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.

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.

It's great it can do that. But it in no way justifies the social and environmental costs of AI, which is the point of the article.

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 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.

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.

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

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.

No, thank God.

One thing I've learned in life is to accept that I'm in many ways an outlier, which means that even if the research is done, it frequently doesn't apply to me anyway.

Like I wouldn't doubt that research could show that more time spent on youtube is inversely correlated with learning. But if you just use it to watch lectures or tutorials for some skill, obviously you will be an outlier.

Or when "research shows that dieting doesn't work," obviously the result there is "research shows that most people don't maintain a healthy diet," and it shouldn't dissuade you from doing so. Choosing to do so anyway is what makes you the outlier.

And so it will likely go with AI's effect on the brain. Most people will likely use it to avoid thinking, and the research will show it to be a disaster. A small group will use (or already is using) it to challenge them and expose them to new ideas. You can choose to be in the latter group if you'd like.

>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.

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.

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.

It's just a lot.

Quick to produce, emerges in vast quantities, and getting hit with it can consume all your attention immediately

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.

I do enjoy fucking, but I don't think I have the emotional bandwidth to fuck everyone.

I think you have misunderstood my comment. I don't know very much about how other people are using AI, or what effect it's having on them. It's much more important what effect it's having on them than what effect it's having on me. But all I can contribute to the conversation is what I'm personally able to attest to, and the approaches that I've found helpful or unhelpful. Hopefully those experiences and those approaches are of value to others — that's why I'm participating in the conversation, after all.

I notice that you don't seem to be participating in the conversation in the same spirit, though — your comment seems to consist entirely of personal attacks, none of which are original or insightful, predicated as they are on a fundamental misunderstanding of the post you're responding to, and it lacks any contribution of your own experiences or techniques. I think you probably should not have posted it.

Precisely. The parent is responding to what is an argument about the social, ethical long term effects of a technology by effectively saying "don't care, I personally benefit so whatever".

Ironically this kind of response just illustrates the article's point but I doubt the parent has enough self-awareness to recognize that.

We're not just sliding towards environmental catastrophe — we're deep into it! Ocean acidification is killing corals, we just had the hottest month in recorded history, mass refugee movements from climate disasters are fueling xenophobia and warfare in many parts of the world, and the rate of species extinction keeps increasing, as it has for decades. Extinct species are irreparable environmental damage; they're gone forever.

However, this is not because of massive data center buildouts. Goldman Sachs's projection in https://www.goldmansachs.com/insights/articles/us-data-cente... is that by the end of next year US data center power demand will have increased from 31GW to 66GW, roughly 17GW per year. The EIA says https://www.eia.gov/tools/faqs/faq.php?id=87&t=1 that the US uses about 95 quadrillion Btu per year (Americans will do anything to avoid using metric units). That's 3200 gigawatts. So the US's data centers are currently using 1% of the US's energy and adding ½% per year, so that in 02027 that number increases to 2%. 99% of the US's energy use is due to non-data-center causes.

And direct energy use is a way in which data centers have an especially large environmental impact. Their other potential impacts, such as cement production, sewage, parking lots, commuters driving to them, and freshwater consumption, are much less than that 1%.

Energy use, by the way, doesn't damage the environment. Burning fossil fuels does. All of China's net new energy production is coming from renewable energy — they're shutting down coal plants faster than they're building new ones, and they're decommissioning gasoline-powered vehicles faster than they're selling new ones. A friend of mine from the US told me that one of the most surprising things about visiting Shenzhen was how silent the downtown was, because almost all the cars are electric there — a much higher rate than for China overall, but even for the whole country, it's over 50% of new cars.

AI might turn out to be a wonderful thing or a terrible thing, but at least for the next decade or two, that won't be because of datacenter buildouts, which are an utterly insignificant fraction of its effect.

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.

Like golf courses in the desert.

(... Palm Springs has around 100 golf courses)

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.

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.

  > amnesia is driven by materialist consumerism

None of them were inherent problems.

Good try.

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'm in a similar position. I can easily imagine the kinds of tasks where "agentic workflow" seems useful. I just don't have any of them personally right at the moment, and think the world of software has more of them than the needs of software actually justify (due to previous bad engineering and planning).

> The other thing I don't like about agents is their ability to run any command. You can set the option to review every command it runs, but you're then just hand-holding the agent.

