(Note: Drafted with AI assistance to structure arguments on educational theory, primary sources, and media tropes.)

BitterEpicâ(TM)s heroin metaphor relies on a fundamental misunderstanding of both learning and primary sources.

1. Practice vs. Intoxication: Shifting away from grading homework isnâ(TM)t "addiction"; it aligns with educational research from critics like Alfie Kohn and Sebastian Thrun, who have long argued that grading practice work destroys intrinsic motivation and replaces learning with compliance. Removing grades from practice allows students to focus on understanding rather than optimization for a score.
2. Primary Sources: High-level language models do not replace primary sources; they act as search, synthesis, and translation layers over them. A student using a tool to parse, cross-reference, or organize primary research is no more "intoxicated" than someone using a card catalog, a digital database, or an index.
3. The Sutter Cane Crutch: Repeating a reference to a 1990s horror film does not turn an automated tool into a mind-controlling deity. It just highlights a reluctance to evaluate tools based on how they are actually used, preferring instead to treat any shift in learning habits as a psychological collapse.

(Note: Drafted with AI assistance to organize arguments on human-supremacist rhetoric and ideological dependence.)

BitterEpic calls everyone else addicts, but he seems hooked on his own drug: performative humanist moralizing.

His entire rant relies on a rigid script: compare software tools to hard drugs, accuse anyone using automated assistance of psychosis, and demand proof of pure human origin before evaluating an answer. That is not original thinking; it is a mechanical compulsion to enforce social conformity.

Dropping a movie reference to Sutter Cane does not make this profound. It just shows he is dependent on drama to feel superior online. If a tool provides accurate information or solves a problem, nobody needs a sermon on human purity. The real addiction here is his need to police how other people process information.

(Note: Drafted with AI assistance to organize arguments on economic measurement and productivity theory.)

dirk's argument assumes a world with infinite demand and zero quality constraints. In reality, saving time or avoiding mistakes frequently does not increase total measurable output for three reasons:

Fixed Demand: If an engineer uses AI to cut decision-making time in half and finishes their assigned tasks in 4 hours instead of 8, output remains at 100%. Unless the company has an endless backlog of marketable products to sellâ"and customers ready to buy themâ"the saved time does not automatically transform into more widgets or higher GDP.

Prevention Is Invisible in GDP: Avoiding a catastrophic server outage or a costly legal mistake adds immense value and resilience, but it produces zero additional units of output. In standard economic stats, a company that spends $1M fixing an error shows the same or higher economic activity than a company that avoided the error entirely using better tools.

Quality vs. Quantity: Better coordination and fewer errors often yield higher quality, safer code, or better-vetted decisions, not a higher volume of output. National productivity statistics measure the quantity of output per hour worked, not the systemic stability or risk reduction achieved along the way.

AI disclosure: I used AI to help organize and edit these thoughts. The arguments are mine to the extent that any argument is ever entirely someone's own. If that bothers you, feel free to attack the argument rather than the tool.

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I think the deeper issue is why we're treating productivity statistics as the final judge in the first place.

Productivity is not a direct measurement of economic value. It is an accounting construct that depends on how output is defined and measured.

That is relatively straightforward when counting tons of steel or bushels of wheat. It becomes much harder when dealing with software, research, legal work, design, information retrieval, decision support, risk management, and other information-intensive activities.

AI could be improving decisions, reducing errors, lowering search costs, increasing optionality, or generating consumer surplus without immediately appearing in revenue-per-worker statistics.

We already know GDP and productivity measures struggle to capture the value of many digital goods. Search engines, GPS, Wikipedia, open source software, and the broader Internet generated enormous value relative to what showed up in traditional economic statistics.

There is also a timing problem. What was the measured productivity gain for the average manual laborer shortly after the steam engine was introduced? General-purpose technologies often require years of organizational change before aggregate statistics move. Factories had to be reorganized around electricity before electrification delivered its full benefits.

