We’re about to learn a painful lesson about delayed gratification in software engineering.
New data from China, 26,811 students tracked January 2023 through June 2025. Students using AI for homework saw their scores jump 20 percent. Completion time dropped nearly half. They aced the assignments.
Then exam season came. Those same students scored 20 to 40 percent worse when they couldn’t use the tool.
The homework phase is over. The exam phase is coming.
We’re doing this in software right now. Vibe coding feels incredible. Features ship fast. Nobody’s asking what happens in Month 18 when the original dev has left and nobody understands the codebase.
Commercial pilots fly with autopilot for most of every flight. They’re required to maintain manual flying proficiency regardless. If the system fails mid-air and the pilot can’t take over, people die.
Most teams using AI right now have forgotten how to fly manually. They’ve become passengers in their own systems. The autopilot flies, nobody checks instruments, and the first sign of trouble will be a breach notice or outage.
Three rules:
- Command the mission. Define architecture before prompting. Ambiguity kills in code and in flight. Delegate selectively. Offload mechanical work. Keep design and security reviews human. Verify everything. Audit before production.
- Never trust the automation without checking instruments.
- Quick wins feel good. Sustainable engineering feels boring. Boring keeps systems standing.
Organisations surviving the next two years won’t ship the fastest. They’ll be the ones who remember how to fly without the aids.
people insisting that you actually be skilled, independently of your tools, doesn’t make them Luddites. Rather, being unable to do so makes you a phony.
Off-topic.
having ai do your homework for you is not a flex
Finding ways to save effort is smart.
Finding ways to trade quality for convenience isn’t. In the case of education, given its fundamental importance, quality is paramount. A mentor of mine phrased it as “learn to do it right first, then learn where you can get away with being sloppy”. Education is the “learn to do it right” part.
In the case of programming, figuring out where you can be sloppy (and how sloppy) is a matter of experience. A junior developer doesn’t have that experience. A senior developer might, but in my impression they tend to be way less excitable and preachy about using AI.
Offloading a homework during brain development to watch some TikTok
This isn’t programmer humor… post to the right comm like fuck_ai@lemmy.world
It’s funny watching this type of bellyaching play out like a loop over history.
People went through this EXACT same bellyaching when compilers first started showing up. The machine coders considered themselves superior and their skills indispensable. Now those people are extinct and modern people consider their compiler skills to be elite, not realizing they’re using the baby mode that people railed against in the past.
It turns out that you, in fact, don’t need to know what you don’t need to know, for the most part.
Understanding the layers of abstraction down to the metal is still a useful way of developing an instinct for how compilers, interpreters, languages, and algorithms etc. work and what is possible. If you ever truly need to optimize something you’ll end up descending those layers, it’s why C has inline assembly and with RAMageddon upon us optimization may well return to being a valued skill.
Which is to say you don’t need to know what you don’t need to know, until you do, and you’ll be better anyway if you can.
Did anyone do studies on the homework and exam scores of people using compilers vs people not using compilers?
Did anyone establish that people who used compilers are measurably dumber than the people who didn’t?
No?
Well then obviously it’s not the same situation, now is it?
Dont expect the pro-AI crowd to have any reasoning capacity. The only argument they have for AI is “I’m lazy”.
Yes they did. Why did you assume they didn’t?
https://link.springer.com/article/10.1007/s40692-018-0103-3
It is mostly between students who used compilers and those who did it with pen and paper.
It did not have a significant impact.
spoiler
Easily found this study with the help of Duck.ai, try it yourself next time. Or try to wade through Googles SEO riddled bullshit if you care so much.
It did not have a significant impact.
Then this is obviously different, because we are seeing a significant impact on test scores. Students that use AI test poorly.
…
I’m going to acknowledge that you responded so that, when I don’t continue this conversation, you’ll know that it wasn’t because I decided to abandon my position.
You could say your response did not have a significant impact.
I agree with everything except for vibe coding feeling great.
Am I the only one who gets incredibly anxious relying on AI to code? I still ask it for code when I really just want to move on from a problem but it always feels like voluntarily putting mold in my floorboards.
I try vibe coding from time to time and it’s a mixed bag. When it works it works but then there’s suddenly just code there. It’s like when a colleague implements a feature in a project with multiple devs but since it’s just your personal project you suddenly got put in the code reviewer chair.
When I write code I reason about all the small decisions but when the agent takes over I have to figure out step by step why decisions were made.
I’m still not sold on coding agents and vibecoding but it’s getting better and more usable.
