You seriously need to go outside and touch grass if you are so defeated by another chess winning machine

Nobody wants to Watch AI play chess, nobody wants to read ai blogposts

AI makes human writing more valuable, not less.

I will pay good money for pure human made books certified as made without a single word auto generated whether in original or during process of Translation.

In what world is "the media" not an integral, tightly-bound part of the ratchet mechanism that seeks to suppress all distinction?

The supposedly starved don't seem to care much for such food. Blogs are kind of a wasteland.

Well, there’s not much of a point leaving a comment saying “yes, this, exactly this,” so I’ll leave one here on behalf of my fellow lurkers.

The more AI gets shoved down my throat, the less I’m inclined to use it for anything, and the more I’m inspired to write my own writing, make my own art, and create my own code — with great creative joy and burning anger. Enjoy your 1000x productivity gains and your inevitable burnout as you downskill to a glorified inference loop.

I'm really getting tired of the programming obituaries. As if LLMs didn't fail at any complex task, as if they didn't vomit shit code and as if they didn't just copy patterns surrounding the new code, and as if they didn't hallucinate and downright write wrong code or made up libraries. Yet for some reason, every time you bring it up, someone will come along and say "You're not using it right then.", Is it that, or is it just that they're only doing toy projects? I'm led to believe the latter.

At this point I don't know what's organic and what's not. Reddit is filled with astroturfing for big LLM. Maybe this place is too? Even if that was not the case, I'm led to believe that it isn't uncommon for people to swallow up all of the big LLM propaganda and fall into despair, or fall into unrealistic expectations, and just parrot it everywhere else. One thing is for certain, LLM evangelism has all the money of the world, and LLM denial doesn't. It's only natural to think that the balance is tilted in terms of media presence.

Even at the best, or worst, LLMs can't do anything you couldn't do yourself better with a scaffolding prompt + manual editing, and at the end of the day, you still need the cognitive energy to review, veto, come up with, the implementation. What does this exactly do anyways other than saving you a bunch of keypresses? I wonder if the people touting it to be all that really didn't think before LLMs, of just switched their brain off on them.

I used to really like this site, but I think that just consuming the RSS feed is enough for me. I think that lobster.rs has less "trend chasing" point of views these days, and I do wonder if it might be on here there's larger amounts of non technical people jumpy to call for the funeral of things.

Setting aside the self delusion that makes a considerable number to erroneously rate themselves above average, the reason you create blog posts should not be for the attention you might gain, there simply are not the eyeballs. You create as a form of self expression, to organise your thoughts, to create a record of them.

AI can never challenge in those areas because it is, as it has always been, the act of creation is the goal.

I think most people cannot destinguish between "genuine" creativity and an artificial almalgamation of training data and human provided context. For one, I do not know what already exsists. Some work created by AI may be an obvious rip off of the style of a particular artist, but I wouldnt know. To me it might look awesome and fresh.

I think many of the more human centric thinkers will be disappointed at how many people just wont care.

What AI represents to me is a teacher! I have so long lacked a music teacher and musical tools. I spent my entire career doing invisible software at the lowest levels and now I can finally build cool tools that help me learn and practice and enjoy playing music! Screw all the haters; if you're curious about a wide range of topics and already have some knowledge, you can galavant across a vast space and learn a lot along the way.

AI is a bit of a bullshitter but don't take its bullshit as truth, like you should never take anything your teacher says as gospel. How do we know what's true? The truth of the universe and the world is that underneath it all, it is self consistent, and we keep making measurement errors. The AI is an enormous pot of magic that it's up to you to organize with...your own skills.

You have to actively resist deskilling by doing things. AI should challenge you and reward you, not make you passive.

Use AI to teach yourself by asking lots of questions and constantly testing the results against reality.

For me right now, that's the fretboard.

According to the author AI is 99% hype.

That 1% of AI utility can unlock more for humanity than 99.999% of blogs; static text hosted from a laptop in a closet.

Odd ball position that cheap publishing via the web is a path to The Next Generation for humanity is 100% hype.

Other than feeding dopamine addiction humanity has not improved greatly since we read all those insipid posts on GeoCities no one remembers today.

It's all been 99%+ hype to feed Wall Street. Young GenX and older Millennials with tech jobs were temporary political pawns and gonna end up bag holders like may older GenXers and Boomers who lived through the car boom, the housing boom, the retail boom.

