I am genuinely starting to fear an almost universal dumbing down of humanity as a result of AI. It feels like so many people have just stopped caring about what they do or what they create. They no longer believe they need to know what they are doing or care about the results. The machines will do the knowing and caring for them. Or they won't - but what they produce without knowing or caring will be good enough to tick whatever boxes are necessary so it doesn't matter.
Over the years I have enjoyed many deep and interesting technical discussions online - both here on HN and elsewhere. I can't help feeling that those discussions have also all but disappeared over the past few months - alongside high quality free material that some experts have kindly given away but increasingly no longer do. I rarely find myself contributing any more because there is little on any of my usual online hangouts that is interesting enough to spark a deep technical discussion any more. It's 90% AI stuff - either written about AI or (usually poorly) written by AI - and most of the discussions that do initially catch my interest at all seem to end being very negative and depressing. (I appreciate the irony that I'm perpetuating that cycle right now. Looking through my relatively sparse recent contributions to HN is actually quite depressing. Although at least I actually am getting out more!)
I wouldn't mind so much if I believed the hype about the benefits of AI-generated work and thought that overall this period would be a net win for humanity. Unfortunately I don't really believe that. I fear the LLM era will eventually be remembered for producing tools that could do average/routine tasks quickly and to an acceptable standard but that were actually used to (try to) do good/innovative tasks with substandard results. But by the time enough decision-makers realise this it might be too late and the damage might already be done and hard to reverse.
Your comment is even more depressing when you realise this applies to other elements of our daily lives, including but not restricted to oil, environmental management, societal support...
Funny how our short feedback loops and greed pushes people towards deeply unstable systems, especially if the price seems so "cheap" for a reward sold as so incredible that it would be dumb not to bet on it...
I'm on the same boat, negatively affected by AI. I'm the CEO and founder of an EdTech company and our B2C revenue has greatly decreased as a result of Gen AI.
But unlike the author of this post (or cited authors) I'm not sore. AI is providing a much better education model for students. So it's us that we have to adapt, not complain that the world is changing.
For example, in Machine Learning our projects are sometimes extremely long and repetitive. Because before AI, it was a valuable skill to be able to recall APIs quickly (what is the method to drop duplicates in a dataframe again?).
But today that's no longer the truth, and for the better. I am happy students don't have to go over the same repetitive low-value processes that I had to go to.
Students can now focus on more high level valuable tasks: understand the domain, compare evaluation methods, compare models, balance tradeoffs, present solutions/reports, etc.
It's like in the 50s when students had to memorize tables of logarithms. Nobody misses that.
We are in the process of recreating all our projects to adapt to the new world. We'll see how it goes.
> But today that's no longer the truth, and for the better. I am happy students don't have to go over the same repetitive low-value processes that I had to go to. Students can now focus on more high level valuable tasks: understand the domain, compare evaluation methods, compare models, balance tradeoffs, present solutions/reports, etc. It's like in the 50s when students had to memorize tables of logarithms. Nobody misses that.
Maybe when it comes to any coding-related learning, I can agree with that point.
However I think the future of education in general is very bleak. When we have plummeting scores for the PISA exam across the world [1], I fear people will get dumber and dumber.
There will always be those who thrive, but the easier it is to obtain information/knowledge, the less I think people have an incentive to do it. And I don't buy that AI will solve all intellectual jobs anyway.
> However I think the future of education in general is very bleak. When we have plummeting scores for the PISA exam across the world [1], I fear people will get dumber and dumber.
This is exactly what AI companies need, so that's development should be celebrated. There are two paths to capture the value that's currently wasted on paying people:
1. Build a system that's superior to nearly all people.
2. Make people worse, so even an inferior system is superior to them.
Getting AI into the classrooms and degrading the educational system are important for path #2.
It's good not to put all your eggs in one basket, so I'm glad the AI industry is pursuing a multi-pronged strategy against their competitors. Who cares about the waste and destruction for humanity, as long the investors get good returns?
PISA exam scores are a lagging indicator with many years of lag. I doubt the reason of that is AI. Mobile phones? Social media? Any other multi causal reason (poor eating, anxiety, low testosterone, whatever), most likely, but not AI.
If you think that’s a lagging indicator, the many reports from teachers and from self reports from students and even adults trying to learn also point in the same direction. See what’s happening with exams and homework exercises.
Education itself has lost access to the tools that were making it cheaper and easier to teach.
Learning something is a side effect of overcoming friction. AI removes friction.
The pitch is learning useful things (if not skills) but we end up using schools as storage for kids, for indoctrination and as a business model. The ratio gradually changes.
We end up with shit results and where they arent shit students are rushed though as if to prevent them from thinking about the materials.
We have libraries full of unused education formulas. Some 2000 years old. Then there is nutrition, sleep and other work/rest ratios, physical health.
How expect results without learning to teach and learning to learn?
Onto what should one anchor learnings if the suroundings are always the same?
I never hear a word about spaced repetition in school. Its so basic i must conclude they knew nothing about what should have been their area of expertise.
When things get bad enough we will [finally] have reason to improve.
Maybe the great work of Salman Khan is merely a hint?
We know about those things and they don’t work the way you have laid out. For example spaced repetition is ideal for memorizing words, but less useful for working through a math problem or creative writing (relatively speaking.)
MOOCs were something I personally hoped were the solution to scaling education. However it didn’t work out, with courses having single digit completion rates.
This is for free, high quality, immaculate pedigree, learning material available at any time and any place.
Years of additional research had to be done to figure out how to raise completion rates, which creates more complexity on systems and delivery.
Unfortunately, that improvement is now moot, because LLMs obviate the friction and effort.