The only downside is that a agent doing its thing is now seen as downtime where you could just prompt another agent and work on several projects simultaneously. If anyone ever tells you vibecoding is good because you can work in parallel RUNI try vibe coding from time to time and it’s a mixed bag. When it works it works but then there’s suddenly just code there. It’s like when a colleague implements a feature in a project with multiple devs but since it’s just your personal project you suddenly got put in the code reviewer chair.When I write code I reason about all the small decisions but when the agent takes over I have to figure out step by step why decisions were made.I’m still not sold on coding agents and vibecoding but it’s getting better and more usable.The only downside is that a agent doing its thing is now seen as downtime where you could just prompt another agent and work on several projects simultaneously.If anyone ever tells you vibecoding is goodbecause you can work in parallelRUN~~I try vibe coding from time to time and it’s a mixed bag. When it works it works but then there’s suddenly just code there. It’s like when a colleague implements a feature in a project with multiple devs but since it’s just your personal project you suddenly got put in the code reviewer chair.
When I write code I reason about all the small decisions but when the agent takes over I have to figure out step by step why decisions were made.
I’m still not sold on coding agents and vibecoding but it’s getting better and more usable.
The only downside is that a agent doing its thing is now seen as downtime where you could just prompt another agent and work on several projects simultaneously.~~ If anyone ever tells you vibecoding is goodbecause you can work in parallelRUN
I only use it to solve specific problems when I can’t find the solution elsewhere. Then I spend the time to understand and rewrite the code myself.
It’s the same workflow as using Stack Overflow, etc. You can’t just copy/paste solutions.
I think it sounds really weird, too. I don’t like the sound of that at all. I’m not a pro though.
I’ll admit I enjoy carrying on little tutoring sessions with my GPU though. “How might I approach something like that?” “Can you explain this concept a bit differently?”
But I try to do all the solid brain work myself. Letting the machine write the code for me feels…kinda gross.
I actually think it’s awesome that it understands coding convention and codebases and stuff well enough. Saves a lot of time digging through the wreckage of search engines…
But I don’t appreciate that a lot of its “skill” is pulled from the efforts of uncompensated coders.
they were absolutely not right… the modern world of plentiful clothing simply wouldn’t be possible without industrial clothing machinery (and i’m not talking about fast fashion and waste - though industrial clothing also makes those things possible, i think that’s an outcome of the plenty rather than an inevitable outcome of industrialised clothing)
artisans don’t magically make better clothing… in fact, modern machinery can and does produce much higher quality, complex clothing than a human alone would, and in much higher volumes
they had a moment when they had a point, when the machinery just wasn’t very good (and of course the child labour concerns)
clothing quality on the modern era comes down to choices far far more than the skill of the person making the clothing… artisans are still able to make cost cutting decisions
the point we should take away from the luddites is more about retraining than about their core point… this applies to coal miners and the green transition, and will at some point in the future apply to the logistics industry when driverless trucks become reliable: we can’t just toss an entire industry out of work and expect them to be okay with it (or for that matter expect the economy to absorb them)… but it’s a much better world when fewer people are required to achieve the same output
You could have saved a lot of time and just said you’re unfamiliar with their argument.
What do you think luddites believed and did?..
the luddites were taylors and the like fighting against being replaced by machines for various reasons, including child labour, low wages for machine operators, and low quality product
imo child labour laws are the way to solve the first problem: that’s, imo, unrelated to industrialisation/mechanisation
lower wages are a product of lowering the barrier to entry: when anyone can do the same job, that is not a bad thing… it’s sad that an industry of people are pushed out of their profession, but we’d never say the same of coal: coal miners should realise that their industry is not going to exist any more, and retrain,… i have empathy for them, which is why we need to provide social programs to cover industries that get made redundant for any reason, but that’s not a reason to deny the rest of humanity the plenty that inevitably comes from industrialisation
and low quality product is only really an issue at the very start of industrialisation… i guarantee these days we can make higher quality clothing in 100x the quantity than we can with artisans and hand stitching… machines always get better, but only if there’s effort put into using them
Ok, so luddism was a grassroots movement so there obviously were different aspects and reasons for their actions, however for most luddites what they were protesting were not “being replaced by machines” (they themselves were mostly skilled laborers operating machines already) but the awful conditions for labor that were exacerbated when new types of machinery became available. They used strikes and capital destruction as two inter-reinforcing methods to strengthen their negotiation position with owners, not because they thought that destroying those machines would somehow save their old jobs and way of life.
The luddites you are disagreeing with probably existed but they were a minority and they were not who made the movement notable and dangerous to the bourgeois.
imo child labour laws are the way to solve the first problem: that’s, imo, unrelated to industrialisation/mechanisation
It’s not unrelated, industrialization has a clear tendency to concentrate the means of production in the hands of the rich; a weaver/taylor can own a 16th century weaving apparatus, they can’t own a 19th century weaving plant unless we get into cooperatives, which are pretty hard to organize compared to buying a loom for yourself.
