects that local water consumption will soar over the next several years and bills will nearly double as The Dalles works to upgrade its aging water system. But the city won’t say how much of the rising demand comes from Google, citing a promise to keep the numbers secret and confidentiality provisions in Oregon public records law.
And data centers are being very cagy with their water consumption because the amount of water that it uses is related to the amount of compute it has and that is being held as an industry secret.
Also in the pic your provided the center literally sits on a river? Who cares? That means they likely are using their own water system meaning the people in the city are completely isolated.
> Therefore, the Legislative Assembly declares that the waters of the state may not be appropriated, stored or diverted for use outside the basin of origin except in compliance with the provisions of ORS 537.801 (Definitions) to 537.860 (Vested rights protected), including, if applicable, the prior approval of the Legislative Assembly under ORS 537.810 (Diversion or appropriation of waters from basin of origin without legislative consent prohibited).
Evaporative cooling of a data center would constitute a diversion of the water outside of the Columbia River Basin.
Furthermore, the river water rights aren't owned by the city (or the aluminum plant that Google bought). There are other treaties and regulations on the Columbia River to ensure that it has adequate supply for power and for fish.
Google is using ground water rights and pulling. Furthermore, even though there's a river there, the area is in drought conditions. The supply of water percolating from the river into the groundwater isn't sufficient for human needs in that area.
> About 70-80% of the water consumed annually by residents and businesses in The Dalles comes from Crow Creek Reservoir. Fed by South Fork Mill Creek, Crow Creek and a pipeline that diverts flows from the Dog River, it held 123 million gallons on Sept. 4, roughly seven million gallons less than the same time last year.
> While the situation isn’t dire, as Public Works Director Dale McCabe emphasized, it’s not normal. The city issued similar voluntary restrictions last summer after two of its now five groundwater wells went offline; where that was spurred by mechanical failures, however, the current advisory is a product of environmental factors.
> “This is fairly new,” McCabe said. “I’m not remembering a period where we went into curtailment for quite some time before this.”
---
Note that "it held 123 million gallons on Sept. 4, roughly seven million gallons less than the same time last year" in context of Google's use of water in 2025: "Google’s data centers gulped down nearly 550 million gallons of water in The Dalles in 2025."
Those are different numbers (current reservoir amount and total use) ... but its something that people will compare.
Thanks for an educated reply. This is the first argument I have seen that isn't stupid.
So there's truth in the statement afterall. Clearly a powerful PR campaign going on because there is soooo many dumb takes this kind of argument vanishes.
I do think that amoung all our water uses this is easily the nicest amoung them. I think datacenters are the new factories and as far as factories go they are the cleanest ones ever made. But I suppose if you have the impression AI is useless then it makes sense. But if this is america's future industry we should make room. These centers are even funding infrastructure upgrades. To me they are the closest thing we'll get to reindustrialization in our lives and I would still want a stronger push for even more aggressive buildout.
Water use is one of the causes that can unite the various edges of political divides. Rural and urban. Conservative and liberal. Many parts of the country have been experiencing drought conditions. I had Oregon up there - here's the current conditions there.
I don't see it so much as a "PR campaign" against it, but rather it is a populist issue that has broad appeal being against technology companies that are seen as the bad guys.
The data center build outs are not doing themselves any favors by going cheap (evaporative cooling), noisy fans ( https://www.npr.org/2026/09/17/nx-s1-5954414/residents-file-... ) and then being secretive about the "how much is there" makes it look all the more nefarious and underhanded.
The claims of "its taking our water" or "its raising our electric bills" or "its taking our (kids) jobs" or "its stealing all our art" are all things that have some grain of truth to them and easy to rally behind one (or all) of those reasons. The choice of water as the topic is easily the most visible and the one that can get farmers and city folk to agree on.
Going to closed cycle cooling, funding the reuse of waste heat for winter district heating, and such could go to mitigate the public outrage about them... but those aren't the cheapest ways to build them.
Evaporative cooling. They think that because the earth is only 2/3rds water we will run out before it rains back down again.
I jest, of course. The actual argument is something about most water being frozen and how some people live in deserts so we should all live as if we were desert dwellers. As you can tell I'm not very convinced by it.
Water is literally the least scarce thing on earth.
There was construction of some data center, and someone's well water started looking dirty around the same time. From there it metasisized into claims that it's destroying all the world's water.
Rather than a myth, it’s more of a meme in the sense of “naturally selected, self-replicating idea”.
Hits all the right buttons for the motivated reasoner: An eco-disaster that our brains aren’t climate-change numb to. A threat to the most precious fundamental substance in the service of a high-tech fad. An evocative symbol of corporate recklessness in the service of greed.
That it’s not really a big deal compared to, say, almond cultivation is no match for that brain-niche fit.
I don't know if it is the minority but I think sanity is the group of people not taking a "side" and just realizing this new tech is what it is and it's going to and has had both major advantages and disadvantages. Blog posts like the above are a dime a dozen along with their opposite and thy only read like people caught up in bubbles.
Yep, good observation. And it's so exhausting not to take a side. Because people on both sides invariably misinterpret you as being on the other side and strawman you accordingly.
Personally, I agree with the author on some things. The copyright laundering, the PR theatrics in search of regulatory capture, the concentration of power in a handful of gargantuan corporations in a country currently headed for totalitarianism at an alarming pace. The proliferation of slop drowning out all the good stuff. These are genuine issues, and they worry me, a great deal.
And yet, it's become impossible to seriously contend that this technology isn't tremendously useful for certain tasks. I've used it myself with good results. But I don't buy the maximally bullish view that an LLM will eventually surpass humans in all areas. There are severe flaws with the technology that are inherent to its architecture and simply cannot be scaled away. This is as incontrovertible to me as its usefulness. The trough of disillusionment is coming for all of us, it always does. And much like the internet past the trough, we'll have a lot of cool new shit as a result of this technology, and we'll have a lot of horrifying new problems as well. This is the case for any paradigm shifting technology.
That's my view when trying my best to be objective.
Subjectively though, I'm deeply depressed about it all. LLMs have taken everything I love about computing and turned it on its head. I got into computers because they were so different from people. Mathematical, rigorous, efficient, unambigious(yes, bugs can be very confusing but there's always a satisfying and logical answer to dig out with enough effort). Now, apparently, to do the job I (used to) love, I have to spend most my time spoonfeeding instructions to a pretentious, know-it-all asshole who repeatedly fails to follow simple instruction, and yet is somehow still better than me at my job. I hate it. I'm 10 times more productive, and 100% of the joy is gone. I've quit, and I'm now considering what the fuck to do with my life. Something with minimal computer involvement. I will continue to code as a hobby and tool for my own purposes, LLM free, but I won't even bother uploading my code anywhere, because what's the point.