The thing about this is that you're treating "agent" as if it refers exclusively to the products offered for that purpose by the major LLM companies. Nothing stops you from designing and implementing your own, with a security model that you think is more sensible. The models won't have been trained against your specific tools, but you can still give them descriptions of what those tools do and then prompt them to make appropriate use of them. All that's really happening is that the LLM outputs some JSON, and your client detects that the output was a tool call (instead of a direct response), parses JSON, invokes whatever other code with whatever parameters and perhaps writes back a response.

There have been several previous HN posts on this, e.g. https://news.ycombinator.com/item?id=45840088 .

This is kinda where I’ve landed as well. I find the chat super helpful as a solo dev almost just as a sounding board for ideas and it is good at pointing out things I’m missing or not thinking through completely. I write almost all the code myself, I like the actual physical activity of writing code and find it keeps me engaged mentally for longer stretches.

I’ve also tried the agentic thing, but I find it so draining laying out in such explicit detail exactly what I want and then cleaning up what it’s messed up, like it’s easier to clean it up than just keep prompting and pulling the magic “Do This” lever.

I probably will never code without AI again. I’ve been doing this for 30 years since I was a teenager, was very fortunate in my career and don’t have to work anymore, but I still code and build because I love it, maybe even more so now with AI, but I would absolute hate my life if I was forced to just run agents all day long and never actually write or be the primary thinking driver for code.

The one thing that poisons the entire online discourse regarding LLMs to me is just simply not knowing who you're dealing with and what their problems are. This, like all things, is complex and nuanced.

For all my efforts to get LLMs to work for me, they've failed. I figure it is because the tech space I work in (Industrial Automation) simply doesn't have the training data that someone building webapps does. The few times I've put LLM to the test its failed horribly, and since my job has me existing in safety critical scenarios I don't humor what AI gives me at all.

So when I bitch about LLMs and their useless nature, its because of how I've experienced them in my craft. They get 95% of the information right, but that 5% it gets wrong can have very serious repercussions.

But when I'm talking with individuals online who see them as revolutionary? I don't know if their job is editing templates or formatting data or any other host of problems that AI can be revolutionary for. I don't know if they're full of themselves, having drank the AI koolaid. I don't know if they're just really deep into the LLM world and figured out things I have yet to learn (or am unwilling to pay for). But from a HN or Reddit discussion, they're all one in the same and without trying to figure out who they are, their opinions all carry the same weight.

Absolutely!

But that’s such a niche part of the industry. AI is in everything.

Craft was premised on the idea that a good writing and composition matters because it would be easier to read and comprehend (sometimes accepted by orgs because it was sold as cheaper).

Now AI can read the code so the craft-leaning people would need to somehow sell it as 'fewer tokens will be spent on a well factored code' or 'well factored code reduces AI hallucinations'?

Now a Slinger (using your terminology) can just ask AI to make the code look 'craftier' - and that is the best case scenario.

In other words, they will not buy what we sell and if they will they can now produce the results for cheaper. Overlooking the devil in the details, as usual.

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”.

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.

Maybe it’s worth actually listening to what these people are saying, or you may find yourself increasingly frustrated and confused as these debates intensify and AI becomes more politically and socially toxic.

that we're creating god but that it's also a fad that will go away soon?

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

This sounds like a lot, but it’s actually not very much. I mean, one singular almond requires 1,000 gallons of water. Beef requires shit ton, too.

Go vegan for a few weeks and you’ve just negated all your AI water use for the rest of your lifetime.

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.

Consume it how, exactly? Are the staff drinking it all? Because the the kit sure as hell isn't. :-/

The electricity, air pollution and noise pollution are all from natural gas. Data centers aren’t loud, on site temporary natural gas turbines are. We can instead install solar and batteries and none of these will be issues. We already grow corn for fuel at 1/10th the land efficiency of solar so it’s not like we don’t have the land for it

You could, you know, stop spreading deception about water usage if it bothers you so much when people call out deception about water usage.

At this point, I almost consider it trolling to bring it up: purposely throw in something incredibly stupid, and then throw a hissy fit when predictably called out on it.

Someone complaining about water usage is a very strong indicator that they aren't well-informed enough to contribute anything worth reading, though.

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.

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.

The Us uses 320 billion gallons a day. Google thus used 0.01% of total US water.

Or about 0.6% of the water used to grow almonds

Thank you, I wasn't aware they did this:

https://sustainability.google/reports/google-2026-environmen...

https://www.aboutamazon.com/news/sustainability/amazon-data-...

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.

Thanks <3

Sry not sure what you mean.

I only wanted to say that finding security issues was def bottlenecked by humans.