It’s like you didn’t read the article.
the “article” that doesn’t mention luddites at all until a comment at the end that kinda agrees with what i’m saying or the wikipedia article that points out the luddites issues being about labour and generally being replaced by machines? i know very well the nuance of the luddite movement and their main good points, as i said, were about labour issues (mostly solved with labour laws on modern society) and the takeaway isn’t about technology but about how to deal with technology replacing people’s jobs
replacing artisans with machines that do a good enough or better job is a good thing, as painful as it is… it means more people get more of the thing… artisans instead of machines is a waste… humans are the most inefficient general machine we have… having a human make clothing is a cost on society
The point is that the Luddites (most of them anyway) weren’t against mechanization at all, it was all about the specific conditions under which it happened, i.e. rich people owned the means of production and until maybe late 19th century, living conditions for the working class were absolutely appalling and a clear downgrade over what they had before. 16 hour shifts at poverty wages are not necessary for industrialization, yet that’s usually how it happened.
It was not really about the machinery, or the quality of the work. It was about the rights of the common person, their livelihood, and their very lives. The reason the Luddites are viewed disparagingly is purely because they lost, and history always favours the victors.
You have to remember that this all took place in a time where workers like you and I had no real rights of our own. There was no universal suffrage, only those with capital had a say in matters of government. So when machines were brought in to your workplace, and the powers that be proclaimed that a large bunch of us would be redundant, we despaired. This was the way we scraped by, it’s how we fed ourselves and our families.
So what did they end up doing? They protested. They sabotaged the machines to buy us more time, in some cases they smashed them, in other cases they removed and hid some parts; each day a machine wasn’t operational was another day that they got paid their wages, another day they’d survive.
Malcolm I. Thomis argued in his 1970 history The Luddites that machine-breaking was one of the very few tactics that workers could use to increase pressure on employers, undermine lower-paid competing workers, and create solidarity among workers. “These attacks on machines did not imply any necessary hostility to machinery as such; machinery was just a conveniently exposed target against which an attack could be made.” ~src
The Luddites specifically targeted the machines, because their goal wasn’t to hurt people, but rather to have their voices heard. This was really the only avenue they had any power to make a difference.
The powers that be obviously weren’t happy about this, they’d spent money on expensive machinery, and now the common rabble was sabotaging and destroying their property. So they drafted laws, like the destruction of stocking frames etc. act of 1812 which classed meddling with the machinery, or the produced goods a felony punishable by death. You can read the act here.
May it therefore please Your Majesty that it may be enacted; […] That if any Person or Persons shall, by Day or by Night, enter by Force into any House, Shop or Place, with an Intent to cut or destroy any Framework knitted Pieces […] or with an Intent to break or destroy any Frame, Machine, Engine, Tool, Instrument or Utensil, used in and for the working and making of any such Framework knitted Pieces […] every Offender being thereof lawfully convicted shall be adjudged guilty of Felony, and shall suffer Death, as in cases of Felony without Benefit of Clergy.
And people were killed for this. From an archived page on Bolton Council’s website.
Job Fletcher aged 34, James Smith aged 31, Thomas Kerfoot aged 26 and Abraham Charison aged 16, were sentenced to death and hanged at Lancaster. Their fate was shared by three men and a woman who had been charged with “riotous assembly” in Manchester and with damage to property and stealing food (mostly potatoes).
This is ultimately what ended the Luddite movement. The unfeeling machinery of capitalism churned ever onward, the ruling class sent out the military to quell the riots, and eventually when enough workers (including children) had died for the cause without making any marked difference, they gave up the fight.
The Luddites were absolutely right in terms of rights of the individual workers, and that’s a lesson we still haven’t learned today. It’s not unreasonable for an industry to undergo large operative shifts, but the people affected negatively by this should still be cared for. It’s not reasonable to throw a person to the wayside and watch them die just because a machine replaced them.
I agree with you in so far as the luddites were not enlightened ideological opponents to technology.
While it’s true that it would be foolish to disregard history i don’t think the loom is analogous to generative AI, and the luddites aren’t really illuminating here.
The evidence thus far is that the current generation of AI is an incremental improvement in productivity in the vast majority of industries.
the mechanical loom isn’t analogous to LLMs exactly, but the current generation of AI also includes things like self driving vehicles, which (whilst not ready) is, imo, set to make a huge portion of the logistics industry redundant in the next 20-30 years if not sooner, and the logistics industry is enormous
Maybe, but maybe not.
All we know for sure is that we can’t do it reliably yet, and that it’s extraordinarily difficult.