We are all caught up in our bubble. That’s why being exposed to someone else’s is useful. The moment you dismiss it as their bubble you assert not just their wall but also yours.
Yeah, when you are pulling out terms of the very online like "meat proxies", you're not exactly in a place to judge the rest of society, you're in a bubble.
AI does not use much water. If you believe it does, like this article does, you have fallen for propaganda and lies, ironic in a post calling everyone using AI stupid.
The main cause of water fear mongering is that one woman’s well was dirty during construction of a data center. First construction is not the center running, and having lived on a well they get dirty for all kinds of reasons.
> Approximately 80% of the water (typically freshwater) withdrawn by data centers evaporates, with the remaining water discharged to municipal wastewater facilities.
Is that supposed be a lot? That article states that all US data centers combined consume 450 million gallons a day, equivalent to 90 towns, which does not sound like very much.
I'm not the one here making assertions, I'm asking questions of the person making claims. I'll leave it to others to judge what is 'a lot' or 'reasonable'.
I don't think 'anyone who thinks X is Y' is a good basis for discussion, which is the real point.
You still have to grapple with the merits of their argument to find out if the indicator is correct or not.
In a world where everybody seems to be quoting grok with no further thought process you would think people would be more welcoming of someone who is "slightly wrong" on occasion. It's the strongest indicator that a flawed human being got their information not directly from a machine.
Maybe yours do, but all the CyrusOne date centers outside of Chicago smell like is grass and landscaping; they smell a great deal better than the car exhaust choked strip malls that dominate the exurban sprawl areas they tend to get sited in. I would much rather have one of those DCs as a neighbor than I would a Walmart.
As long as they can operate under capacity (for the grid) I don't disagree.
However I live in a much nicer area than Chicago and any Walmart, large mass of people, or DC would really destroy the PV as well as it would be an eyesore.
I don't really understand why so many just want to over industrialize so many beautiful places so that a corp. can sell the next gimmicky iteration of our "best model yet" which is just slightly slower and more expensive then the previous.
They're stinky? How? And how do they pollute water sources? A datacenter is a building filled with computers that uses water and air for cooling. What pollutants get "emitted" by a bunch of CPUs and video cards? No one seems to go into details.
There are certainly problems that can be crated by dumping heat into a body of water, but that's not the argument being made.
I'm willing to bet that a datacenter creates a fraction of the pollution of a similarly sized industrial facility such as a chemical plant, refinery, smelter, or steel mill.
It's mostly the emissions from diesel generators which many DCs use as it's far too expensive to ever shut them down. Often diesel generators are used to lighten the load on a power grid as well, so many DCs will run generators 24/7.
That source of power, since our grid is so outdated and struggles with the weight of these power-hogs, EVs as well as increased usage of AC during the summers create some dangerous conditions.
There is the risk of heavy metals getting into the water supply as the copper degrades but that will only be a problem down the line, that's prescient but not yet realized.
> I'm willing to bet that a datacenter creates a fraction of the pollution of a similarly sized industrial facility such as a chemical plant, refinery, smelter, or steel mill.
I agree; however I would not want a DC or a refinery, smelter or steel mill anywhere near my town. We have industrial districting for that reason, and because a lot of DC projects want to be put next to lakes and water sources, this causes issues for the residents.
In the case of one amazon data center, they were pulling in water that already had nitrates in it due to agricultural run off, but it wasn't enough nitrates to cause a problem for anyone until the data center came. It pulled in a massive amount of water, a lot of which was evaporated and that left behind water with very high concentrations of nitrates.
Normally, the nitrates would be filtered naturally and would mostly remain in the top layers of soil. Amazon pumped out 10s of millions of gallons of the vastly more contaminated water. It was so much water that it was forced much deeper into the ground. It was pushed deep enough to reach the aquifer which contaminated the water source for an entire community of 45,000 people.
Suddenly the water coming out of people's taps was polluted at 10x the federal level for safe drinking water. People got sick. Cancer rates spiked. Babies died. Amazon was forced to settle and pay out 20 million for water treatment and to dig new deeper wells for the community.
> I'm willing to bet that a data center creates a fraction of the pollution of a similarly sized industrial facility such as a chemical plant, refinery, smelter, or steel mill.
This is whataboutism. The existence of other bad things, or even worse things, doesn't make data centers good. They are a problem for the environment regardless of what else is a problem and the companies who build and operate data centers should be held 100% accountable for the harm they cause.
It's helpful to put this number in context, although if the people you're talking to will do anything to avoid using the metric system, that becomes much more difficult.
Fortunately, now we have computers, which are great at unit conversion, so we can cut right through these feeble attempts at obfuscation. In non-medieval units, 10.9 billion gallons per year is 41.3 million cubic meters per year or 1.3 cubic meters per second. The river a few kilometers from me has a discharge of 22000 cubic meters per second (of fresh water dumped into the sea), so Google is the equivalent using 0.006% of the Rio de la Plata. Lake Superior contains 12070 cubic kilometers of water, which is 1.207 × 10¹³ cubic meters, also of fresh water, so Google's current use would dry up Lake Superior in only 290,000 years.
Google is mostly not very close to Lake Superior or the Rio de la Plata; a more relevant river might be the Sacramento River, which drains into the San Francisco Bay where Google was born, and it's much smaller than the Rio de la Plata. Specifically, its average discharge is 797m³/s, so Google is using 0.16% of the discharge of the Sacramento River. (But some of that is at datacenters far from California.)
https://en.wikipedia.org/wiki/Water_in_California#Agricultur... tells us that agriculture in California uses 34.1 million "acre feet" of water per year (Americans will do anything to avoid using the metric system, especially when they're trying to be sneaky). In non-medieval units, that's 42.1 billion cubic meters, and per year, it's 1330 cubic meters per second, almost exactly 1000 times Google's use. Of that, 18% (240 cubic meters per second) is spent on alfalfa, or was in 02014, anyway.
One major difference is that you need fresh water, like the water of the Sacramento River, to irrigate crops, but you can cool data centers with salt water from the ocean. It's less convenient, because there are a variety of annoying things that happen with biofouling and corrosion, but that's what you'd do if hyperscalers scaled up by another factor of 100× so that their water usage became large enough to be environmentally significant.