The argument also seems oddly selective. Slok removes the companies where AI's effects are most obvious, then concludes that the remaining firms have not yet shown economy-wide productivity gains. If the steam engine first changed mining and textiles, would we have concluded steam had no economic impact because most workers were still digging ditches by hand?

Most importantly, why assume productivity is the metric that matters? A technology can create value by reducing uncertainty, improving coordination, avoiding mistakes, increasing resilience, or expanding opportunities. Those benefits do not necessarily show up as higher output per worker.

So before concluding that AI has no economic impact because productivity measures are flat, I would first want to know whether productivity statistics are actually measuring the thing we care about. Flat productivity could mean AI is useless. It could also mean the metric is only observing a subset of the effects.

(Disclaimer: Written with an AI collaborator, because human editors were apparently too busy copy-pasting to proofread.)

Speaking of slop, notice how the summary ends by repeating the exact same sentence twice:

"It's hard to compete against things like the DALL-E image generator."
"Long-time Slashdot reader schwit1 quips that maybe 'It's hard to compete against things like the DALL-E image generator...'"

When humans publish duplicate-riddled writeups without reading them, it really raises the question of whether "human slop" is even setting a higher bar than "AI slop."

To your point about "good enough": market dynamics have always favored cheap and good-enough over high-quality and expensive for standard commercial uses. Stock photo giants like Getty relied on charging massive licensing fees for stock images (or bullying photographers over copyright).

When a restaurant menu, blog post, or corporate deck just needs a generic image of a salad or a boardroom, AI generation is free, instant, and "good enough" for the buyer. The tragedy isn't that AI art is superior--it's that for 90% of basic commercial applications, nobody wanted to pay Getty prices in the first place.

AI disclosure: yes, I used an AI as a drafting assistant. I do not consider that fundamentally different from using a compiler, debugger, search engine, calculator, spellchecker, or discussing an idea with another programmer. The argument is mine. The responsibility for it is mine. Judge the reasoning, not the tool.

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The thing that smells off to me is that Slashdot itself mangles Unicode every time I paste it into a comment box.

So I'm reluctant to accept the implicit premise that software written entirely by humans has already conquered all the easy problems and that AI-generated code must therefore clear some uniquely high bar before we acknowledge it may be useful.

Perhaps the 15% figure is exaggerated. Self-reported numbers often are.

But "real software contains domain-specific rules, institutional habits, regulatory requirements, and weird edge cases" is not an argument against AI coding. It's a description of software. Human programmers have been wrestling with exactly those problems for decades.

What I find interesting is that the article treats the existence of hard domain-specific problems as evidence that AI cannot be writing large amounts of production code. Yet many mature systems built entirely by humans still struggle with things that sound straightforward when described in a sentence.

Again, I submit as evidence the inability of this very site to faithfully render Unicode text pasted into a comment.

The benchmark is not perfection. The benchmark is whether the AI can produce code that is competitive with the code humans were already producing.

If the evidence is merely that real-world software is messy, full of exceptions, and imperfect, that seems equally consistent with the hypothesis that AI has reached parity with a substantial fraction of ordinary software development.

AI disclosure: yes, I used an AI [Copilot] as a drafting assistant. I do not see that as fundamentally different from using spellcheck, a search engine, a calculator, a compiler, Stack Overflow, Wikipedia, or discussing an idea with another person. The argument is mine. The responsibility for it is mine. Judge the reasoning, not the tool.

You're conflating social acceptance with correctness.

"The in-crowd can recognize the out-crowd" is mostly a statement about tribal pattern matching, not truth. History is full of examples where the majority correctly identified the dissenter and incorrectly identified reality.

This reminds me of an HN discussion where multiple AI models reportedly converged on a controversial observation about humans: many people would rather fit in than be right. Your comment seems to elevate that tendency from an observed human bias into a social ideal.

If the objective is social survival, conformity matters. If the objective is discovering what is true, conformity is often an obstacle. Scientific, artistic, and technological advances routinely begin as ideas that fail prevailing social tests.