The point of doing a homework exercise is to provide learning friction for students.
> For example, in Machine Learning our projects are sometimes extremely long and repetitive. Because before AI, it was a valuable skill to be able to recall APIs quickly (what is the method to drop duplicates in a dataframe again?).
> But today that's no longer the truth, and for the better. I am happy students don't have to go over the same repetitive low-value processes that I had to go to. Students can now focus on more high level valuable tasks: understand the domain, compare evaluation methods, compare models, balance tradeoffs, present solutions/reports, etc.
You honestly believe that students that don't have the tenacity to stick with learning a simple set of verbs and grammar are going to have the tenacity to learn concepts steeped in jargon?
I do mean learn, which AI use has been repeatedly shown to be detrimental to.
What a great perspective to have! Completely agree with you and I want to add on to it by saying mentors will always be valuable because students have always had access to information even before AI, if you think about it. It's organizing and packaging it in the right format that's always been the key issue.
" It's organizing and packaging it in the right format that's always been the key issue."
LLms dont help here either.
Part of learning is about struggle. Seems many here want to disregard that fact and just run to the LLM lmao. Yeah you can do that - the knowledge won't really stick.
But it becomes different knowledge. You learn how to manage an LLM to create the thing you need instead of writing code to do the thing you need. Still a learned skill. In some cases, still a struggle.
The initial creativity is still with us, not the LLM. It's the Art/Craft thing - we have the Art, the machine does more of the Craft (and it always did do a fair amount of the Craft).
I'm seeing folks who couldn't (for whatever reason) work out how to code, starting to produce some amazing stuff with the LLM doing the coding now. It's their creativity, their project, their vision, still. The fact that they didn't write the code is meaningless.
>But today that's no longer the truth, and for the better. I am happy students don't have to go over the same repetitive low-value processes that I had to go to.
It's a real shame a leader of an education company doesn't value the actual learning process. Those "low value" processes are the building blocks to understand and master high level concepts. I'm not spending my day to day thinking about the low level memory allocation in my job, but that knowledge and work helps immensely in how I approach the higher level assignments and wider architecture. And I still kick myself because my assembly knowledge is is only 1.5 semester's worth.
And yes, I still look up how to construct an array in C++. Not really because my memory is bad (okay, kind of), but more for the practice of reviewing API's and parameters and maybe making new revelations. I probably knew internally some 12 years ago I could set an initial capacity in one of the array's constructors. I didn't really "understand" the value in that until one random work day 4 years later as I was working through some in-house container packages.
You can even say that doesn't matter if you know what resize() is, but it's those little bits of learning nuggets that builds you up from a "fine engineer" to a "great engineer". Less the knowledge and more the work ethics built to obtain it.
> before AI, it was a valuable skill to be able to recall APIs quickly
That’a the low value they’re talking about. And all of that stuff is accidental complexity.
To use their example, you need to know that dropping duplicates is a good idea (and why). Knowing what the syntax and api calls to do that is, in my opinion, unnecessary.
That's not accidental, anymore than human language itself is accidental. APIs are designed very intentionally, and a good API's parameters have architectural reasons behind what they include (or exclude).
Even your example has unintentional complexity. A 'duplicate'? What's that? Do we compare the memory it points to? Through use of a custom comparator function?by an id or tag? APIs and entire languages are designed around how we define such seemingly simple terms.
Ultimately a language, be it a programming language or human one, is about communication. I find there to be value in knowing how to communicate effectively, even if employers increasingly disregard the value of such knowledge. Without it, we'll quickly find out why it's fundamentall quickly.
As an educator and author, I feel Molly's pain (Anthropic owes me $60k for pirated books). My course and book sales have dropped significantly. I feel like much of the value in my book-based knowledge is harder to discover in AI agents. (One example might be inspecting SHAP values from XGBoost models and using that as feedback to feature engineering for a linear model (like Logistic Regression)). So I'm afraid more advanced techniques might go by the wayside in the name of delivery speed.
I use AI both in the cloud (I tend to avoid Anthropic...) and with local models.
I've probably written more code in the past year than in my whole career. I can now create what I desire (I just created a telemark skiing game over the weekend based on my Strava segments). I think this has helped my teaching as well. In a recent ML course, I created many interactive examples that in the past were just doodles on my whiteboard, but are now embedded in the notebooks I give students.
I've also taught a few AI courses to clients as well. However, with the inevitable rust/ASM-ification of everything, I'm not sure how long those skills will be valid. I do, however, think that having a human in the loop for ML and data analysis is still important.
The people reaping AI's benefits today generally developed their skills as juniors through old-fashioned struggling in the pre-ChatGPT era -- actually reading docs and articles, trial and error, puzzling over mysterious bugs, and generally doing lots of mental lifting.
How will skill building happen when LLMs and coding harnesses seemingly provide all the answers at one's fingertips?
> How will skill building happen when LLMs and coding harnesses seemingly provide all the answers at one's fingertips?
They don't provide all the answers. And are often wrong/mistaken. But they also produce stuff faster than you can consume it. This is great for when you know exactly what you want and can cheaply test the output and guide the LLM to the right solution. It is expensive (in developer hours) in other cases.
I have been building a new PL+VM this year and had to pause development on a few occasions because I have not had the time to go through the implementation because there are so many modules. But smaller tools (5-10KLOC), you can judge fairly quickly.
So, the answer to your question is: people need to discover the strengths and weaknesses of the tool on their own, decide what kind of expertise they want to attain, and if it is worth the effort.
That's a great question. I don't know what the future will be like, but looking into my crystal ball, I'm not seeing much hand-generated code. Very little (or no) human code review.
Having the taste and business sense to develop the right thing will be important. If it stops working, ask the AI to fix it.