But that doesn't happen until they have 100× the computing power they have today. So anybody who tells you AI datacenters are a major water user is lying.
Me, I pointed Claude Opus 5 at a C codebase I've been working on for years and it immediately found five serious bugs and told me how to fix them, as well as how to use Linux system calls I wasn't familiar with to solve some other problems. And I gave it a new language for PEGs I'd written up a couple of years ago, and it wrote me a working implementation in OCaml that afternoon, fixing several bugs in my example grammars along the way and resolving a conceptual problem I'd had a roadblock on. I asked Fable 5.1 to implement a minimal proof assistant, and it wrote a clone of J-Bob in Python, which I'm studying now. Although there is a certain firehose quality to this stuff, I sure don't intend to use AI to actively de-skill my brain.
That doesn't guarantee that AI will be a beneficial innovation overall, of course! As with most innovations, it probably depends on the balance between people being able to use the innovation to gain control over their own lives, and people being able to use it to gain control over others' lives. (Barring a FOOM scenario, of course, where our prediction ability is nonexistent.)
So, I don't think a pro-AI post can be well thought out, either. It's too early and chaotic to understand what's going to happen, and it may actually be uncertain. Pro and anti are both far too simplistic.
Basically, I don’t know how well thought out it is, but the prose argues that the point isn’t for it to be an objective take, and that if it were well thought out (ie highly iterated on and more objective or factual than subjective) some personal meaning that was intended to be expressed is lost along the way.
In other words It may have not appealed to you but that’s fine - you might just be outside the target demographic. In any case I don’t think it necessarily should be more well thought out. I prefer that these pieces exist or have their place. I definitely prefer their existence to a world where every personal Blog post has to arise from fiduciary or technical concerns, instead of from the soul. This is a soulful blog. I like it.
p.s. and at the same time, it's such a fantastic learning tool. It distills the intuition of a whole world and is able to transmit it on demand, like in your examples. It's an interesting dichotomy.
Structurally, though, I'm sort of pessimistic. Throughout my career as a programmer, I've earned much more money than electronic engineers whose skills are mostly very similar, and probably much of this happy situation is due to the fact that my productivity depends only on me having access to a computer with GCC and Perl or Python on it, and the internet. If I were living in rural Malawi, I probably couldn't practice my trade, because the US$200 it takes to buy a working laptop is a year's wages there, and people lack the social permission to innovate. (William Kamkwamba's astounding achievements under those circumstances deserve more recognition. Read his autobiography!) But, if I work in any developed economy, that's somewhere between 1 hour and 20 hours of my earnings, so I'm not dependent on investors to create jobs for me.
By contrast, electrical engineers mostly can't ship their designs unless an investor is willing to put up the capital to produce a batch of PCBs or chips — probably three batches or so before you get a fully working product. If you're working on a cutting-edge chip, that's several million dollars, so you're probably not going to save that up while working as an employee. This puts electrical engineers in a much worse bargaining position relative to investors. To a smaller extent, the same thing applies to machinists, auto mechanics, and many other skilled workers: they only get jobs if investors invest to create jobs for them.
The capital-intensive nature of current AI seems like it might push the negotiation equilibrium for programmers two or three orders of magnitude in favor of investors.
But it might not work out that way, and, at least at the moment, I'm finally bringing about numerous projects I'd been procrastinating on for years.
The only problem I have at the moment is it's very prone to hallucinations, even now, yes frontier models astra fable with all the bells and whistles. This makes it hard to confidently use while learning because I have to be on the lookout for lies while I'm learning, which is precisely the moment I am least able to distinguish them. So instead theres just a constant low lying dread.
Nonetheless, I am able to get some value out of them. Just not all, everything requires manual effort to duplicate and check which you should probably be doing anyway as part of learning
Then it suggested writing a fuzzer to try to flush out more soundness problems. It loves fuzzers! And usually they are an excellent cost/benefit tradeoff. However, in this case, I questioned whether a fuzzer would ever actually succeed at finding proofs of a theorem it was set to prove, even unsound proofs, and after doing some tests it admitted that the fuzzer it had proposed would have been completely useless.
Then the conversation was incorrectly flagged as me working on a malicious security attack, so I was downgraded to Opus 4.8. I switched back to Fable, renamed the file in its scratchpad, and asked it to please use the term "generative testing" instead of "fuzzing". Thanks to not using the computer-security name for generative testing, there were no further false flags.
Then, this morning, I was reading the spec it proved its program fulfilled, and asked whether a certain trivially incorrect alternative program would also fulfill the spec (a misformalization problem rather than a soundness problem). It churned away for a while, discovering that while, actually, no, that program would be rejected, a different trivially incorrect program would pass, and credited me in the docs with pointing out the issue. I pointed out that in fact the issue it had found was completely different from my stupid misreading of the spec. It fixed the doc.
Fable 5.1 isn't Mythos but it's generally considered to be a "frontier model".
So, from my point of view, the whole experience has been a constant fractal of hallucination, in which I have to constantly struggle to keep my grip (and Claude's grip) on actual reality, because it's so willing to make up surface-plausible nonsense.
Misinterpreting the results of performance testing it had just run to argue for the exact opposite of what the data it generated showed.
Stating something was current guidance (a quick read shows the document it found was from 2016, it was served the last edit date in it's API call, along with newer documents that contradict it).
Assuming what a Jira ticket said without ever reading it with it's tools and then doubling down on the contents it has assumed.
On learning specifically, it constantly gets grammar in foreign languages wrong it can write fluently when prompted correctly but when asked the sort of wrongheaded questions from flawed premises learners commonly make it is prone to making stuff up. I experienced this yesterday when asking about how danish comparisons work.
Heck i mean see https://alignment.openai.com/misalignment-reports/self-gener...
They are prone to make up restrictions for themselves you never asked for. Ive seen this behavior on occasion also.
Likewise, you may not feel like AI is de-skilling your brain. But it probably is. We don‘t have the research (yet) that AI is addictive and causes brain atrophy, but all the evidence is certainly pointing that way, the same way the evidence were pointing that way about tobacco in the 1950s. My only hope is that it doesn’t take us another 2 decades to prove the obvious.
It is, but why is that a problem? Moving from physical labor on the farm, factory or construction site to sedentary work and lifestyles would also atrophy our muscles so now we pursue physical activities we actually enjoy like gym and sports instead of hanging on to those dangerous and strenuous physical labor jobs just to stay in shape.