Same old human shit, different hype.

Everyone wants to be a famous author, or at least a published/somewhat acknowledged one; few are willing to write their novel and be satisfied with zero or near-zero sales/readings.

But that is exactly what you need to do, especially in the age of AI. Everyone who was "in it to win it" (think linkedinslop which existed before AI) is going to certainly use AI - because they do not give a shit about the quality of themselves - they just want the result.

And you can only become a writer (unpublished, unread, or no) by doing the writing - it takes time (10,000 hours?) that cannot be replaced by AI, just like you can't have the body of a marathon runner without running (yes, yes, the joke). You may be able to get 26 miles and change away, even very fast, but unless you personally do the running of that distance without cheating, you will not get the inherent benefits.

And if you instruct an AI, or another human even, to write for you, you may get some of the results you want, but you won't have changed to become a writer.

We shouldn't celebrate the successful blogs; they're already rewarded enough. It's celebrating the unsuccessful blogs that is needed - even if, frankly, the vast majority of them are sub-AI levels of crap it is still a human changing and progressing behind them.

Babies fall over a lot but unless you take them out of the stroller and let them do so, they'll never progress to crawling, walking, running.

Might be just me though, but I definitely don’t get why blogging should be the solution.

I mean, to put a price tag on enabling vastly more creation than would otherwise have occurred!

More pretentious gatekeeping from luddites who like to yell at clouds. This is someone who would love a piece of artwork created using ai tools right up until someone told them it was created using ai tools.

Mixed messages fr

Hot take, folks packing it in because of AI probably were not difference makers before AI, and wouldn't be difference makers after it either.

I agree with the author, keep writing. It helps hone your ability to communicate effectively which we all need for some time to come (at least until we become batteries).

- spend tons of tokens on useless stuff at work (so your boss knows it’s not worth it)

- be very picky about AI generated PRs: add tons of comments, slow down the merge, etc.

There is nothing new about using machinery to automate boring / repetitive tasks, including the wall of resistance that comes up. But it should be clear that genuinely useful tooling and automation tends to become a normal part of life, from the plow, to the printing press, to the dishwasher, to digital video editing, to autocorrect, and now to large language models.

There's a lot that has to be worked out with LLMs in particular as they are now encroaching heavily upon human creativity and thought. This is an extremely important topic. But rants like these with terms like "the plagarism machine" and "the solution is that we all must vow to never use AI in any shape or form" are not really contributing.

I guess it's iterating in plain English instead of iterating in code that I'm having trouble latching onto. It's a "left brain vs right brain" kind of situation for me (not sure how valid that trope is, but it best expresses what I'm feeling).

I'm pretty good at outlining what I want to accomplish and how to get there, but cracking open vim and getting into it is super duper exciting for me, and I'm pretty good at communicating what is and isn't working with the agent when I use it. Claude (or any agent, I suppose) takes that away and doesn't fill that gap.

It's also been harder for me to stay focused with Claude since I'm basically printing code and reading the results. Claude's changesets err towards being pretty large (though I have rules [^1] to try and keep that at bay). When I use it, my mind shifts from "writing code that others might (probably won't) maintain someday)" to "writing code that builds the thing". Given those heavy diffs, I'm less inclined to pore through them than I would be if I were actively writing the code. I fear that this will lead to having less understanding of what my code is doing over time, which is sweeping the bugs and tech debt under the rug (especially since Claude, atm, likes to solve bugs with adding more code). This is probably one of those things that will just take some adjustment.

Then again, maybe part of this has to do with me being a long-time a Vim user and not having used a proper IDE for everyday development in a long time...

Okay, I think I finally came up with a good anecdote for how I'm feeling. I wear Mexican huarache sandals [^0] pretty much exclusively when the weather's warm (which is almost all year round in Houston). They are so unique, and getting them to work perfectly with my feet has been a Linux-like experience (i.e. lots and lots and LOTS of experimentation).

I used to buy them from Luna, Xero and others at, like, $150/pair. However, they are INSANELY EASY to make at home for a fraction of the price. I made four pairs at home. They didn't fit quite right, so I'll need to make them again, but I take MASSIVE satisfaction in wearing what I made.

The journey is as exciting as the destination for me; more so, even!

(Selfishly, I took a lot of pride in being able to show others how to do damn nearly everything they do in VSCode in Vim, but that's another victim of the Era of AI.)

