alt Hacker NewsThe more I read about articles like these, I grow even more convinced that the education industry as a whole, regardless of the country or stature, has kind of lost their plot.
Sometimes I even wonder if this is the outcome of sheer laziness, fear or both.
When I speak to professors, teachers and students - It's also surprising that "top tier" institutions are fighting AI harder (outside extremely specific courses like Harvard’s flagship CS50, MBA courses at Wharton (UPenn) and MIT) while "bottom tier" institutions are completely embracing it and rebuilding their curriculum around it. One CS professor at a "bottom tier" CSU mentioned to me that he's actively going completely "open book using AI" - students are allowed to use anything they want from Claude to Codex to OpenCode to finish assignments but the assignments have now changed from "blurt out quicksort" to "let's sort N natural numbers in a cache efficient way using least amount of resources". I would hire the latter over the former anytime. I am tired of interviewing candidates who can shit out quicksort before I can even finish my sentence but stare at me dumbfounded when I ask them to sort people's name serialized in unicode.
In my opinion, the bulk of traditional education has been a mix of memorization of facts, knowing inference rules, and applying inference rules to those facts, coupled with recall.
Before the age of LLMs, only very expensive-to-build rule-based expert systems were able to replicate that functionality. Humans were just simply cheaper and way more reliable.
In 2026, Frontier models are exceedingly, across the board, across industries, breaking records and challenging those notions on cost, capability and sophistication.
Trying to replicate how education used to operate pre-frontier LLMs is like forcing people to farm by hand in the age of automated tractors that have LIDAR, Vision, RTK on board.
I'm not discounting other elements of learning like collaborative debate, clinical/lab work, Socratic reasoning, emotional intelligence and the development of a professional network - but I argue these skills are not limited to a school or university setting. Infact, a lot of this is distorted in a school or university setting compared to the real world.
I have been filing my own taxes, including complexities like equity, real estate and business income for over a decade now, so it's not just a simple 1040 and 540. Reading through IRS documentation, talking to EAs and CPAs to fill in ambiguities and gaps was pretty expensive in terms of time and money.
Both Claude Opus and GPT 5.5 now, as of 2026, answer all my tax questions correctly. Those thousands of dollars in time and money I had spent has been replaced by a single $20 subscription. Unless tax codes drastically change every year, that $20 is a one time cost.
If I were to begin my tax journey in 2026, I would never had to spend those dollars: dozens of tax professionals are out of a job - all their education is for nothing.
It's entirely irrelevant whether they passed their exams by carving answers out on granite, taking their exams in a jail cell on an island proctored by Catholic Nuns under the watchful guard of automatic machine guns manned by T-1000s, I just don't need them anymore. For my usecase, these humans and their credentials provide 0 additional value over a one-time $20 expense, no matter how complicated it was for them to get their credential and what complex interpretive dance they had to do to impress the people awarding their grades.
All this "reject AI, do it by hand" is just insanity at worst and laziness at best.
That said, I'm personally unsure what the future of education in the age of tractors is like but removing weeds, planting seeds, watering them, all by hand is certainly not it.
It's my understanding that most countries - developed or developing - are bottlenecked on educating their masses due to lack of qualified teachers.
That's a bandwidth problem. Having those teachers listen to oral arguments from a handful of students is not solving the core bandwidth problem. All these shenanigans is doing a disservice to the public.
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> In my opinion, the bulk of traditional education has been a mix of memorization of facts, knowing inference rules, and applying inference rules to those facts, coupled with recall.
These are important skills to develop, even in a world with LLMs.
> All this "reject AI, do it by hand" is just insanity at worst and laziness at best.
If a 3rd grader complained about having to learn multiplication because calculators exist, would you agree with them?
Why do we make kids learn how to do math if they can pull out their phone and open the calculator app? Because learning how to learn is important and there is value in understanding how the answer is produced, even if you have a machine that can produce it for you.
Universities can teach a separate class on how to use LLMs. The existing classes should be focused on teaching their existing subject matter, not becoming an extension of a how-to-LLM class
Two points:
There are two kinds of engineers in Finland. Some received a more theoretical education at research universities. Most went to more applied institutions that focus more on practical skills. Regardless of what employers say, they generally prefer the theoretical engineers from research universities. Because the higher status of those universities attracts more talented individuals, because theoretical understanding tends to stay valid longer than practical skills, and because it's easier to learn practical skills at work.
The kids who start their studies today are supposed to graduate in 2030, and they will probably retire around 2080. Focusing too much on the skills their early employers might want in the 2030s would be a huge misallocation of resources.
Depends on what skills you want the students to have.
In e.g., philosophy, allowing students to write their assessments with the help of LLMs changes the students’ depth of understanding, as well as their ability to synthesize, formalize, and drum up their own arguments and objections.
These are all useful skills, even in a post-LLM world.