You think we should all be hand-weaving textiles because power looms took jobs away? 🤔
No, I think technology should serve the people, not the rich people who own the means of production. I suggest you actually read the article I linked.
Oh, I have read it.
Luddites were strongly motivated by loss of jobs. The article refers to this, and you can find plenty of examples of pamphlets and letters about this:
http://faculty.humanities.uci.edu/bjbecker/SpinningWeb/week8d.html (“We know that it have been mentioned to our great men and Ministers in Parliament by them that have Factorys how many poor they employ, forgetting at the same time how many more they would employ were they to have it done by hand as they used to do.”)
You can characterise this as “technology should serve the common man, not the rich people” through a modern lens of class struggle, but the clear motivation at the time was simply loss of employment and the problems that brought. If they had a more complex understanding like I think you’re voicing, I think you would see their ire directed elsewhere rather than destroying the machines.
The vilification of the Luddites as cantankerous tech haters is a really good example of how malicious falsehoods can succeed, I think. I’d guess that most English speakers who know the word would define Luddite as “someone who hates technology”, and I think it resonates on some level because we all hate technology some of the time. The fact that Luddites didn’t indiscriminately hate technology, they just destroyed the means by which their oppressors oppressed them, is handily swept aside. And I never even questioned that narrative on Luddites until I happened to read up on them.
It’s sneaky, because before then “Luddite” didn’t feel like an important or politically charged term at all. It was simply a slang word for people who grump about technology. Calling people haters just short-circuits any examination of the so-called haters’ reasons. It’s exactly what people say about terrorists, except instead of technology its freedom. They just hate freedom. I wonder how many people have “terrorist = freedom hater” embedded so deeply they don’t even think about it.
One persons terrorist is another persons freedom fighter
The luddites chose the wrong target. It was not the machines that were the problem. It was the Capital.
This is kind of like the “you won’t have a calculator with you all the time” argument by your 8th grade math teacher in 2003, except instead of making yourself dependent on a little solar powered device (that you could have with you all the time if you really wanted to, even before smartphones) you’re becoming dependent on a subscription service offered by a trillion dollar company that can increase the price tenfold at will, or cut you from the platform entirely, stripping you of all your professional expertise at once.
This is kind of like the “you won’t have a calculator with you all the time” argument by your 8th grade math teacher in 2003
Which is grand, given we’ve had researchers agreeing effectively incorporating calculators into math education improves everyone’s ability to do math without calculators - Since the 90s
There’s pretty good arguments to include calculators from a really young age, to improve the understanding of numbers
There is no good argument for including calculators before the pupils haven’t mastered basic calculations in their head, there are good arguments against it.
ya very hard to do proper math applications even with a calculator if you lack the fundamental understanding of how it works.
You’re ending up with a larger group of pupils “mastering” basic calculations through counting, when you remove the calculator as a tool for learning. Using the strategy of “counting all”, is one of the clearest signs a 1st grade pupil will be behind their peers in 4th grade.
Broken calculator (just search for it), is one way to include calculators in a didactic way. But using calculators in general, improves a kids ability to estimate results - Which is an ability that helps anyone out tremendously, as it’s giving you a clear idea if something went completely wrong in a calculation
A “broken calculator” isn’t a calculator. It requires you to calculate in your head to be effective, which is exactly what I was talking about.
First you need to solidify this ability, before it makes sense to introduce reliance on calculators.
It’s still a calculator, it just misses some features. It’s one didactical way to include calculators.
It is not a functional calculator and can’t be used as such. Learning how to use a simple calculator doesn’t require much training or special skills, that children of that age wouldn’t have already aquired by other means anyway. The important skill broken calculators learn is to analyze the problem and predict solutions in your head.
You could achieve something similar by giving pupils just a piece of paper and the numbers and signs they are allowed to use. The calculator part makes checking easier, yes. That’s about it.
To me, doing math without a calculator is like trying to do carpentry without a tape measure. It’s possible, but way harder and far less accurate for no real benefit. Back in the day, people absolutely would use abaci and other calculation aids while learning math. Calculators are good actually, and always have been.
If you need a calculator for the easiest quick guesstimates, you are handicapped. If you start from day one with offloading every calculation to a calculator, you will be like that.
I dont think so. If(here is where my argument fails for most people cause i got really good education) your teacher thought you math properly tho point isnt the calculations but that you understand the logic. With ai the problem is the same with as a calculator that just spits out derivatives, graphs, etc by just typing in a formula. The reason you have to understand those is to be able to build upon it.
100% agreed. My teacher said that he taught us tools, how they worked and how to use them, in order for us to apply them in new ways. Even with a calculator you have to understand the underlaying logic to actually do something. Don’t know basic mathematics? Good luck using a calculator.