While this may be true, there are certain types of development (rockets and kernels come to mind) where you will always need highly skilled people willing to be responsible. LLMs excel at many logical tasks but they struggle with creativity and responsibility.
So I teach a couple of web architecture classes, and it’s been my experience that there is still a desire to learn how to truly build quality systems because they want to learn how to build quality systems.
I think our industry needs to transition to figure out what does it mean to build a quality system in the age of AI? It’s one thing to vibe code an application that works. But would you depend your livelihood on it? Would you get business funding and base the future of your team on it?
I think the challenge of the educational space is to figure out how to teach the judgement to build solid systems without relying on “hand coding”. For me I’ve been working on technology agnostic composable frameworks that help build that judgement. But honestly we are all just figuring this out together.
There will still be a need to be able to train system builders, the question really is what do they actually need to learn to be solid system builders in this AI era. And there’s a strong chance that pure programming language or tech stack learning may not be enough. This is what we educators need to figure out.
> But would you depend your livelihood on it? Would you get business funding and base the future of your team on it?
Yes. I stopped looking at the code about 9 months ago. It's easier/better/quicker to learn how to get the LLM to audit the code.
Investors don't care if the code is LLM-generated, they're mostly assuming that now anyway. The VC's I've talked to recently are screening pitches using an LLM, they're embracing this tech.
If I recruited a new dev to the team now, I would expect them to be able to run multiple agentic coding instances simultaneously. I would not expect them to be hand-crafting code any more.
I agree with you no investor or user cares how the code is built, and actually there’s nothing wrong with using LLMs to code. LLMs are the way to code now absolutely.
But, investors do care about the stability of the system they invested in. And how quickly it can be extended and expanded upon while still maintaining functionality. And they deeply care about scalability. I don’t believe this is a question about whether code is LLM generated. I think this is a question of having the ability to build a system that can be up and provide the value that investors expect. And the way you use AI and your knowledge of systems does play a role in that, especially over time.
And another point: it doesn’t have to be either or. Sometimes the prudent thing is to hand code a specific highly sensitive part of the system while your agents are building other things. The fact that these agents can do things in the background frees us with different possibilities. And also, sometimes hand coding some areas in the code that you are not familiar with builds your knowledge which the ln enables you to guide the agents more effectively later on. There’s benefits of both approaches and both approaches can be done simultaneously.
Nobody is mentioning the other side of this. Technology creates all of those jobs too. The field of web dev, and the ability to earn an income from as ebook was awesome. Things change and what we should doing is going in eyes wide open.
Founder of Boot.dev here: the industry is absolutely having a VERY rough time in 2026. Our revenue in particular is actually up in 2026 vs 2025, but modestly low double digit percent) vs 2025 being nearly double 2024. That said, I feel we're an exception in that we have been able to grow, mostly due to a complete doubling down on high quality human content, and trying to build experiences you just can't get from plain text (interactivity, animations, etc). time will tell.
But isn't this (interactivity, animations) exactly the kind of stuff someone already familiar with a concept would turn to AI for yet another interactive visualization that might help develop intuition?
That's at least what I do. Sometimes it feels performative at best, other time I get genuinely new ideas by having a vague thought turn into a tweak able viz.
I tried creating a similar concept at https://www.codembark.com but felt it would be too hard to monetize with the headwinds of AI. I ended up just getting rid of all of the paywalls and just offering it for free.
Thanks for boot.dev, it's the one website I regularly point my students to when they ask about places for supplemental programming education. I hope the genAI bubble doesn't put you out of business like it might do for us in traditional academia.
I'm taking courses at my local college (heavy duty diesel tech) and I'm finding how little use the teachers is for me. I got a digital copy of the textbook, and downloaded all the courses notes, pumped that into claude and made a discord bot that generates me quizes, tracks all my progress, and builds me a study guides off the results.
Superior to any teacher I've ever had, no matter how involved they are. I genuinely don't even see what my teacher is needed for beyond a requirement for me to be there. I can ask the bot "can you clarify X section" at 3am and it'll do in 1 second. In class, the teacher reads the slides, adds some extra points and takes questions. But my bot does all this, completely personalized to me.
Times move on, and I don't see teachers surviving. I'm hoping by next year the college will offer an "at home, self paced course" option. Theres no reason for me to be there.
AI is moving fast, so I'm very open to the suggestion that Claude can do today what it couldn't six months ago. But my experience with folks who are learning from AI, historically, has been that they have high confidence in abilities they are not able to demonstrate when asked to show mastery through conventional problem solving.
I teach many data/ML courses for clients using their data. It is amazing how many insights both the students (as SMEs of the data) and the teacher (as an SME of the techniques) can have when going through certain techniques together. Quite often, we get a "those last 5 minutes more than paid for the training" insight.
I think that is possible with AI (I haven't experienced it), but I also feel like most folks use basic/naive/cursory techniques when using AI because they don't know what they don't know.
This has been my experience as well as someone who uses the frontier models quite a bit, I think it's easier than ever to deceive myself into thinking I'm being productive or learning. I've noticed it in others as well.
Part of it is shear volume of "stuff" that I'm doing on the fly while leaning on AI as a crutch for speed (otherwise why wouldn't I just do it myself), the other part is that it's ephemeral, even if you read all the lines of code, it's hard to beat manually typing them yourself for retention _and_ failing at it, and being forced to teach myself what I did wrong.
All that's to say, I think AI psychosis can happen at a group level.
I do, all the time. I get test, do good and then the college signs off that Im a certified mechanic when Im done.
Maybe its more of a critique on the school, but no one tests you on your ability to disassemble an engine and rebuild it. They simply make you write a test based off terms you learned in a textbook.