[^0] These bad boys: https://xeroshoes.com/pages/tarahumara-sandals

But partly overlapping with perspective is reasoning (subjective or objective), which is also something that makes a judgement not arbitrary. But your pre-judgement here tells me that that part is uninteresting to you.

>Backill reasoning? Providing reasoning later is less legitimate? Why?

I think you might miss interpret the phrasing. To backfill reasoning means you reached your conclusion prior to reasoning about it, then attempt justification afterwards.

This is indeed significantly less legitimate.

>Some people state things without spelling out the reasoning because they assume it is common sense.

"Common sense isn't common" aka incredulous fallacy. It's up to you to clarify yourself. Not to expect others understand you immediately.

>Your opinions are fact.

They factually exist, but they are mutually exclusive from the definition of being a fact.

Opinions are not facts themselves.

>Your comments here are textbook arbitrariness.

Ok, let's look at a definition

>Arbitrary describes actions, decisions, or rules based on random choice, personal whim, or impulse rather than reason, system, or law.

Not sure how you could call a statement pointing out an issue with the authors position as claimed as not following any reason, or being based on whim. The reasoning was provided and referred to a specific system (synthetic vs non synthetic). Very much out of the bounds of a book definition of arbitrary.

I noticed you did not seem to provide a definition.

>To dig a little into it: it is generated content,

That's what I said...

>but that’s not necessarily what their arguments hinge on at all.

Based on what?

The author put multiple no-AI badges on the page. Infer what you wish, but it's clear the context given the broader palle of information avaible to anyone. The author drew an arbitrary line around the context to grant themselves the use of certain tools while avoiding a blow to their morals for the use of others.

They built up a dirt hill so they can feel like they are taller.

Don't support such delusions.

AI is the future. AI will do this. AI will cause that. It is inevitable. Everything is obviously changing.

They leave no room left for debate. No openness to pushback. And no evidence or proof. It just is because it is, and if you don't believe it, you're simply wrong. We saw the same sort of attitudes with blockchain and NFTs.

Which of course is a lie propagated by those who want to cast the disbelievers as mentally defective. Why the hell would you care how readable and easy to extend the code is if you weren’t interested in the result?

You're low by several orders of magnitude. "The 2025 development cycle saw 2,134 developers contribute to [Linux] kernel 6.18" [1]

[1] https://commandlinux.com/statistics/linux-kernel-contributor...

How does building agentic systems, a "really hard" problem, not just end up a "regular code" problem? Because that is what it is. A distributed systems problem with non-deterministic run lengths. How do you switch agent contexts? Similar to how you solve regular program context switching. How do you search tool capabilities and verify them? How do you effectively manage scheduled tasks?

Oh, look, you've just invented the operating system kernel. Suddenly, those 'dozen or two' experts don't seem so archaic after all!

Also, 200 years ago we didn't have bike mechanics. Car mechanics. Boat mechanics. Plumbers. Electricians. Not all new professions fade away.

With how much some people spend on tokens that they've shared on here, and concerns about raising prices, I've kind of been wondering if we're actually heading to a point where seniors who don't use AI are going to be cheaper than juniors who do.

Otherwise it's straightforward to say that the mathematics is being applied to achieve a practical goal via execution on a computer. (You'll see the term non-transitory computer-readable media" a lot in claims.) You now have a method and system. Now, caselaw frequently changes things, like the "Alice" decision in the US made it much harder to just patent things done "on a computer" but the underlying principle holds.

I'd also guess if your approach makes something faster or cheaper, it should be possible to show it is non-abstract, because resources like time and costs are not abstract quantities.

Standard disclaimer: I'm not a lawyer! I've just worked with patents extensively.

We certainly do suddenly live in "interesting times".

I’ve never found a way around it, and I don’t want to believe that some people can’t grok this field, but that is what I’ve experienced. Maybe other people can educate better.

I’ve just found that at some point you have to limit the blast radius and move onto more productive uses of your own time.

I agree if that's all you can do. Using a coding agent to complement a valuable domain-specific skill is gold.

No one will be eager to employ “ai-natives” who don’t understand what the llm is pumping out, they’ll just keep the seasoned engineers who can manage and tame the output properly. Similarly, no one is going to hire a bunch of prompt engineers to replace their accountants, they’ll hire fewer seasoned accountants who can confidently review llm output.