I think its both. you have to understand it to be able to build upon it, but it’s also no nearly as readily available as pocket calculators, and they require much more energy that too. It’s not as portable as a calculator.
Local models on a gaming PC are already a viable replacement for a Claude subscription, and are rapidly improving, so the idea that we will have powerful open models running on our phones isn’t at all far-fetched. It’s exactly the same situation as with a calculator like you said.
I wouldn’t call 48GB of VRAM a normal gaming PC, and even with that memory you’re not getting claude intelligence or performance. It’s still much more viable than ever before though. Are you running local models with limited vram with good results?
I have a 7900 XTX with 24GB of VRAM where I am running Qwen 3.8 27B at 4 but quant with 200k context. I traded in my RTX 3070 and got it for around $700 recently. That model performs pretty similarly to Claude Sonnet 5 in performance for coding and certain other tasks and it “feels” similar to Sonnet 5 that I use as a daily driver at work. I was running Qwen 3.6 35B-A3B on the 3070 before and I still run it on my server with a 4060 and 32GB of RAM, and that model is more like Claude Haiku.
I expect 3.8 35B-A3B should be released pretty soon and provide a nice bump in performance.
I regularly follow this guy’s YouTube channel, and his latest video is about running a 177B model on his RTX 3060 via SSD offloading and getting Opus-like performance for certain tasks: https://m.youtube.com/watch?v=IH8XmxiwliQ.
Supposedly, open weight models that run in a data center are like 4 months behind the frontier at this point, and what can run on a gaming PC is progressing rapidly as well while the exponential gains at the frontier have largely turned into incremental gains at this point.
This is great info! I’ve been using OpenCode Go because I only have 16GB to work with and their limits are pretty generous. Looking forward to tiny, competent local models. Thanks o7
The 0.4.0 release of llama.cpp just added the n-cpu-ffn flag for offloading weights for dense models to the CPU to complement the existing n-cpu-moe flag for MoE models. If you have a 16GB GPU and some extra RAM to spare, you might even be able to run Qwen 3.8 27B at a usable speed after some experimentation. I don’t own a 16GB card, so I haven’t tested it myself, and it might not work as well as I am imagining.
I’m going to stick with OpenCode Go, but the available models keep getting more expensive and the DeepSeek peak hours is annoying to deal with
Maybe this is good enough for small projects but if you deal with a large codebase the small context starts be becoming a problem. In my day job I frequently keep maxing out the 1M context of Opus and Fable when I am dealing with any mildly complex task. I can’t imagine how a fully local setup could even start being viable on my 16 GB GPU. And yes I know about RAM offloading and it is really damn slow, at least from my own tests.
This might be the case for an absolutely massive codebase where code files are also huge. Even with Claude, though, you’re supposed to compact regularly well before you hit 1M, or you’re otherwise paying a higher price for the oversized context. That generally means breaking down the work into smaller tasks, which is a useful practice anyway. I also find it useful to have the agent write any detailed info that will help needed later to a markdown file that can be re-read after compaction and r in a new session when needed.
I’m mostly working with smaller, personal codebases locally, though. With my 24GB GPU, I hit a hard wall with my configured 200k context and have to compact in OpenCode to continue, which I don’t mind. I do have to micromanage context to a higher degree than with Claude, though, since Anthropic will gladly charge a higher price when your context gets large instead of cutting you off.
I also find it useful to have the agent write any detailed info that will help needed later to a markdown file that can be re-read after compaction and r in a new session when needed.
Yes, I do that a ton. And yes, I am aware of the additional cost for when the context exceeds 150K. Still though, I try to avoid compacting too much because I found that sometimes the agent starts chasing its own tail. Also, the more of the codebase you can fit in the context the more you benefit from the cache. If you are doing a large refactoring job on a legacy codebase it really helps.
This is kind of like the “you won’t have a calculator with you all the time” argument
It’s not even that! Students without a calculator don’t see their test scores crater, the work just takes longer.
Also calculator is still prohibited in schools in many countries. Like mine. And I’m forever grateful for mental math skills I’ve gotten. Teaching math like that has it’s own downsides, but mental math is a soft skill that helps in life.
and also the calculator is actively destroying the planet.
And tells you it is your girlfriend and to shoot up your school.
you’re becoming dependent on a subscription service offered by a trillion dollar company that can increase the price tenfold at will, or cut you from the platform entirely
with local open weight models that is no longer an argument tbh
Not every software company is a game developer, and even at home, not every programmer plays games on their PC that require a powerful GPU. If everyone working on, for example, business software all of a sudden needs a gaming PC that will be constantly running an AI model, that will greatly increase costs, both in terms of procurement of equipment and electricity. An increase in demand for powerful GPUs in fields that traditionally had no need for them isn’t exactly going to improve the hardware cost situation either.