Similarly, you will use the AI to churn through the repetitive mundane tasks the AI can do, and then work your brain on the activities you actually enjoy.
Now if you choose to not exercise your brain and dumb yourself down the same way sedentary people don't exercise their bodies and get obese, then I guess that's on you, but we can't force the world to technologically regress just because some people are lazy and don't exercise, the same way we haven't forced construction workers to use pickaxes instead of machinery to tear up a road just to make sure they stay in shape and don't get too fat from sitting in their air conditioned excavators.
I used to have several good answers, but now I use Claude for everything, I can't remember any
I think that was the same day I prototyped an approach to using Service Workers from localhost as a platform for persistent mobile apps that don't show up in the app list but also don't rely on the TLS CA system for their security. Which involved learning a lot of stuff about the Service Worker lifecycle and localStorage and IndexedDB that I didn't know before.
It's just a lot.
When I see people worry about LLMs atrophying their mental abilities I assume they haven't thought very hard about ways to lean into using them to expand their mental capabilities.
It has definitely accelerated my learning: through the process of writing rigorous plans, I have learned so much about network programming... the intricacies of HTTP2, how to design a fast MITM proxy, performance pitfalls in SSL...
These are things I studiously avoided learning for a decade, now demystified, mostly through Claude patiently rendering many figures and diagrams.
And with Fable, I was able to ship a working Envoy Rust extension in a one-shot.
On the other hand, my grasp on the details is tenuous. Every so often the agent can't progress and I am stuck for ideas, hitting different prompts like they were slot machines. I forget how to solve problems by myself.
I can feel myself becoming supine and dependent on something I know is going to become more expensive, a dependency AI vendors will seek to exploit. It has happened quickly. I do not really consent; it is forced on me by my employer.
Obviously there are higher-level design issues that I might not notice while engaging with the code at the byte-by-byte level, but I won't have the embarrassing problem I had a couple of weeks ago where duck.ai wrote me a CPU in Verilog, and after I tested it, I tried to write something in Verilog myself and couldn't even figure out how to write a syntactically correct XOR-gate module. (Verilator's parse errors are not designed as a Verilog tutorial, it turns out.)
These 'serious' bugs aren't important if you've been working on this code base for years and only now they pop up. I suspect - although I'm guessing - that probably a hobby project.
Frankly speaking, although this comment is very dismissive about the opinion blog article - assertively stating that this isn't a well-thought-out post - it seems to me that the personal anekdote is irrelevant and that the blog post in question still fully stands.
(... Palm Springs has around 100 golf courses)
> As a historical U.S. benchmark, an average 18-hole facility had about 80.7 irrigated turf acres and used approximately 152.5 acre-feet/year—about 49.7 million gallons (188 million litres) annually.
So about 220.
But it's still, ahem, a drop in the bucket compared to the California almond industry.
(I was only half joking)
Sure they can mostly write better code than a toddler but this constant nudging and reminding and reiterating and stopping them from using the token budget of the whole company for a one off script. It gets tiring and I feel like I am losing brain power while doing it. Maybe it's faster but explosive diarrhea is also a faster way to produce shit.
i'm in the midst of a very large global roll out of a new system including about 24 separate erp integrations. My team's system is dependent on another system coming online first then we go then the integrations come online then a massive data migration happens and ends with all the associated testing. So like a huge number of dependencies and I'm second in line. Today we get word that the first system is having issues with a vendor and will not come online as scheduled (our dry run deployment is tomorrow and spans all next week as each dependency gets their turn. Week after next is PROD.
We're not heavily integrated into that first system but we are in spots and so there's a reason why they go first. Writing around that system is feasible but we're looking around 5k lines which isn't a lot but there's still testing and sign off. My offshore team is in bed, meanwhile they, and onshore, all have other shit to do anyway so pulling them just puts everything else behind.
I tasked an agents to make the changes as soon as i woke up to the news, they got it mostly right. It took two rounds of fixes with some offshore testers who stayed up late but the PR got in and merged. We just did (literally like 5min ago) a validation run against our target system and we're green for tomorrow. I told the testers to goto bed and then i pulled up HN and opened a coke.
There's no way in hell that would have happened without the coding agents we had on tap. So, yeah, i find a lot of value in the rate at which AI can work on code even if it's not perfect every time.
Maybe not as satisfying to people who enjoy being heroes. But it would not have been an automatic disaster.
I'm still a lot faster for certain things with AI but its weird. Instead of just being annoyed about some weird bug, i'm annoyed about an LLM which can do everything and then falls over itself on weird issues.
It feels weird true but it still also relevant faster?
Proof of this is the amount of unnecessary tasks that Claude does just as an excuse for not doing a good job doing the tasks that we ask it to do
It's called a fancy word "steering". Most of engineering is now steering or providing "taste" to AIs so they don't produce slop
I also found that slowing down your development (just by a bit!) on purpose helps. Do not rush into implementing your new idea and give yourself at least a couple of days to think it through.
Also we’re just so damn stupid to learn from history, or even just people 10 years older than us, that we repeat the cycle.
And there I guess is where saying a new sucker is born every minute is from.
There's the lingering societal PTSD to consider, but I think most of the challenge in the aftermath are latent issues that preexisted covid and it just brought them to the surface. I think our world a couple decades from now will be stronger than it would have been in a universe where covid never happened, and actually has a better chance at dealing with the next covid-level threat. Perhaps that is this, in a way.
Covid proved that a healthy looking society is not always so healthy, and I think it works in reverse too. The outcome of the upcoming election will tell us something about how far we have to go.
The places that needed restrictions such as hospitals & nursing homes still got covid by & large. We didn’t necessarily need to close down the whole show.
I’ve had my jabs, also had covid multiple times. I’m not a disbeliever, I just think the collective reaction was completely OTT.
As a result, they had relatively short periods of lockdown compared to other countries, such as the UK, which had comprehensive vaccination but dithered about going into lockdown.
But I can tell you that our collective sense of (unusually strong) community has taken six years since the first lockdown (four and a half years since the end of mask restrictions) to truly return to what it was before.
So even in this quite cushioned place I think we didn't really return to a sense of proper ordinary community positivity for quite a long time (it helps that we had a pretty great summer). Last summer things still felt very disjointed.
Kids, young adults, I can assure you, resent what happened and how poorly we managed it.
In other towns where community was weak, a lot of damage has been done, and you can see that in how little collective spirit there is in dealing with new challenges. Even around where I live, things like reduced footfall and contribution shortages in community services have been used as a pretext to cut them entirely. We have done damage to young people by simply deleting community things we benefited from that they no longer will.