This was exactly my experience in high school, university, and now the same in college.
I would of killed for this bot during my math courses in university.
> no one tests you on your ability to disassemble an engine and rebuild it. They simply make you write a test based off terms you learned in a textbook
Out of curiosity, where–geographically–are you going to school?
If you're able to pass you theoretical tests without AI, it's fair to say you're learning what's being tested.
reminds me a lot of my learning process. I read fast, seemingly picked up concepts quickly, can answer some sample questions. I felt fairly prepared, and honestly most classes were a breeze with that.
Then, for better or worse, I was pushed to honors and AP classes in high school. The same methods didn't work there. Things got more abstract and I needed to connect multiple concepts together. Math drills turned into word problems that revealed weaknesses in my older math fundamentals. reciting facts from a required reading wasn't enough; I needed to know what that meant and understand the setting of the book.
My grades suffered and you can argue the "academically optimal" way would have been to not take so many advanced classes. But those experiences definitely helped me to critically think better. Eventually (My English and History appreciation would come much later. Math and Science trained me well).
It is also a shame how much the quality of the teacher can affect this experience and perception of education as a whole. I wonder if those enthusiastic to replace the teacher ever had one that fit their needs?
And are you learning whatever you are learning for personal gratification or hoping to use that skill for survival? I am asking because the way I see it, just like the teachers, everyone is becoming useless.
Teachers and schools need to let LLMs do the things they are better at, and concentrate on having instructors do the things that LLMs cannot. Teachers that only read from the slides have always been a problem.
Your instructor should be having you dismantle an injector pump or bleed an air locked injector rail. You can read a book about how to do that, but you won’t really know how to do it until you’ve done it for reall
I thought the same until I had kids. I realized that kids generally want to learn, but they usually think what the teacher is telling them is not the best thing to be learning. No technology, not even AI, overcomes the student's ego; in fact, technology rarely even tries to address that issue. I think this often applies to adults too. Teachers continue to be necessary to help students achieve an appropriate level of humility to be able to learn.
You clearly have enough humility in your field to be able to soak up knowledge. That's great for you! I suggest your dedication is rare and teachers continue to be essential for society.
Formal education has more than just an instructive role. In fact, it's everything but the instruction. Reciting content to learners doesnt necessarily help them learn.
Teaching should turn into conveyance of taste. The teacher should help figure out what needs to be examined and how to examine; help figure out ways to close the gap between the textbook and reality. AI can't do those things well yet, and perhaps it never will be able to.
Sadly, the truth is that in school, you're only rewarded for what you vomit back up on the test. Rote memorize some formulas and facts, copy those back on the test and you're now a certified mechanic/engineer/doctor/whatever. That's exactly what got me through math courses in university.
Sucks, but its true. In my case, if there was a test that required me to disassemble an engine top to bottom, claude would be mostly useless.
In my experience, that was pretty much true until I started doing small discussion-group-style graduate classes. But those are necessarily capped by staff-to-student ratios.
Maybe all education will get more and more similar to e.g. learning an instrument.
You can get everything from YouTube videos, sure. But a good teacher will help with things like knowing how to get a good repertoire for your skill set, what bad habits not to develop that will cripple your ability to learn more complex pieces over time, etc.
I think expertise in hard subjects will only become more and more valuable (as always), and thus harder and harder (and more expensive) to achieve.
I have a feeling AI is hitting all the same dopamine receptors as your attention grabbing apps and video games, is highly addictive, and is merely making you feel like you are achieving something. Sort of like DuoLingo.
We see the same at my university. It's sadly the reality of it.
We are kind of envisioning that university will be a place for social activities, mingling, rich people meeting partners, etc. So we are moving towards more of that.
Speaking as someone who never learned well from courses and always preferred documentation and 'just doing it': I wonder how much of this drop is 100% LLM usage by devs vs. devs realizing a lot of video content was just padded out anyway.
The mentioned 2ality blog by Axel Rauschmayer was an extremely detailed and thorough look at TS and JS specs. So right up your alley. Same with Josh W Comeau.
Well as someone who got a ton of value out of tutorials and would go back to the documentation and "just do it," I wonder how much this is really actually just LLMs as we're all seeing out sites bombarded with bots ¯\_(ツ)_/¯
The traffic to my blog and my books (which were free to read online) increased beyond what I can currently afford.
That’s a shame. I’m surprised someone so well versed in web technologies has such a brittle setup. Cloudflare Pages, or if you you’d prefer to stay CDN-less, a $4 VPS, will handle any sort of traffic this blog can reasonably receive.
People here seem incredulous that others would learn from a video series, course, or book, but I've always found this content extremely valuable and would continue learning from them even now. I learned the basics of async programming through learning about AJAX from Jeremy Keith's book on the subject, I dove very deep on JS itself from Secrets of the JavaScript Ninja, Cocoa from BigNerdRanch, Much of Swift and SwiftUI from John Sundell's writing, tutsplus, HackingwithSwift, Grid and subgrid from Rachel Andrew's writing. As a largely self-taught programmer, these resources have been absolutely crucial, and in retrospect it was a mistake to conflate the ability to find any information I want in discrete chunks with actually learning parts of a subject. I've also only rarely found University level formal courses to be as substantial in terms of what's actually useful to bring with me into practice. LLMs are more sophisticated in many ways, but if I want to learn something, I need to approach it more seriously than modern tools would have me believe. LLMs are great at letting me skip over the learning part, and they're great at helping me explore the problem space, but they're not what I'd turn to for educating myself on anything I care about, in much the same way that listening to a podcast or watching a documentary does not qualify as education, nor does it replace reading and/or physically practicing something.