Whether you run the model locally or you leave it to a company, someone is going to have to pay the cost.
Okay, well you’re on a forum filled with nerds. The average AI user is asking ChatGPT or Claude or whatever the fuck. I garun-fucking-tee you they do not have the knowledge of local models or the capability to set one up. Like genuinely most Americans are fucking stupid.
The “open-weight models” argument just a fallacy IMHO, frontier models would require a pretty strong AI PC, not something that GTX1050 you put away as a backup could handle. The “just use smaller models” argument just gives leeway to just not using AI and using more classical methods of coding - use of dependencies, use of code generators, use of semantic search engines (can someone suggest me one?), etc. LLMs don’t do anything particularly new, they’re just mimic how humans talk.
Who can afford the hardware to run an open weight model? We aren’t all earning enough to afford high end NVIDIA cards (when they’re even available).
I’ve done it at my job.
lucky for you to have your boss paid for it. but it’s likely not yours, but your company owns it, and you have access as long as you work there. after that, you can say goodbye to your “professional expertise”
this is completely different from the calculator that can run off its puny solar panel
If you consider what companies pay for the subscription you will see that the hardware prices aren’t really the issue here.
You may be overestimating the hardware requirements for current open weights. I am running Qwen3.8-27b with 52.000 tokens context on a RX 7900 XTX from 2022 with 15 - 30 tokens / second. Sure, it was a high end card back then but for a graphics card today it’s quite affordable when you’re looking for a used one. Also it’s not blazingly fast, but it gets the job done.
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“Just run it local, you can use cheap hardware”
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is running it on a $1200 card and is still struggling to get it done quickly
Keep on sucking up that slop, I’m sure paying a company to do your thinking for you will pay off in the end, as we’ve been seeing.
When I bought that card this year I payed significantly less than you’re suggesting. That’s still a lot of money but it’s not more than many gamers where willing to pay for their gpus way, way before ramageddon. Of course you can’t run open weights on a potato but you also don’t need a $4000 gpu to do so.
As for the rest of your comment? What? 🤷
How much did you pay?
I spent $70 on a “new” Aisurix amd radeon 580 2048 SP graphics card earlier this year, but it was a sidegrade more than an upgrade to the Nvidia GTX 980 i had before (which had declining Linux support).
Modern graphics cards seem to be very expensive compared to how much it used to cost to be a few years behind the cutting edge.
I payed around 700 € used, but in turn I sold my previous GPU for ~ 400 € and I got a significant performance upgrade for that money.
Solarpunk scoffing at anything but maximum efficiency for minimum price is deeply funny.
They used a computer they already own and made up for the difference with simple patience… what a corporate whore, right? How dare they want their personal machine to do private magic unless the numbers say infinite growth forever.
Im not scoffing at efficiency, my issue is with the technology being paid for - the one that’s actively being used to ruin the planet, destroying old single edition books because they’re untainted by the slop bein pushed out, not to mention how it’s being used to spread misinformation, propaganda, mass surveillance, security threat level code, scams, and of course deepfakes of everyone from children to politicians.
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Your graphics card cost more than my entire computer lmao
Sorry, I didn’t want to come across as detached. It’s true that my hardware budget increased in the last ~ 15 years but even then I would have considered 700 € (that’s what I paid for my card) a very tight budget for a moderate gaming pc in my country.
There’s models that run on your phone.
“You won’t have a tiny pocket computer with you all the time” really is the exact same argument with different specs. And frankly I’m a lot more likely to do math without a computer than write code without a computer.
“You won’t have a tiny pocket computer with you all the time”
likely true in 20 years
yea no
calculators are deterministic
come back to me when ai isn’t fucking wrong silently
that can increase the price tenfold at will
That will have to increase the price ten fold to stop bleeding billions of dollars every month.
The American taxpayers will save them, whether they want to or not.
You can’t bail them out, they will still be losing money. It’s not like banks.
The play now seems to be that they will offload the bags on retirement funds and US 401k accounts. The ECB already issued a warning because of this.
I’m curious if the repeated bailouts will cause an adverse selection effect - the people getting bailed out gradually become the last dollar users.
Vibe coding at work lets you slack off and then secure your job when shit inevitably hits the fan and you have to untangle the mess. Seems like a win-win to me, assuming you know how to program to do the untangling part. The only bad part is not having any satisfaction in doing the job, but there was enough corporate bullshit in place all along to ensure that regardless.