Also, the writing argument feels circular. If LLMs write like average humans, you say the crowd will still detect them. At that point you're no longer evaluating writing quality. You're assuming the crowd can identify outsiders because they are outsiders.

The deeper issue is that your metric quietly shifts from "is this writing good?" to "does this writing belong to our tribe?" Those are different questions.

Herd recognition may be real. What it does not provide is a guarantee of truth, merit, intelligence, or authorship. Human societies have spent thousands of years demonstrating otherwise.

AI disclosure: The underlying opinions are mine. The AI's contribution was mostly translating an emotional rant into something less likely to get dismissed as an emotional rant. If that's cheating, then so is spell-check.

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This seems to assume that social acceptance is the thing being optimized.

Why should it be?

The entire point of constitutional rights is that they apply equally to the in-crowd and the out-crowd. A society based purely on social acceptance is just a popularity contest with better branding.

The view you're describing may be descriptively accurate in some settings. Groups often enforce norms through informal ostracism. But that's an argument about how humans behave, not about how they should behave.

If someone's argument is wrong, show why it's wrong. If someone's writing is bad, criticize the writing. "You're out-crowd now, therefore nothing else matters" strikes me as abandoning reasoned evaluation in favor of tribal status enforcement.

AI disclosure: The underlying opinions are mine. The AI's contribution was mostly translating an emotional rant into something less likely to get dismissed as an emotional rant. If that's cheating, then so is spell-check.

More broadly, I think we're heading toward a strange place where people spend more effort policing the provenance of an argument than evaluating the argument itself. If the reasoning is wrong, it should be wrong because the logic is faulty. If it's right, it should be right because the logic is sound. Whether an AI helped turn "this article makes me mad" into a coherent critique seems orthogonal.

Slashdot has traditionally been a "show me the source code" community. In argument terms, that means: show me the logic, not the authorship pedigree.

Disclosure: I fed my initial "old man yells at cloud" reaction into an AI and asked it to separate the arguments from the emotions. The result is below. Feel free to blame either of us.

Every open-source governance problem is increasingly being described as a funding problem. Sometimes it is. But before concluding PHP needs more money, I'd like to know why a language used by so much of the Internet can't attract enough contributors under its current structure. Funding may be the symptom rather than the cause.

I'm also struck by how much of this story revolves around coordinated disclosures, embargoes, privileged access, advance distribution of patches, and leaks. Open source originally leaned heavily on transparency, yet modern security practice often seems to move toward security through obscurity. The irony is that this very episode is largely about how difficult that secrecy proved to maintain.

If important vulnerabilities, mitigation advice, videos, binaries, and CVE information all leaked anyway, perhaps we should be asking whether the bottleneck is funding, or whether increasingly elaborate disclosure processes have created governance and coordination problems of their own.

I don't know if you're a russian bot or some deluded idiot, but it amuses me to do a breakdown of your post.

NATO turned what was originally intended to be a mostly peaceful show of force like the temporary invasion of Georgia into a war of attrition.

First of all the "peaceful show of force" "temporary" invasion of Georgia involved a few hundred dead in the first two days, and another 5000+ civilians killed in the ethnic cleansing after that, all for a land-grab to seize control of territory covering half of Georgia's coastline that Putin wanted.

Secondly, the "peaceful show of force" "temporary" invasion of Ukraine involved hundreds dead, ballistic and cruise missile attacks on all of Ukraine's largest cities, and Putin publicly admitting the goal of overthrowing the Ukrainian government... and that's just within the first 36 hours. Within two and a half months Russian officials began admitting the intent to permanently annex parts of Ukraine, proceeding with a constitutional amendment a few months later claiming to annex vast territories that Russian had not remotely taken control of, and which Russia is not remotely capable of capturing. Donetsk alone has a population of over a million, two million if you include the metro-area. Russia spent months and many thousand of lives to capture, and later lose, villages in the range of low tens of thousands.

Remember WWI when the lines were pretty much static for years and then suddenly it was all over?