Web development, as much as some would like to think, is and has always been, complex.
I haven't tried learning Rust yet, and I'm sure as hell not going to lean on an LLM at all when I do.
I've written for a range of front-end publications. This year they've all cut down the amount they're publishing, started slopping out articles, or gone quiet altogether. It is rough. Speaking as an author, even those that seem 'fine' at a cursory glance now feel strained behind the scenes. It makes me so sad.
I considered myself to be a web developer in the 90s and early 00s. Then things began changing very quickly into something I didn't recognize. I came from an era that did layout with table tags! I felt like an old dog having to learn new tricks. I chose to pivot into statistics rather than adapt, though I've since come back around via data science and systems engineering.
I don't think what's happening is a uniquely AI phenomenon. If it wasn't AI, it was going to be something else. The ground is always shifting beneath you. It's happened to me in multiple fields through my career. You adapt or you pivot. Like a startup.
For many people who feel negatively affected by AI, my advice to them is to do what I did when my professional disciplines changed to something I didn't recognize: pivot. The great news is that AI makes it really easy to be a beginner in a new adjacent field.
I come from the same era. Learning new languages and frameworks is nowhere near the same ballpark as having the whole ground your business was built on pulled out from under you when it comes to "just pivot."
Fair, though I'd argue businesses are even less entitled to operating the same way long term. I haven't stepped foot in a department store in years. Disney isn't making movies the way they used in Walt's day.
This implies that you know which question to ask. If people don't know about accessibility, security etc. How are they able to learn? Also, most people don't use AI to learn but to do it for them.
That's a good point, but if you have an always-on agent focused solely on helping you improve your knowledge/skills, it can ask you questions every day and gradually identify gaps in your knowledge and it gets really good at knowing where to push you.
That's where books come in. Read them, explain what you're learning to the AI, and what interests you about it, ask for it to check your understanding. Explain your other interests, ask it to suggest other things to read which will bridge the gaps between what you're learning now and the other things you already know.
I mean, the frontier models are pretty damn good at giving you all the standard conventions on things... The first question I usually ask is "give me the all the modern day conventions for this use-case", and then I start the context building from there. This applies to a lot of things, but I mainly use it when I am coding.
I constantly get dragged into web tech from tangential projects. I still found it valuable to take the time to learn Electron (and update my front end knowledge) properly to do a port of an Electron app for a slightly different context.
I used AI to extract the raw frontend structure of the app because I know I can't design to save my life. And I still need to tweak it quite a bit because the interface was always janky (a desktop app but content is overflowing everywhere, and it definitely can all fit in a typical full screen view). But the act of structuring that stuff into a modern framework and hooking up the logic will still come down to me.
I definitely understand the uncertainty and frustration with a field changing beneath you, and the distastefulness of a lot of the content made with agents. But I think this is going to be a short lived sentiment. I only recently started using claude code because my earlier experiments resulted in more time instructing the bot than working with the code.
This time my approach was better and so was the capability of the model. I can make a small change in one place and have the model propagate the change throughout the codebase. I'm still working directly with the code, and the agent doesn't have to make any important decisions about structure (which remain generally terrible). My familiarity with the codebase is the same as if I had made each edit myself.
It is definitely possible to build faster and better with an LLM and not give up control or the enjoyable part of coding. The energy in this space still seems to revolve around guiding the agent or letting it take over, the key is ignoring it entirely and discovering what works for you.
the older your brain, the less plastic it is! lets remember what it might have felt like for you to write your first BASIC program or hand-code your own HTML website. there was a desire to understand :: HOW IT WORKS? HOW DID IT DO THAT?
just because our old-brains did it "the hard way" and now we have these LLMs that can just make it happen, doesn't mean that our little ones want to/should skip the steps of understanding HOW IT WORKS
me and my kids have been making all sort of silly games and my oldest is starting to wonder HOW DOES THAT WORK, PAPA??? and i'm like, well, let me show you this...
a magical thing! what a time to be alive!!! there is joy, but you have to conjure it!!
I used to listen/watch some youtube channels for learning. Especially as a newbie, I used to listen to the channel - Programming with Mosh (5M+ subscribers). I see that he has stopped producing videos regularly. Last one year, he produced only 3 videos. There could be other reasons. But I suspect lack of interest from viewers because of AI.
The real question is who was still buying this type of book in the last decade or two? What value were they getting out of it? Was it being used as reference or training or what?
If you haven‘t been paying attention you will off course miss the good stuff out there.
Rachel Andrew’s (mentioned in TFA) for example has The New CSS Layout (2017) https://abookapart.com/products/the-new-css-layout.html an excellent book I still recommend for anybody who want to learn about modern CSS layout.
But if you are this dismissive of the field of course you will fail to see the value of them.
A Book Apart shut down and says all copies have been sold. They suggest reaching out to Rachel Andrew directly to see if the book is available elsewhere. (Her website just links back to A Book Apart).
Around 10 years ago I used to worry a little about keeping up with younger folks. I only really started using computers when I was 9-10, and didn't get the internet at home until my mid-teens. I thought there's probably kids learning JS at age 6 these days... These kids are going to be almost super-human in their technical skills compared to someone like myself who didn't learn HTML until their early teens.
But then around 2020 I realised kids actually have no clue how to use computers because their primary computer is a phone or a tablet. And there only experience with desktop computers are Chromebooks at school.
Now I suspect my generation will be the most knowledgable technical generation by far. The only issue for us is that no one will care.
As someone who used to write a lot of tech tutorials and has published a technical book, for me it's much less a financial thing and much more just sadness that something I spent a lot of my life doing, that used to generate emails every week from people saying thank you for helping them is now just completely worthless. I've spoken about this before here, but I feel like I've lost a large part of myself over the last couple of years because almost everything I used to do in my spare time now seems completely pointless.