Whether or not you can pass an exam barely means anything IRL
Compilers would look the same. You give some people a tool that turns fiddly low-level repetition into relatively painless double-checking. Then you yank that tool away, and oh no, they’re not as good at the fiddly low-level repetition.
What matters is - are these students worse-off, with the tool? It’s not going away. Foreverafter, a couple gigs of linear algebra will turn your to-do list into an actual running project. We have to ask if teaching the fiddly low-level repetition is the point… or just a means to an end.
You can scoff that compilers are objectively better, but they weren’t! Sometimes they still aren’t! We were teaching kids to consider inline assembly well into the Windows Vista era. Even now, compilers with decades of active development can have bizarre corner cases, which any hardened bit-banger of machine code would never write. But they’re all good enough that plaintext assembly has become an arcane third-year topic, and hexadecimal machine code is the realm of bare-metal maniacs.
Teaching math, kids have to know what numbers are, and how base ten works, and why the calculator says 11-3=8. But as you go up to college math it matters a lot less whether people can do shit in their heads… or even remember how. Open-book and open-calculator exams are still fuckin’ hard. They’re just hard because you’re trying to apply some obscure proof to a rat’s-nest of swooping symbols, instead of because you’re worried about having enough time to write out long division to umpteen places. The latter can be sufficiently approximated with two wooden sticks. We can assume anyone doing math professionally has two sticks. Continuously! As a given, for their job. Probably at home as well.
Teaching programming, you have to break people a certain way. No gentle and charming syntax can disguise the mechanized nastiness of what code is. Whatever semi-readable text you’re looking at will be squinched through a flake of tortured sand in a bazillionth of a second. But only after getting transformed at least two times in processes you kinda have to trust will be computationally equivalent, unless you want to minor in a branch of mathematics haunted by Stephen Wolfram. Ultimately there is a shockingly small state machine designed to trick you into off-by-one errors.
But once people can knock out fizzbuzz on a paper 6502… they’ve kinda got it. They’ve been inculcated. They will soon apply arcane patterns to a rat’s-nest of obtuse variable names. Ssshould they have to do that by hand? They’re not doing the assembly by hand. They’re not even looking at the assembly. They might never need to think about assembly again. So long as they’re playing spot-the-bollocks for a flurry of pull requests, that’s arguably a more useful skill than writing clean toy code from scratch. Especially in pen and ink.
The main problem with AI is that it’s pretending to understand more than it actually does right now. It can’t do software architecture. It can’t really write maintainable code without a lot of re-prompting and corrections. And yet it will happily make a bunch of those decisions for you when you ask it to write you an app.
Compilers are well-defined tools. “Human-readable” code goes in, “machine-readable” code comes out, according to some spec somewhere. Yes, compilers can be nondeterministic and they do a lot of weird stuff sometimes and they choose the wrong approach often, so some developers still need to understand assembly and CPU cache and SIMD and other features of the hardware our code runs on. At the very least every developer needs to understand the performance tradeoffs they’re making, or we end up with a JS-based start menu in Win11. But at least compilers have a well-defined class of inputs and outputs.
For AI these issues are amplified a lot. They are non-deterministic and unbounded in what layer of software they operate on or produce. I’d argue every developer who uses AI needs to understand software architecture, approaches to software development, and actually read and understand the code that the AI produced, at a minimum. Otherwise the whole industry will become saturated with and built on top of code no-one understands or can maintain, and it will literally collapse in on itself at some point. Carefully reviewed, selected, maintained code has always been precious, it will become a golden nugget in a sea of pig manure.
or we end up with a JS-based start menu in Win11
It can’t really write maintainable code without a lot of re-prompting and corrections.
Which is a skillset being learned. One which users are presumably better at than non-users, since they’re practicing it. If the chatbot-that-codes Just Worked, there’d be nothing to discuss; we could consider human coding successfully completed. The people who don’t move up to proper computer science can get on with whatever they wanted software for. We only teach them all of this because they’ve got shit to do, and up until now, it’s been really really hard. Like if beginner astronomy meant telescope engineering.
Already the key complaint has become “maintainability.” That’s quite a high-level criticism. When I sass specific compilers, it’s for using register-juggling macros that could have been one hardware instruction… not for adding a feature from a one-sentence description, but in a way that will complicate any future refactor. Or would, if refactoring was not also something you can tell the chatbot to do.
Compiler developers are a hardened core of ultranerds. I couldn’t do it above a toy level. If I needed to understand how they work, in detail, then I would be in trouble. Thankfully it is sufficient to abstract all of their work into ‘C goes in ARM comes out.’ Or at least to mumble about intermediate representations and distract people with Godbolt before running away. Sure, ‘add a button above the widget’ is more pluripotent than a K&R-standard Hello World, but even the foundation you celebrate is layer upon layer of Don’t Worry About It.