> you don’t know what you’re talking about

Consider: Why did Google have a bazillion TPUs, anyway?

I do not see why you can't write your spec in pseudocode if you really want to - communicating your intent to the LLM, for how the code should be developed is far closer to programming than writing skillwise.

If you expected things to stay the same forever, maybe software engineering wasn't the right career move for you. Even though it looked safe enough, given that we've spent 50 years writing the same old code the same old way, that was never guaranteed.

I for one am glad to see something genuinely new come along. The last dozen or so "paradigm shifts" turned out to be disappointing variations on the same old paradigm. Not this one, though.

Overall, we are trying to "silo" LLM-generated code into its own services with a well-defined interface so that the code can just be thrown away and regenerated (or rewritten by hand) because maintaining it is so difficult.

The only way I was able to direct the AI to a better design was by saying the words I know in my head that describe better designs. Anyone without that knowledge wouldn't be able to tell the heavy interpreter architecture wasn't good, because it was fast enough for simple test cases which all passed.

And you can say "just prompt better" but we're very quickly coming to a place where people won't even have the words to say without AI first telling them what they are. At that point it might as well just say "The design is fine don't worry about it" and how would the user know any better.

In my experience, if you are trying to dodge congestion at a peak time, so is everybody else. Excepting in the first 15-20 mins after a major incident, the alternate routes end up congested and settle to an equilbrium time because everyone is trying to do the same thing.

If a wagon or trolley hit someone that was considered the fault of the driver, every time.

When cars started arriving and being driven around by people who were wreckless and bad at it, you started getting manufacturers and "motorists" lobbying for the concept and laws around jay-walking. Even the word was a way to delegitimize what used to be normal. "Jay" was negative slang for country-person (think red-neck). The idea was "modern city people stay out of the streets!"

"Fighting Traffic" by Peter D. Norton talks about this at length.

The suburbs didn't exist when automobiles hit the market. Most people lived in cities because that's where the jobs were and transportation (outside of whatever public transportation options the cities provided) was limited. Kids and adults used the streets freely (which were for horses, though they were widened as automobiles started growing in popularity).

This changed as cars killed kids (and adults) who didn't know that cars were much faster than cars and didn't react in time. Traffic deaths were so numerous, cities invested lots of money in "safety parades" that were kind of gruesome, actually (like showing tombstones of the future deceased). [^0] Jaywalking was a crime that was invented to deal with exactly this phenomenon.

People fought HARD to keep the streets free (where else are kids going to play). People lost that battle, as we know.

[^0] https://www.bloomberg.com/news/features/2022-06-10/how-citie...

Before it was "hey $senior_programmer where's the $thing defined in this project?", which either required a dedicated person onboarding or someone's flow was interrupted - an expected cost of bringing up juniors.

Now a properly configured AI Agent can answer that question in 60 seconds, unblocking the Junior to work on something.

And no, it doesn't mean Juniors or anyone else get to make 10k line PRs of code they haven't read nor understand. That's a very different issue that can be solved by slapping people over the head.

To your individual points:

- OOP and UML are domain-specific abstractions. Aside from still being very much used in expanding niches [1], they have failed to automate much work because their proponents failed to cover enough cases to have a useful general-purpose abstraction.

- Outsourcing is a labor strategy. There's nothing technical that prevents another similarly capable person from doing your job, at least in the next town, if not another country. The obstacles were/are social and political, and the WFH movement shows that. Also, outsourcing is not going anywhere, it's just reduced and converted to nearsourcing due to backlash.

- By contrast, software is a general-purpose abstraction [2]. Databases are a type of software. You can see LLMs [3] as schema-less databases that contain millions of abstractions connected to each other. You can get a UML model or Python code or text by querying the LLM's query engine in a language much more flexible than SQL.

Vibe coding makes it seem like the funny intermediate bullshit is the end result of using LLMs, but it's not. Sure, I agree that LLMs don't make sense to use when a calculator is enough, but I don't see any functional limitations to improving LLMs. Maybe new algorithms or combinations are needed, but no matter how slowly, quality is expected to reach at least human level for the majority of current tasks (on which many jobs depend).

Which leads to my point: we need political, social, philosophical reasons to limit or integrate automation in our civilization, not just watch and hope there's a big enough technical obstacle so we can keep our current jobs.

[1] For example, model-based software engineering is still a growing; slowly, but growing.