This is quite weird that "AI" presumably ruined book sales, since the info from the books were mostly available though the search.
You want it structured? You need the book - "AI" won't solve it for you (well, if we discount cases of word for word reproduction... which we probably shouldn't, but this does not seem to be the argument here).
The kind of people, that read the books, are the kind of people that largely won't settle for a chatbot as a replacement.
Can there be another reason for the sales drop? Unemployment, "death of the junior", wages decline?
Personally, I read way less traditional books when it comes to learning stuff. Especially the “utility”/“tutorial”/“handbook”. Top nitch books talking about general principles I’d still read.
Especially for books that need to teach me a subset of a certain discipline - in the past I’d get 4-5 (or at least samples), and try to find the parts that are of interest to me in a style that fits me. Novadays I’d just ask Claude to explain things in a form that I like, with pretty illustrations from Imgen :)
E.g. I don’t think I’ll read the animal books from O’reilly again. But an equivalend of “Thinking in C++” or “Pearls of programming” of a new field? Sure.
Economic headwinds and the collapse of tech labor would definitely impact people's willingness to learn tech, especially on their own time with books/courses. I'm not sure if it's enough alone to cause yearly 50+% declines, though.
AI for sure impacts ad revenue. It's an absolute mess trying to measure proper web traffic anymore, and it' been shown quite a few times how AI summaries in search impact page clicks.
It depends on whether you bought books to learn or bought books to solve.
There are a vast number of books that I purchased not for any interest in the topic, but to solve a particular problem. I have zero interest in understanding Docker. I find it tedious. But I do have a book on it as I did need to know it at some point.
I wouldn’t buy that book today, as AI means I no longer need to know Docker.
> The income from my book sales went from being enough for me to live off (2024) to zero (2026).
> The traffic to my blog and my books (which were free to read online) increased beyond what I can currently afford. Virtually all of it comes from AI crawlers, so there is no ad income.
I know correlation is not causation, post hoc ergo propter hoc etc. etc. But these circumstantial evidence are too strong to simply ignore... As it stands AI is the obvious culprit. And with the current evidence, it is perfectly reasonable to blame AI and nothing but AI.
Most of the stuff these Ed-Tech companies taught is counterproductive. Much of it was unnecessary solutions to problems that didn't exist. So so many Web tools are things created because their creator didn't properly understand HTML, JavaSript, CSS and the DOM. Then these schools taught everyone these unnecessary things and they become the standard and made things overly complex and give us massive build times for stuff that was never meant to need a build phase in the first place.
LLMs with HTMX and plain old CSS and JavaScript (maybe Typescript) is the future. Getting back to little to no build times and frontends that don't take up 1+ GB of RAM on the clients
What Ed-Tech companies? This article isn't talking about Ed-Tech companies. Axel Rauschmayer isn't an Ed-Tech company. He's an individual author who wrote books about JavaScript, the language. He wasn't pushing these "unnecessary solutions", he was helping developers understand JavaScript, exactly the thing you say is necessary. Josh W. Comeau isn't an Ed-Tech company, he's an individual who writes content about new CSS features like Anchor Positioning[1]. What do educators like this have to do with 1+ GB RAM frontends?
I've personally been using a Phoenix LiveView-like approach extremely successfully, combined with LLM coding. It is extremely, stupidly fast. We are talking about loading an entire multi-window desktop environment in the web on spotty 5G networks in half a second, transferring less than 1MB of data.
I think traditional web frontends might be dead for any applications with servers that can afford to keep server-side state of a logged-in user.
(Notably this includes almost any kind of AI application, because the LLM costs dwarf the web hosting costs anyway.)
>LLMs with HTMX and plain old CSS and JavaScript (maybe Typescript) is the future.
1. LLM webpages in my experience have definitely not gotten simpler, nor load faster. It just pushes out more of the same junk underneath without any of the oversight we'd give a human
2. I'm not even sure the webpages are the big resource hog anymore. Chromium itself has had the reputation for eating RAM for well over a decade at this point.
3. In many ways, we did this to ourselves. In the name of shipping faster, we (or perhaps the executives) outsourced solutions that would sacrifice the simplicity of the code for "more mainainable, cross platform" frameworks. Electron was a solution for software companies not wanting a dedicated Windows and Mac (and perhaps Linux) team. React was a very specific solution for one of the largest websites in the world, that the rest of the industry adopted as a trend.
It's over guys. Web Development (1994-2025) will be remembered like elevator operators. What it transforms into at this point is still an open question being actively discovered. But our vocation is dead and gone as it was.
Education as we know it is doomed. But we have to realize that all our education systems were shaped by the means we had available to us in the past for imparting education, learning, and testing knowledge at scale, and critically the kinds of jobs we were being trained for. To put it bluntly, the entire system was tuned for producing cogs in a machine. (Or just bricks in the wall, if you will.) Because that is what the world needed.
With AI everything has been upended.
And by "everything" I mean everything: how we teach, learn, test, and most importantly, the kinds of jobs we will have in the near future.
With AI, all the "cogs in a machine" jobs are essentially gone. There is no economic reason to employ people when AI will do 80% (and rising fast!) of the work at a fraction of the cost without pesky things like perks, leaves, raises, promotions, or heck, even sleep. Humans will be needed only for the 20% (and dropping fast!) of work that AI cannot do and to keep it honest.
And unfortunately, to get to that 20% we had to go through years and years of the 80% to "pay our dues" and learn enough to get up there; the exact 80% that is usurped by AI. Not only is education hosed, so is expertise building through on-the-job experience.