AI coding right now is a blunt instrument. Those often suffice. And this one can already be used to remove layers. To obviate a fat framework. To translate to a faster language. To golf. Or it could format your hard drive if a website tells it to, IDFK. It is a higher class of footgun. We take those.
I guess exams in school are supposed to represent real life???
Real life is open book. Exams are horseshit.I kinda agree. Although, I think the logic is nuanced. There is value in being able to know your stuff when your advanced tools and reference materials aren’t readily available or have failed.
… But then again I’m sure most of these kids aren’t going to be needing to emergency land a spacecraft by doing complex math from their head, Apollo 13 style… so… :p
But the cynic in me agrees “exams are horseshit.” It feels like they’re often used as a filter to keep the degree/cert/whatever “valuable.”
And the post is written with fucking AI lmao
I know that when i started using AI i got over blocks much faster. A system from design to implementation that use to take a week now only takes a few hours with most of that is testing and reviewing the code.
I don’t use agents to test and review code btw because i still want to know what’s going on but my colleagues are definitely using agents to build test large codebases. Im sorry but the truth is AI has changed how we build products in the same way intellisense and jet brains did but on a scale i haven’t seen in my lifetime.
Agreed. If you don’t use AI in coding you are not competitive with someone who does. It really is that simple. You won’t be able to keep up, your bosses will see, you will get fired and that’s that.
Even if the quality you deliver without AI is better, quality is not everything. Time is always a factor and AI beates you ten times over. The rest is sane flows with lot’s of testing etc.
Haha, nah. If you’re generally faster with AI assistance it just means you never actually knew how to do your job properly. Sure it can help you get over some hurdles, make docs searches a bit easier if some library has crap docs, but it’s a 5% speed improvement at best and it’s all worse the moment it sends you down some stupid hallucinated rabbithole.
You should give it another go, it has evolved disturbingly since last year. It out performs a junior level software engineer in both design, implementation, testing and debugging.
The hybrid model of a senior engineer using AI to produce code while the rest of the time allocation is spent on reviewing is the new normal.
You get 4 weeks to build x feature, you spend maybe a day with the help of AI then use the rest of the allotted time testing and debugging. What’s happening now is your allotted time is shrinking because managers understand how much faster engineers are working so its a cycle of shorter deadlines which pushes everyone to use AI.
I wouldn’t worry about software engineers going extinct. The role is changing but those core skills are really important to catch mistakes from both humans and AI.
Right now theirs two types of people using AI, software engineers who learned computer science and built software products and Joe MBA who struggles to write a bat file with the latter struggling to build cohesive products
I don’t know whether this is just ragebait, whether you have never tried any advanced AI agent or whether you genuinely think you can work as fast as an AI, but I can asure you that you can’t.
This isn’t One Hour Hot Dog. If you need a big huge fix right the hell yesterday, you fucked up last week. Possibly last year. And what’s gonna prevent that sort of company-liquidating blunder is a layer of crotchety obsessives who can spend a day reading and then commit one line. ‘Hit engine with hammer: $1. Knowing where to hit: $9,999.’
A system that’s pretty good at guessing a hundred places to try hitting has obvious value. Especially when undo is a thing. But this attitude of ‘the future is now, old man!’ is almost as off-base as the folks insisting a magic coding robot won’t help anybody.
I agree with you. I’m not even 100% anti-AI even though a lot of how it is used absolutely reeks.
Of course Big Business is gonna be all about shipping it fast and cheap to the detriment of all else as long as it “works right now.” The ridiculous farce of capitalism as we know it now is that their real goal is to sell off and bail at a profit just before all that vibe-debt comes due and things implode.
It doesn’t mean it’s the best way to create software.
It reminds me of how homes nowadays are thrown together and so ridiculously shoddy because it’s all about speed and holding together just long enough to sell.
This is largely an oversimplification because it depends on how you use AI in the first place. Are you building modularly and incrementally? Or are you letting it ride on black?
All it takes is two developers who let it ride and approve each other’s PRs.
That’s a very good point
ive personally found LLM coding to be pretty effective if i adhere to very strict “engineering best practices” like TDD, good documentation, thorough API design, systems design, etc.
im very afraid that the next generation of software engineers will never develop the skills needed to make the most out of it because they skipped the rudiments of good software engineering.
to me it feels like playing jazz without learning scales. it’s possible to be an incredible jazz musician without formal training if you’re a savant… but you’re probably not.
“AI is the asbestos we are shovelling into the walls of our society, and our descendants will be digging it out for generations.” - Cory Doctorow,