[2] So is the organization of mechanical machines or analog computers, but it's faster to reorganize and orchestrate electrical signals.

[3] More precisely, foundation models, because it's far more than natural language processing.

I have a friend who uses Google Maps to find places, then memorizes the route there and closes the app to navigate because he wants to build a better mental map of our city. Meanwhile, I just check the app every five seconds like a dummy, and my hippocampus stays small.

Yeah, but there’s “able to use Excel”, and then there’s “able to use Excel.”

There is a vast skill gap between those with basic Excel, those who are proficient, and those who have mastered it.

As in intermittent user of Excel I fall somewhere in the middle, although I’m probably a master of knowing how to find out how to do what I need with Excel.

The same will be true for agentic development (which is more than just coding).

That probably won’t be necessary in a few years.

Like, yeah, you have the resources right now to boot strap your knowledge of most coding languages. But that is predicated on so many previous skills learn through out your life, adulthood and childhood. Many of which we take for granted. And ultimately AI/LLM's aren't just affecting developers, they are infecting all strata of education. So it is quite possible that we build a society that is entirely dependent on these LLM's to function, because we have offloaded the knowledge from societies collective mind... And getting it back is not as simple as sitting down with a book.

Yes we can but there is a big problem here. We will "learn it again" after something breaks. And the way the world currently functions there might not be a time to react. It is like growing food on industrial scale. We have slowly learned it over the time. If it breaks now with the knowledge gone and we have to learn it again it will end the civilization as we know it.

We've always been able to do that, but that's not the point. There's a reason free software licenses require the "the preferred form of the work for making modifications to it" to be opened.

One of the core tenets is that any user should have the exact same access as the original developers.

Jesus christ.

"The people who wanted everyone to have a home should be happy with the invention of the lockpick. You can just find a nice house and open the lock and move in. Ignore the lockpick company charging essentially whatver they want for lockpicks or how they got accesss to everyones keyfob, or the danger of someone breaking into your house"

That is basically your argument. Like AI is a copyright theft machine, with companies owning the entire stack and being able to take away at will, and comitting crimes like decompiling source code instead of clean room is not a selling point either...

The open source community wants people to upskill, people become tech literate, free solutions that grow organically out of people who care, features the community needs and wants and people having the freedom to modify that code to solve their own circumstances.

Probably even more valuable than code that just worked, because evidently we have enough of that and AI code still has issues.

That said, very sophisticated next word predictors can and sometimes do write good code. It’s amazing some of the things they get right and then can turn around and make the weirdest dumbest mistakes.

It’s a tool. Sometimes it’s the right tool, sometimes it’s not.

Indeed. Sometimes I think the so-called “lower classes” end up functioning more like crops to be farmed by the rich. Think, dollar stores that sell tiny packages of things at worse unit cost, checking account fees, rent-a-center, 15% interest auto loans and store credit cards with 30% interest…

Setting aside the AI point about it, the idea of people becoming essentially irrelevant to the economy is an indictment on society. But I'd argue that the indictment really is towards what constitutes measurement in the economy. Not an indictment on society itself, or technology.

Sure, someone may not spend much money or produce much money, but if they produce scientific research or cultural work that is intangibly valuable it is still valuable regardless of whether economists can point to a metric or not. Same goes for the infinite amounts of contributions to our world from nature: what is the economic value of a garden snake or a beetle? A meaningless question when the economy can only see things in dollars.

Downloading public stuff off the internet with no regard for the creator's wishes or license is bad enough, but we have many people here who defended AI companies seeding models with pirated content.

The internet is a social contract. AI is not the first thing to try and erode it for profit, but it's by far the most aggressive one.

Rather, I don't like that the terms I released my work under aren't being respected. I believe LLMs are derivative works of the pieces they are trained on. I spent more than ten years working on open source code, and now the models that were trained on my GPL'd code are being used to make proprietary code against the terms of the license. I find this reprehensible.

While it wasn't an explicit term of release, generally I did not expect anyone to get any kind of financial value from the blog posts I wrote. I just wrote them for fun & maybe others would find them interesting. Now, LLMs have been trained on my blog posts and are generating financial value for some of the worst human beings on the planet who are using their money to murder, demean, and maim other humans.

I now know that blog posts I wrote for fun are putting money in some sociopath's bank account, and the GPL'd code I wrote is being used to create software to exploit me & other users. If I continue to create things publicly, it will be used against me and other people, and there's nothing I can do to stop it except to stop creating things. It's all very disrespectful & demoralizing.