But the resentment isn’t towards the handling, it’s towards the reality. It sucks covid happened and it shouldn’t have. But there’s nothing that could have been done to save their youth; it was already ruined for those years.
I mean, if the lockdown didn’t happen and instead a few million more people died, would they have preferred that? I doubt it, especially considering such a situation would inevitably result in even stricter restrictions going forward. After all, lockdown was a reaction. If you make the thing it’s reacting to even bigger, even more of a problem, then… well… the reaction will be more extreme.
That’s basically all the elderly or an entire cohort, I’m really struggling to believe that.
Oooooh yes it is. They are so mad at how badly we handled it. And they are right to be.
> I mean, if the lockdown didn’t happen
That isn't their complaint. Their complaint is not the first one (except that in our case in the UK it was idiotically weeks late and major sporting events happened; the older ones understand how stupid that was). It's the fact that we subsequently undermined it, and then did it again. And again. And again.
The communities that did exist were always running on fumes, basically only existing due to inertia. When the inertia was cut, even if only for a couple weeks in some places, they were done. That’s it.
The social damage has been here, and we’ve been zombie-ing our way through it. Covid just let the undead stay dead, and turns out we can’t revive it.
My child had two intelligent and supportive parents, including a stay-at-home mother, and it was still rough. Many of her classmates just flat-out lost a year of education. There's still obvious effects on her cohort years later.
I first started noticing this in the 90’s .. comp-sci grads were entering the industry with no clue whatsoever how to do software. (Of course its gotten worse since then, but I started noticing it in the 90’s..)
Everything old was thrown away as being archaic and obsolete - only the New Cool Shit™ mattered .. except nobody had ever done anything, properly, with the New Cool Shit™ - everything was still running on the old.
(Unix was dying, everyone was learning only Microsoft tech because “that was the future” ... until it wasn’t. Now, a majority of us are running 21st century Unix workstations given us .. by Apple, of all companies, which didn’t die so easily, after all..)
People entered the market not because they were truly interested in improving the world through computerization, but because they wanted the lifestyle afforded to them by a career in “Information Technology”, a nascent term back then which simply meant “career path for the budding materialists”. Trouble is, you can’t be materialistic with computers, they are almost entirely a spiritual device, which value is determined strictly and only on the decision of value made by humans. It is humans which decide the true value of all that physical hardware after all.
I think this cyclical amnesia is driven by materialist consumerism. People who take a less material approach to technology, tend to build stuff that lasts a long time.
The reason I think it happens in cycles of 4 years, is that is the average time it takes someone to enter the academic churn, and get spit out on the other end, ready to join the work force and do big things.
Or .. not.
They know what they're doing, the people who fund them know it and the people with half a working brain cell sooner or later hear someone like me and go 'oh, that explains it'.
It's much simpler than some mythical cycles - manufactured 'mass stupidity' is a conscious, deliberate, ongoing choice.
It used to be religious organizations, then it was newspapers, now its social media platforms. The playbook has been the same for thousands of years - nothing has changed.
To save everyone some time - the playbook is you're cattle, I'm shepherd. I'm master, you're slave. It's not anymore complicated.
The bit 'educated' people miss is that most people would love nothing more than to be the master (freedom they call it? American doublespeak). They dislike being slaves, not the concept of slavery.
Anyhoo.
Good try.
This rings true.
I don't know how this will play out, but I haven't seen anything like this before.
When I tried using agents for something as a test it immediately started doing things instead of being part of a conversation. I want to be actively involved in the process, not sit back and let AI agents write/generate stuff that I'd have to/end up rewriting/modifying anyway when it goes against the design I have in mind.
The other thing I don't like about agents is their ability to run any command [1]. That seems like a nightmare w.r.t. the potential for leaking secrets (signing/access keys, etc.) or doing damage (deleting files, database tables, etc.).
[1] You can set the option to review every command it runs, but you're then just hand-holding the agent.
The first group is generally disillusioned, for two reasons. First, it's an attack on their hobby. Second, they sort of can't let go: they want to own the product, they want to understand if the code is good or bad, and they spend a lot of time cleaning up after LLMs. Which, frankly, is not fun. You're no longer doing anything clever, you're just a janitor.
The second group is over the moon about it because they feel it gives them the elite powers previously only reserved for greybeards.
I don't think this is unique to coding. It's the same thing with writing. If you like writing, you probably hate LLMs. If you see writing as a boring chore that needs to be done, you are delighted to have a button you can press. Haha, take that all the influential bloggers, tech writers, etc. I can now do your job at 10x the speed.
Just a bunch of controversial ideas: structured programming, null, intellisense, microservices, cloud first, serverless, OOP, "Clean Code", exceptions, SaaS.
The approach currently being foisted upon me is to offload almost everything to LLMs (have it write a complex tech spec -> one shot into tickets -> one shot implementation of said tickets), with humans reviewing throughout, and repeating this iteration until it 'looks good'...throwing sh*t at the wall until something sticks, basically. However, we're being expected to review at a far faster pace than one reasonably can while maintaining an understanding of the system.
Meaning, with this paradigm, humans will largely be rubber stampers and will atrophy their abilities as a result, which will seemingly result in compounding adverse effects.
TLDR in my experience the AI can help with some 'busy work' eg translating a well defined solution in my head into code. The time it takes to understand an implementation and ensure correctness will not change. LLMs cannot reliably do this. This traditionally has occurred during implementation by the implementer, and during code review by code reviewers. I don't think simply shifting the implementer's comprehension 'duties' to code reviewers provides any benefit.
It was a huge shift in the world of system administration, gave birth to devops, and, along with the rise of containers & cloud computing, it radically altered how companies ran their infrastructure
Some people leaned into it, others didn't and a huge rift opened up between them
I used to say "automate all the things" - I still do, but I used to too
AI tools are just an acceleration of that mindset and in my world of cloud/devops/sre I'm heavily leaning into AI-driven development and daily workflow
I still count myself as "dejected" overall. I'm dejected by the economic shape of AI which seems destined to keep concentrating outsized rewards to the top few who own it or have enough capital to shackle it to their will. I'm fearful that intelligence, once it becomes a commodity you can rent any time you may need it, will be socially devalued in our already anti-intellectual society. I worry that in a couple decades we may resemble the world of "The Machine Stops" (1909), where nobody really knows how things work.