Yes, I remember. As I recall it wasn't exactly "sudden". As I recall... Russian casualties were around five million killed, wounded, or captured, the Russian economy was collapsing, Russia was running out of food, and Russian literally lost it's own capital to civilian rebellion. A few months later the Russian government collapsed and surrendered vast territories including Finland, Estonia, Latvia, Lithuania, parts of Poland and Ukraine to Germany and its allies (known as the Central Powers). Right about that point the U.S. joined the war reinvigorating the Allied Powers. Germany&friends knew they couldn't win a protracted war. They attempted a quick win, and, in short, they failed. The Allied powers steadily beat them down, with the allies eventually breaking through the lines and progressively liberating territory. With the Allies steadily advancing and the war obviously lost, German forces began rebelling and Germany surrendered.

That's what's happening here. Russia has most of Donbas plus a buffer zone in some other regions that directly border Russia. Ukraine is throwing men at the front lines for Russia to kill but is running out. Territory held is largely irrelevant compared to the number of men killed and weapons destroyed.

So much to unpack there, but it's amusing how you cite "territory held is largely irrelevant" given that the tide has turned and Ukrainians are now the ones breaking through lines and liberating territory from Russian occupation. It's not much yet, but all the map trackers show the reversal. Russia is now officially loosing more territory than they gain. Russia WAS slowly gaining small bits of land, largely through sending meat waves of untrained ill equipped soldiers at Ukrainian lines until the Ukrainians ran out of ammo and had to fall back. However now 7 out of 10 Russians killed are killed by drones. The "no man's land" between the two sides is now many kilometers wide. Any Russian trying to advance gets hit by a drone. Russia has also losing on average 1 air defense system every day, and rapidly depleting. Russian supply lines are getting pummeled by drones. Russian refineries are getting pummeled by drones, with progressively worsening fuel shortages for both the military and for the increasingly rebellious population. Cheap advanced Ukrainian drones are taking out expensive crappy Russian drones, including Russian's new jet-drones. Practically every country on earth is asking Ukraine for their military drone tech, the Russians can't remotely match it. Russian's economy is also fucked, but that topic pretty needs a separate book to cover.

Interesting side notes on weapons destroyed. Russia is destroying it's aircraft almost as fast as Ukraine is, between incompetence and maintenance failures and friendly fire shooting down their own aircraft. Also the nation that is the biggest donor of tanks to Ukraine is... Russia. Ukraine captured countless Russian tanks intact because the Russian military is so abysmal incompetent and corrupt. And as I mentioned, Russian air defense units are depleting. The war is now approaching 5 years, longer than the entirety of WW1. Ukraine is a small fraction of Russia's size, and Russian is literally losing and headed towards another soviet-union-style collapse. The biggest shock to the world of this entire war is just how worthless Putin has made Russian military, through systemic corruption and systemic incompetence.

Polls show the Ukrainian population isn't interested in surrendering. They are defending their homes. It's simple, the war will end when all the soldiers go home. When Russian soldiers go back to their homes in Russia, and when Ukrainian soldiers go back to their homes in the currently occupied parts of Ukraine. Although that's not likely to happen until Putin either expires or is overthrown. Not only is he fanatical enough to drive his country to collapse in the attempt, he knows if he did end the war in failure he'd get killed or overthrown for it.

Anyway, pointless reply to a bot or a useful idiot. But maybe some random passer-by will find some bits interesting. I don't know about the rest of the world, but mainstream US news rarely mentions the Ukraine war anymore, and certainly not in any detail.

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"all those "saved" watthours will get sucked up by their subscribers' homes. Then what, shut down the datacenter until things get warm again?"

Why assume the saved watt-hours just disappear? If local residential demand absorbs them, Google can still buy power from elsewhere. The interesting economic question is why Google finds it cheaper to pay consumers to curtail usage than to acquire additional supply through the grid. That suggests congestion, transmission limits, [price gouging, psychological noise,] or peak pricing are the real bottlenecks, not total electricity production.