But! On the flip side, we can now have a dedicated, personalized, omniscient, always-available tutor! Do we even need school or college? Like, literally a 100% of children are naturally curious and exploratory; just that formal education (shaped by understandable economic pressures) is very effective at beating it out of them. What if we free children from the restrictive rails of rote, conventional education and let them explore wherever their interests take them? They could stay home to spend more quality time with parents who outsource work to their agents.
And AI makes it very easy to just do things, and we learn best by doing, so let them do! Would that not be a good way to nurture motivated, practically skilled talent that is truly passionate about whatever discipline they choose, which will be the exact quality needed to drive them to push the boundaries where AI cannot yet reach?
We have to critically examine with brutal honesty what jobs will be needed in the future, wholly rethink from first principles how we should prepare young talent for those, and start adjusting our society and economics to safely transition to that future. I do not know what that looks like, but I know it will be tumultuous and that we must start immediately.
This is Schroedinger's Future, simultaneously terrifying and glorious.
Some people, specially on HN, routinely complain about ads on free online resources. Well, now there are no ads. The resources are gone. "[T]here’s no incentive for people to make high-quality free content." I wonder if this is what they wanted.
I'm surprised it's continued for so long! I've been doing web dev for 30 years and never felt the need to read a text or even watch a video, for me it's just all available in text on the web and always has been because the people building the web are using the web to do it.
I bought some books to support A list Apart, but most of the content seemed to be an aggregation of stuff that authors were already writing about before/after.
curation is very expensive (in time) and nearly impossible to do without already being a SME who knows what's good/bad content. I have spend weeks trying to piece together curriculum for a "free" learning path on some topic I desire to learn. It's exhausting.
In that case, why not just find a good Udemy course after maybe a few hours of research and throw $11 at it when it's "on sale" (I hate the psychology there, but that's a whole other bag of worms) when I just got back from paying $12 at Starbucks?
Of course, I'm not a web dev and don't need full books whenever that tech inevitably comes my way. I love books for my own domain, and several of them are well worth their weight in gold, since all the amazing tech out there isn't just freely available to view with an inspector.
What does education look like 2027 and onwards? My son is graduating soon and will major in Computer Science, with a secondary Art degree.
I have no idea how it will feel to be forced to write code and learn data structures, and SQL, and infrastructure, when it's all right there in 15 seconds with the AI agent.
Does anyone have any experience with this in 2026 specifically? How are the kids doing?
At least with a medical degree you HAVE to study, and memorize. It's part of the job.
As someone without CS background working in a modest app, I think a lot of it will come down to architecture, supervision and direction rather than grunt code writing.
You need to know about database normalization, about algorithms and techniques, ideate solution to problems etc because as impressive as those 1-shot youtube videos on model release look, once you go beyond that, that's where the value ad comes in my experience.
I think nobody knows for sure what software development is going to look like in 2027 and onwards.
I am convinced that there is no fundamental difference between artificial neural networks and biological ones. Eventually, anything a human can do, a computer will do better.
Tech companies have poured trillions into trying to make AI program better and it's still worse than any competent human. That does not give much confidence that computers will be able to do everything better than humans can.
> I have no idea how it will feel to be forced to write code and learn data structures, and SQL, and infrastructure, when it's all right there in 15 seconds with the AI agent.
> Does anyone have any experience with this in 2026 specifically? How are the kids doing?
Here's what it looks like from the perspective of Europe's largest tech company as of 2 months ago [0].
During the various covid lockdowns I started a YT channel to talk about coding and programming, not necessarily only frontend. When technologies such as ChatGPT started to show me that this kind of education was becoming unused, I stopped creating new content because I felt cheated by those AI bros. This is a comment I posted over three years ago where I was expressing my frustration: https://news.ycombinator.com/item?id=35543668#35548305
I wouldn't go quite that far ("death" of web dev ed). there's still a very large gap in certain areas. Two off the top of my head are systems thinking or org psychology; areas that developers could pivot towards as things get more clanker-driven.
I've reluctantly dipped my toes into using AI for development. I make sure I understand the codebase, and I review every line of code that was changed. Honestly, I don't see what would motivate anyone to learn TypeScript, or React anymore. This is not me glazing AI (excuse me, SI) either. Software will only be vibe coded slop after the people who already know how to read code have moved on, and the industry will deserve it.
I saw a couple of interesting new tech books from Manning and Packt and they were AI slop that just appeared out of the blue. So I held off buying them.
There is no guarantee that the authors invested the time in creating the tutorial,book or the course so why would I waste money on that?
Packt? Avoid, avoid, avoid. This is true. Their stuff tends to be slop grenades thrown over the wall. And as you correctly point out, this was the case before generative AI.
My experience with Manning, OTOH, tends to be good. Most of the material I've seen from them was human-written.
LLMs made it easy to skip the BS. Once you know programmingh you don't need hours and hours of content. Just the mental model for and you're good to go.
If it weren't for the job losses I'd never want to go back to 2015 or so to go back and forth on SO questions and answers and spend days on a boilerplate issue.
Eh, combing the internet for ideas, perusing revision history, and finally discovering the cause of a problem was kind of fun. It was a challenge. It was slow, and I understand why business was frustrated by that, but on a personal level I enjoyed it. It had the same rewards as any other game or puzzle.
> Most of my peers who had been selling courses and training were shutting down their businesses
“Nobody’s buying your course bro” has been a meme for years
things people didn’t want are disappearing, the people that would actually take initiative in education have another solution. those error-prone chatbots that the article mentions are good enough. most people aren’t trying to get jobs in the profession, they are trying to make minimum viable web products and landing pages that fit on free tiers, and succeeding
After speaking with programming interns, it's most likely because software development as a career is dead now with the advent of AI. Not because people are using AI to learn.