But if you peel back that layer to the point where you are no longer discussing the code, and just saying "code X that does Y"... how big is X going to get without verifying it? This is a basic, fundamental question that gets deflected by evaluating each case where AI is useful.

When you stop being specific about what the AI is doing, and switch to the general tense, there is a massive and obvious gap that nobody is adequately addressing. I don't think anyone would say that details are irrelevant in the case of life-threatening scenarios, and yet no one is acknowledging where the logical end to this line of thinking goes.

I've vibe coded plenty. I mostly don't look at the crap coming out. Don't want to. When I do I absorb a tiny bit, but not enough to recreate the thing from scratch. I might have a modicum more surface-level knowledge, but I don't have deep understanding and I don't have skills. To the extent that I've fixed or tweaked AI-generated code, it's not been to restructure, rearchitecture, or refactor. If this is all I did day in and day out, my entire skillset would atrophy.

I vividly remember understanding how calculus works after watching some 3blue1brown videos on youtube, but once I looked at some exercises I quickly realized I was not able to solve them.

Similar thing happens with LLMs and programming. Sure I understand the code but I'm not intimately familiar with it like if I programmed it "old school".

So yes, I do learn more but I can't shake the feeling that there is some dunning kruger effect going on. In essence I think that "banging my head against the wall" while learning is a key part of the learning process. Or maybe it's just me :D

How many bytes is a pointer in C? How many bytes is a shared pointer in C++? What does sysctl do? What about fsync?

What is a mutex lock? How is it different from a spin lock?

You want to find the n nearest points to a given point on a 2-D Cartesian plane. Could you write the code to solve that on your own?

Can you answer any of these questions without searching for the answer?

I don't use LLMs and I learn things fine. Always have. For several decades. I care deeply about the underlying code and systems. It annoys me when people say they do and they cannot even understand how the computer works. I'm fine with people having domain-specific knowledge of programming: maybe you've only been interested in web development and scripting DOM elements. But don't pretend that your expertise in that area means you understand how to write an operating system.

Or worse: that it prevents you from learning how to write an operating system.

You can do that without an LLM. There's no royal road. You have to understand the theory, read the books, read the code, write the code, make mistakes, fix mistakes, read papers, talk to other people with more experience than you... and just write code. And rewrite it. And do it all again.

I find the opposite is true: those who use LLM coding exclusively never enjoyed programming to begin with, only learned as much as they needed to, and want the end results.

What I am saying is that once the high quality training data runs out, it will drop in its capabilities pretty fast. That is how I compare it to perpetual motion mechanism scams. In the case of a perpetual motion machine, it appear that it will continue to run indefinitely. That is analogous to the impression that you have now. You feel that this will go on and on for ever, and that is the scam you are falling for.

People yeating a (shitty) Github clone with Claude in a week apparently can't imagine it, but if you know the shit out of Rails, start with a good a boiler plate, and have a good git library, a solo dev can also build a (shitty) Github clone in a week. And they'll be able to take it somewhere, unlike the llm ratsnest that will require increasingly expensive tokens to (frustratingly) modify.

Is the world any better for them existing? The decline of coding and sw engineering skills in humans from outsourcing the practice of it to AI is it worth it and sustainable long term?

That ship has sailed. The revolution is happening. We live in a new reality now, one where we're still trying to figure out what rules should even be.

And there will be winners and losers, and copyright and patent law will be modified in an attempt to tame the chaos, with mixed results because of all of the powerful players on both ends.

You can live on the front of it for high risk/reward, or at the back for safety. But either way, you're going to exist in this new reality and you need to decide your risk appetite.

These people have always been doing this. Starting in the 90s it was outsourcing programming jobs, they were right then, they got more work for less money and you could have less expertise on staff farming out work somewhere else that was cheaper. You also got worse results sometimes. So it goes.

LLMs are making people more powerful and sucking a lot of income off to the people who provide them. Yup. It makes idiot shysters more powerful just the same as it makes experts more powerful.

People are acting like the software engineering industry is full of fine artistry building the finest bespoke tools instead of duct taping rocks to sticks. I'm sorry but there is a tremendous amount of crap out there by people who barely know what they're doing.