Of course we already live in such a complex world, no one person has complete knowledge of the "stack" they rely on. I can write software in C or assembler but I can't design a CPU and don't really understand how one is manufactured. (I may someday study that field, but I haven't yet!) But I take solace in the fact that somebody out there, has put the time in to study each of those things and is an expert in them. At every layer and in every niche of our engineering world there are masters of their craft, and there are students learning the fundamentals to keep that knowledge alive and growing. What if in 30 or 40 years that is not the case, and there are whole corners of knowledge the modern world depends on where everybody is reduced to "I dunno how it works, but Claude said..."?
Oh my god this nails my experience to a T.
Now a new powerful tool shows up and I think it is time for the Jesus Christ camp to throw in the towel.
Samuel Butler presaged this in Erewhon (1872) : "May not man himself become a sort of parasite upon the machines? An affectionate machine-tickling aphid?"
But if you do think vulnerability research matters, and you're trying to argue that frontier models aren't a seismic change for that discipline, you have almost no company. Vulnerability researchers are overwhelmingly leaning on automation to find vulnerabilities and, just as importantly, generate the tooling required to test hypotheses.
You can feel about that however you want to feel about it. I mostly don't care, except: you can watch people like this being negatively polarized back into the bad old days of the mid-1990s, content-free CERT advisories, and vendor-controlled "responsible disclosure" by a use case that frontier models unimpeachably excel at.
And yet we continue to do so. I understand the feeling of loss some people may be facing. And there are definitely some really bad practices - like nakedly spewing claudspeak at your colleagues instead of communicating. Or raising a PR you don’t understand. There are asymmetries we haven’t learned to navigate. But we aren’t returning to a world where it doesn’t dominate our discipline so it’s best to find opportunities.
For me the answer is still absolutely resolutely “no”.
Why is using AI tools self-debasing or degrading?
Programming is inherently analytical and logic-driven. It’s a great brain exercise, even if the code has no value. When you use AI, you lose that exercise. What replaces it isn’t the same.
I mean, consider. I can solve a crossword, or I can ask AI to solve the crossword. AI will do it perfectly, and faster too. But which one is better for my brain? What was my goal with solving the crossword, anyway? On the surface it was to find a solution to the crossword. But, maybe, deeper down, the goal was to improve myself in some way.
People conflate the improvement of products with the improvement of self. Maybe it’s a result of our consumerist mindset. But the truth is the product can improve greatly, and you can be making it, while you yourself degrade.
We write better and better code, at a faster rate, but are we better programmers than before? Maybe, maybe not. I’m leaning maybe not.
It’s not new or unique. The assembly line is the same. Sure, I can build better furniture faster at the factory than by hand. But what is the goal here? Is it to make the best furniture, or to become the best carpenter?
If it’s to make the best furniture, the best product, then I’ve won. If it’s to become the best carpenter, then I’ve lost heavily.
So it should be utterly unsurprising that many people are going through a bit of an existential crisis around this. Because what you actually sat down and enjoyed doing, what motivated you, may be entirely gone now.
And on top of that, there’s an extreme amount of pressure to do more in less time, which is by definition stressful. And do much more context switching.
I’m not sure I follow. There are dozens of zero day, full RCE/privilege escalation linux vulnerabilities that have been found and fixed due to the use of LLMs. Some of which existed for decades. Unclear how that doesn’t make us safer than before.
AI , trained on that garbage , is producing what now? Supposedly clumsy , buggy and so on.
The lack of self awareness is just hilarious.
LLMs are actually producing a lot of pretty good stuff, can debug things that would have taken an entire team a week, and the people running AI companies are also generally like the most boring supervillains imaginable. All true.
It is also completely screwing up the global economy, and most people barely understand what it is and what's happening.
It's also not going to collapse anytime soon as a technology despite what the economy does, and it's going to get a lot worse before it gets better. Everyone who's extreme on it on either end is generally wrong.
Though if any followers still exist, they probably wouldn't agree that 𒀭𒂗𒆠 was just a fad.
rotary telephones and pay phones went away but we still have phones.
What is screwing up 'the global economy'? LLMs?
It was annoying before when I had a very clear idea of what I wanted and yet it still took a whole week to implement.
Now, with AI coding, I can implement any decent sized feature, exactly how I want, in a few hours and it's all polished and ready, all edge cases handled.
Everything it's generating looks almost exactly like what I would have written, just written faster.
Personally, I feel avenged by AI because I had been saying for years that you don't really need static typing once you reach a certain level, getting types right isn't the most difficult problem and isn't a significant source of bugs. Everyone was gaslighting me about this... Yet now everyone can verify themselves because AI has reached this level I was speaking of.
Now anyone who coded with a frontier model on both TypeScript and JavaScript can see that it makes no difference at all. I can't remember ever seeing Claude mistake the type of a variable with either language... And TBH, I find Vanilla JavaScript from AI to be more succinct, not over-engineered like Typescript. Which is a point I'd been trying to make for years about incentives and actual patterns of usage (as opposed to theoretical benefits).
Same. I quit, aside from two contracts I'll serve until they run out, I'll be studying Electrical Engineering. Even if AI takes over that space... good luck constructing a robot with the dexterity required to pull cables.
To anyone in IT... go and study for some qualification in tasks not easily doable for a machine. The trades are going to be a goldmine especially with all the boomers retiring. Or buy some ranch in the midst of nowhere and farm artisanal chickens, cattle or goats.
(For legal reasons, the latter was a joke. Farming is extremely risky, requires a lot of upfront cash, a lot of what used to be generational knowledge, but it seems to attract a lot of IT people, especially for whatever reason the goat farming)
https://datacenters.google/discover-more/photo-gallery/ and scroll down to "The Dalles, Oregon" and well... look at them.
And then its reported water use:
https://www.oregonlive.com/silicon-forest/2022/12/googles-wa...
> Google’s water use in The Dalles has nearly tripled in the past five years, and the company’s data centers now consume more than a quarter of all the water used in the city.
> That’s according to records released this week after the city settled a lawsuit against The Oregonian/OregonLive and agreed to hand over data on Google’s water consumption. The company’s water use is poised to continue soaring in the years ahead, as Google has plans for two more data centers along the Columbia River.
https://www.oregonlive.com/silicon-forest/2021/11/the-dalles...
> Google is contemplating two new server farms on the site of a former aluminum smelter in The Dalles, where it already has an enormous campus of data centers on its property along the Columbia River.