Yes new technology empowers idiots, but it also empowers smart people and if you use it well it'll lead to more quality. Yes you're going to have the same problems you had before of someone doing something cheaply competing with someone trying to be careful to build something well. There also will continue to be idiots spouting off about it.

Nothing changed but the tools got more powerful and people are whining complaining about this change this time ruining everything. Like they always have forever.

Oh, no doubt. I'm certain that that is because

> Kubrick was criticizing the false morality of the entire adventure, mixed with common bureaucratic fuckups in an unaccountable environment, with tragic results.

relying on a "intro to cinema criticism"-level summary of the themes of the entire work almost always leaves you entirely ignorant of the specific themes and characterizations that are explored in a particular scene.

Watch the scene with your actual eyes and ears, maybe a couple of times. Ruminate on it and consider what aspects of your statements and their surrounding context might cause someone to be reminded of it.

It seems they were correct not to invest in your skills.

I've worked for six companies over almost 20 years. The majority invested in my skills, and I hope that investment has paid off for them!

I can't understand what people are looking for when they talk about lack of investment into training for engineers. It's not the kind of job where someone can train you. It's like an executive complaining they aren't trained. You're the one who's supposed to be coming up with answers and making decisions. You need to spend time on self-motivated learning/discovering how to better do your work. Every company I've been at big or small assumes that's part of the job.

In US you go to college for 4-5 years and pay $50k per year. Or more.

You pay to learn. A lot of money, a lot of time.

Then you get a job, where the idea is that you get paid for doing work and you expect the employer to do what?

You seem to expect that not only you won't be doing the things you're being paid to do but the employer will pay for your education on company's time.

How many weeks per year of time off do you expect to get from a company?

You'll either say a reasonable number, like 1 or 2, which is insignificant to the time you supposedly spent learnings (5 years). You just spend 250 weeks supposedly learning but 1 or 2 weeks a year is supposed to make a difference?

Or you'll say unreasonable number (anything above 2 weeks) because employment is not free education.

With 35 companies, that would be around 1-2 years per company on average if you are retired or near retirement. I doubt any company is seriously investing in a worker who would likely be gone the next year. Getting lip service seems already good deal at that point.

There is no "conservation of fallacy" law (bad data must conserve it's level of bad), so I'm struggling to connect the dots on the analogy, unless I ignore the fact that training on synthetic data works, is being used, and the models are getting better.

At my own firm, we generally have a rule we do almost everything through metaprogramming.

Yes it is. What do you expect, formal verification of a toy GUI library? Get real.

> and isn't going to fail due to some obscure or unforessen corner case.

That's called "a bug", they get fixed when they're found. This isn't aerospace software, failure is not only an option, it's an expected part of the process.

> You need actual proof that's driven by the code's overall structure.

I literally don't.

> Humans do this at least informally when they code, AI's can't do that with any reliability

Sounds like a borderline theological argument. Coding agents one-shot problems a lot more often than I ever did. Results are what matters, demonstrable results.

So? We didn't prove human code "isn't going to fail due to some obscure or unforessen corner case" either (aside the tiny niche of formal verification).

So from that aspect it's quite similar.

>so most coding agents simply work their way iteratively to get their test results to pass. That's not a robust methodology.

You seem to imply they do some sort of random iteration until the tests pass, which is not the case. Usually they can see the test failing, and describe the issue exactly in the way a human programmer would, then fix it.

The explosion of stacks means it’s hard to keep everything in your head at once. Lookup is routine but will sink you as a candidate.

Personally not great under the gun in adversarial interviews, so my extensive self learning is not well highlighted.

LLM hallucinating is not an edge case. It is how they generate output 100% time. Mainstream media only calls it "hallucination" when the output is wrong, but from the point of view of a LLM, it is working exactly it is supposed to....

The core concepts covered by a good CS curriculum haven't really changed. Specific languages were never the focus.

If I write code for medical devices I might not tolerate even one AI-induced issue. If I write glorified web apps, I could tolerate dozens of them as long as it still helps get stuff done faster when it works.

Your car fails ocassionally and needs service. If most of the time it gets you there, enough that you find it worth it over NOT having a car or buying a new one, then it's useful.

And unlike the car, you can do whatever review/verification/testing of the resulting AI code before you deploy it. And the code failing wont kill you or others (if you write trading software, medical devices firmware, or airplane code, you can always not use it).

You don't even need to let it rip on your system, can use it with user confirmation for any action or have it go in a sandbox.