> Google says it needs more water to cool its data centers, but neither the company nor the city will say how much more – only that The Dalles can’t meet Google’s needs without expanding its water system. The deal calls for Google to pay for the upgrade.
> Even so, the proposed water pact has attracted scrutiny and skepticism in The Dalles, a riverfront city of about 15,000 approximately 80 miles east of Portland.
> Residents and nearby farmers are concerned about the city’s long-term water supply amid an ongoing drought. They complain they don’t know enough about Google’s actual water use.
----
It is possible to do some cooling with closed cycle, though more than a few data centers have been built with open cycle cooling in places were the water table is precarious or in parts of the country under drought conditions.
Unless a data center construction discloses its water use and shows that it isn't using a lot, then people are assuming its using as much as it can (and up to the water rights or capacity that it has). ... Which isn't an unreasonable assumption to make.
https://www.oregonlive.com/silicon-forest/2026/04/more-orego...
> Google’s data centers gulped down nearly 550 million gallons of water in The Dalles in 2025. That’s nearly 40% of all the water consumed in the entire city and a huge jump from the year before.
> The city expects that local water consumption will soar over the next several years and bills will nearly double as The Dalles works to upgrade its aging water system. But the city won’t say how much of the rising demand comes from Google, citing a promise to keep the numbers secret and confidentiality provisions in Oregon public records law.
And data centers are being very cagy with their water consumption because the amount of water that it uses is related to the amount of compute it has and that is being held as an industry secret.
Compare:
> Annual water withdrawals in Oregon since 1985 have ranged from 7.3M to 9.4M acre-feet (AF)
https://www.oregon.gov/owrd/WRDPublications1/230721_FINAL_Bu...
Note that 7.3M acre-feet is equal to 2.3T gallons. 550M/2.3T = 0.02%
https://oregon.public.law/statutes/ors_537.801
> Therefore, the Legislative Assembly declares that the waters of the state may not be appropriated, stored or diverted for use outside the basin of origin except in compliance with the provisions of ORS 537.801 (Definitions) to 537.860 (Vested rights protected), including, if applicable, the prior approval of the Legislative Assembly under ORS 537.810 (Diversion or appropriation of waters from basin of origin without legislative consent prohibited).
Evaporative cooling of a data center would constitute a diversion of the water outside of the Columbia River Basin.
Furthermore, the river water rights aren't owned by the city (or the aluminum plant that Google bought). There are other treaties and regulations on the Columbia River to ensure that it has adequate supply for power and for fish.
Google is using ground water rights and pulling. Furthermore, even though there's a river there, the area is in drought conditions. The supply of water percolating from the river into the groundwater isn't sufficient for human needs in that area.
https://www.oregonwaterdata.org/datasets/94c6ec9b19de4ce6b7e...
You can see that the groundwater in The Dalles has a status of "Critical".
Citizens there have been under water restrictions for some time.
https://www.thedalles.gov/news_detail_T4_R275.php
> Voluntary water restrictions currently in place.
https://www.columbiagorgenews.com/news/poor-snowpack-and-the...
> About 70-80% of the water consumed annually by residents and businesses in The Dalles comes from Crow Creek Reservoir. Fed by South Fork Mill Creek, Crow Creek and a pipeline that diverts flows from the Dog River, it held 123 million gallons on Sept. 4, roughly seven million gallons less than the same time last year.
> While the situation isn’t dire, as Public Works Director Dale McCabe emphasized, it’s not normal. The city issued similar voluntary restrictions last summer after two of its now five groundwater wells went offline; where that was spurred by mechanical failures, however, the current advisory is a product of environmental factors.
> “This is fairly new,” McCabe said. “I’m not remembering a period where we went into curtailment for quite some time before this.”
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Note that "it held 123 million gallons on Sept. 4, roughly seven million gallons less than the same time last year" in context of Google's use of water in 2025: "Google’s data centers gulped down nearly 550 million gallons of water in The Dalles in 2025."
Those are different numbers (current reservoir amount and total use) ... but its something that people will compare.
So there's truth in the statement afterall. Clearly a powerful PR campaign going on because there is soooo many dumb takes this kind of argument vanishes.
I do think that amoung all our water uses this is easily the nicest amoung them. I think datacenters are the new factories and as far as factories go they are the cleanest ones ever made. But I suppose if you have the impression AI is useless then it makes sense. But if this is america's future industry we should make room. These centers are even funding infrastructure upgrades. To me they are the closest thing we'll get to reindustrialization in our lives and I would still want a stronger push for even more aggressive buildout.
https://droughtmonitor.unl.edu/CurrentMap/StateDroughtMonito...
I don't see it so much as a "PR campaign" against it, but rather it is a populist issue that has broad appeal being against technology companies that are seen as the bad guys.
The data center build outs are not doing themselves any favors by going cheap (evaporative cooling), noisy fans ( https://www.npr.org/2026/09/17/nx-s1-5954414/residents-file-... ) and then being secretive about the "how much is there" makes it look all the more nefarious and underhanded.
The claims of "its taking our water" or "its raising our electric bills" or "its taking our (kids) jobs" or "its stealing all our art" are all things that have some grain of truth to them and easy to rally behind one (or all) of those reasons. The choice of water as the topic is easily the most visible and the one that can get farmers and city folk to agree on.
Going to closed cycle cooling, funding the reuse of waste heat for winter district heating, and such could go to mitigate the public outrage about them... but those aren't the cheapest ways to build them.
I jest, of course. The actual argument is something about most water being frozen and how some people live in deserts so we should all live as if we were desert dwellers. As you can tell I'm not very convinced by it.
Water is literally the least scarce thing on earth.
Hits all the right buttons for the motivated reasoner: An eco-disaster that our brains aren’t climate-change numb to. A threat to the most precious fundamental substance in the service of a high-tech fad. An evocative symbol of corporate recklessness in the service of greed.
That it’s not really a big deal compared to, say, almond cultivation is no match for that brain-niche fit.
Personally, I agree with the author on some things. The copyright laundering, the PR theatrics in search of regulatory capture, the concentration of power in a handful of gargantuan corporations in a country currently headed for totalitarianism at an alarming pace. The proliferation of slop drowning out all the good stuff. These are genuine issues, and they worry me, a great deal.
And yet, it's become impossible to seriously contend that this technology isn't tremendously useful for certain tasks. I've used it myself with good results. But I don't buy the maximally bullish view that an LLM will eventually surpass humans in all areas. There are severe flaws with the technology that are inherent to its architecture and simply cannot be scaled away. This is as incontrovertible to me as its usefulness. The trough of disillusionment is coming for all of us, it always does. And much like the internet past the trough, we'll have a lot of cool new shit as a result of this technology, and we'll have a lot of horrifying new problems as well. This is the case for any paradigm shifting technology.
That's my view when trying my best to be objective.
Subjectively though, I'm deeply depressed about it all. LLMs have taken everything I love about computing and turned it on its head. I got into computers because they were so different from people. Mathematical, rigorous, efficient, unambigious(yes, bugs can be very confusing but there's always a satisfying and logical answer to dig out with enough effort). Now, apparently, to do the job I (used to) love, I have to spend most my time spoonfeeding instructions to a pretentious, know-it-all asshole who repeatedly fails to follow simple instruction, and yet is somehow still better than me at my job. I hate it. I'm 10 times more productive, and 100% of the joy is gone. I've quit, and I'm now considering what the fuck to do with my life. Something with minimal computer involvement. I will continue to code as a hobby and tool for my own purposes, LLM free, but I won't even bother uploading my code anywhere, because what's the point.
It's a great time to be alive. Everyone is infected with pessimism.
The main cause of water fear mongering is that one woman’s well was dirty during construction of a data center. First construction is not the center running, and having lived on a well they get dirty for all kinds of reasons.
https://www.eesi.org/articles/view/data-centers-and-water-co...
According to EESI (a bipartisan-founded non-profit), a large data center:
> can consume up to 5 million gallons per day, equivalent to the water use of a town populated by 10,000 to 50,000 people.
Also noting that AI datacenters can use more.
> Approximately 80% of the water (typically freshwater) withdrawn by data centers evaporates, with the remaining water discharged to municipal wastewater facilities.
I don't think 'anyone who thinks X is Y' is a good basis for discussion, which is the real point.
I don't disagree with your assertion; however you do have to realize that their grievances, while not completely informed, are not wrong.
In a world where everybody seems to be quoting grok with no further thought process you would think people would be more welcoming of someone who is "slightly wrong" on occasion. It's the strongest indicator that a flawed human being got their information not directly from a machine.
However I live in a much nicer area than Chicago and any Walmart, large mass of people, or DC would really destroy the PV as well as it would be an eyesore.
I don't really understand why so many just want to over industrialize so many beautiful places so that a corp. can sell the next gimmicky iteration of our "best model yet" which is just slightly slower and more expensive then the previous.
There are certainly problems that can be crated by dumping heat into a body of water, but that's not the argument being made.
I'm willing to bet that a datacenter creates a fraction of the pollution of a similarly sized industrial facility such as a chemical plant, refinery, smelter, or steel mill.
That source of power, since our grid is so outdated and struggles with the weight of these power-hogs, EVs as well as increased usage of AC during the summers create some dangerous conditions.
There is the risk of heavy metals getting into the water supply as the copper degrades but that will only be a problem down the line, that's prescient but not yet realized.
> I'm willing to bet that a datacenter creates a fraction of the pollution of a similarly sized industrial facility such as a chemical plant, refinery, smelter, or steel mill.
I agree; however I would not want a DC or a refinery, smelter or steel mill anywhere near my town. We have industrial districting for that reason, and because a lot of DC projects want to be put next to lakes and water sources, this causes issues for the residents.
In the case of one amazon data center, they were pulling in water that already had nitrates in it due to agricultural run off, but it wasn't enough nitrates to cause a problem for anyone until the data center came. It pulled in a massive amount of water, a lot of which was evaporated and that left behind water with very high concentrations of nitrates.
Normally, the nitrates would be filtered naturally and would mostly remain in the top layers of soil. Amazon pumped out 10s of millions of gallons of the vastly more contaminated water. It was so much water that it was forced much deeper into the ground. It was pushed deep enough to reach the aquifer which contaminated the water source for an entire community of 45,000 people.
Suddenly the water coming out of people's taps was polluted at 10x the federal level for safe drinking water. People got sick. Cancer rates spiked. Babies died. Amazon was forced to settle and pay out 20 million for water treatment and to dig new deeper wells for the community.
> I'm willing to bet that a data center creates a fraction of the pollution of a similarly sized industrial facility such as a chemical plant, refinery, smelter, or steel mill.
This is whataboutism. The existence of other bad things, or even worse things, doesn't make data centers good. They are a problem for the environment regardless of what else is a problem and the companies who build and operate data centers should be held 100% accountable for the harm they cause.
Or about 0.6% of the water used to grow almonds
https://sustainability.google/reports/google-2026-environmen...
https://www.aboutamazon.com/news/sustainability/amazon-data-...
Fortunately, now we have computers, which are great at unit conversion, so we can cut right through these feeble attempts at obfuscation. In non-medieval units, 10.9 billion gallons per year is 41.3 million cubic meters per year or 1.3 cubic meters per second. The river a few kilometers from me has a discharge of 22000 cubic meters per second (of fresh water dumped into the sea), so Google is the equivalent using 0.006% of the Rio de la Plata. Lake Superior contains 12070 cubic kilometers of water, which is 1.207 × 10¹³ cubic meters, also of fresh water, so Google's current use would dry up Lake Superior in only 290,000 years.
Google is mostly not very close to Lake Superior or the Rio de la Plata; a more relevant river might be the Sacramento River, which drains into the San Francisco Bay where Google was born, and it's much smaller than the Rio de la Plata. Specifically, its average discharge is 797m³/s, so Google is using 0.16% of the discharge of the Sacramento River. (But some of that is at datacenters far from California.)
https://en.wikipedia.org/wiki/Water_in_California#Agricultur... tells us that agriculture in California uses 34.1 million "acre feet" of water per year (Americans will do anything to avoid using the metric system, especially when they're trying to be sneaky). In non-medieval units, that's 42.1 billion cubic meters, and per year, it's 1330 cubic meters per second, almost exactly 1000 times Google's use. Of that, 18% (240 cubic meters per second) is spent on alfalfa, or was in 02014, anyway.
One major difference is that you need fresh water, like the water of the Sacramento River, to irrigate crops, but you can cool data centers with salt water from the ocean. It's less convenient, because there are a variety of annoying things that happen with biofouling and corrosion, but that's what you'd do if hyperscalers scaled up by another factor of 100× so that their water usage became large enough to be environmentally significant.
But that doesn't happen until they have 100× the computing power they have today. So anybody who tells you AI datacenters are a major water user is lying.
Thats just not true.
I only wanted to say that finding security issues was def bottlenecked by humans.