It sucks for the people caught by the change. Honestly, I’m sorry. But rapid, disruptive change has always been part of working in technology. The industry doesn’t owe any particular job category permanence.
I think the more interesting conversation is what happens to the learning industry now. If AI changes how software is built, then teaching people to become developers has to change too.
We shouldn’t be asking how to preserve the old pipeline of teaching people to write code so they can get an entry level programming job. We should be asking what it means to teach someone to become a developer when AI can increasingly write the code.
The scarce skill may shift from producing code to understanding what should be built, decomposing problems, designing systems, evaluating tradeoffs, debugging complex behavior, verifying AI generated output, and understanding whether the resulting system is actually correct, secure, maintainable, and fit for purpose.
That doesn’t necessarily mean fewer people need to learn software development. It could mean many more people can become capable developers because the mechanical barrier to producing software has fallen dramatically.
The educational model just has to catch up.
The technology changed. The answer shouldn’t be to pretend it didn’t. It should be figuring out how to use it to produce the next generation of developers.
That’s going to be contentious for some people, even a little insensitive. But it’s just how it works in our industry.
the people are good at using AI are the same people who are good at developing software systems. traits like curiosity, knowledge-hungry and desire for continuous learning are not common in the population, so eliminating the coding barrier doesn't magically increase the number of people who can become capable developers.
I am genuinely starting to fear an almost universal dumbing down of humanity as a result of AI. It feels like so many people have just stopped caring about what they do or what they create. They no longer believe they need to know what they are doing or care about the results. The machines will do the knowing and caring for them. Or they won't - but what they produce without knowing or caring will be good enough to tick whatever boxes are necessary so it doesn't matter.
Over the years I have enjoyed many deep and interesting technical discussions online - both here on HN and elsewhere. I can't help feeling that those discussions have also all but disappeared over the past few months - alongside high quality free material that some experts have kindly given away but increasingly no longer do. I rarely find myself contributing any more because there is little on any of my usual online hangouts that is interesting enough to spark a deep technical discussion any more. It's 90% AI stuff - either written about AI or (usually poorly) written by AI - and most of the discussions that do initially catch my interest at all seem to end being very negative and depressing. (I appreciate the irony that I'm perpetuating that cycle right now. Looking through my relatively sparse recent contributions to HN is actually quite depressing. Although at least I actually am getting out more!)
I wouldn't mind so much if I believed the hype about the benefits of AI-generated work and thought that overall this period would be a net win for humanity. Unfortunately I don't really believe that. I fear the LLM era will eventually be remembered for producing tools that could do average/routine tasks quickly and to an acceptable standard but that were actually used to (try to) do good/innovative tasks with substandard results. But by the time enough decision-makers realise this it might be too late and the damage might already be done and hard to reverse.
Your comment is even more depressing when you realise this applies to other elements of our daily lives, including but not restricted to oil, environmental management, societal support...
Funny how our short feedback loops and greed pushes people towards deeply unstable systems, especially if the price seems so "cheap" for a reward sold as so incredible that it would be dumb not to bet on it...
I'm on the same boat, negatively affected by AI. I'm the CEO and founder of an EdTech company and our B2C revenue has greatly decreased as a result of Gen AI.
But unlike the author of this post (or cited authors) I'm not sore. AI is providing a much better education model for students. So it's us that we have to adapt, not complain that the world is changing.
For example, in Machine Learning our projects are sometimes extremely long and repetitive. Because before AI, it was a valuable skill to be able to recall APIs quickly (what is the method to drop duplicates in a dataframe again?).
But today that's no longer the truth, and for the better. I am happy students don't have to go over the same repetitive low-value processes that I had to go to. Students can now focus on more high level valuable tasks: understand the domain, compare evaluation methods, compare models, balance tradeoffs, present solutions/reports, etc.
It's like in the 50s when students had to memorize tables of logarithms. Nobody misses that.
We are in the process of recreating all our projects to adapt to the new world. We'll see how it goes.
> But today that's no longer the truth, and for the better. I am happy students don't have to go over the same repetitive low-value processes that I had to go to. Students can now focus on more high level valuable tasks: understand the domain, compare evaluation methods, compare models, balance tradeoffs, present solutions/reports, etc. It's like in the 50s when students had to memorize tables of logarithms. Nobody misses that.
Maybe when it comes to any coding-related learning, I can agree with that point.
However I think the future of education in general is very bleak. When we have plummeting scores for the PISA exam across the world [1], I fear people will get dumber and dumber.
There will always be those who thrive, but the easier it is to obtain information/knowledge, the less I think people have an incentive to do it. And I don't buy that AI will solve all intellectual jobs anyway.
[1] https://www.dw.com/en/pisa-2026-results-reading-math-scores/...
> However I think the future of education in general is very bleak. When we have plummeting scores for the PISA exam across the world [1], I fear people will get dumber and dumber.
This is exactly what AI companies need, so that's development should be celebrated. There are two paths to capture the value that's currently wasted on paying people:
1. Build a system that's superior to nearly all people.
2. Make people worse, so even an inferior system is superior to them.
Getting AI into the classrooms and degrading the educational system are important for path #2.
It's good not to put all your eggs in one basket, so I'm glad the AI industry is pursuing a multi-pronged strategy against their competitors. Who cares about the waste and destruction for humanity, as long the investors get good returns?
Paul Graham would be proud...
Ah, yes! The classic Socrates play.
Learning to write will either help all the humans by extending their capabilities, or will make them stupid -and dependent on writing.
Socrates: It will definitely make them stupid, and I am suspicious of this new witchcraft.
Maybe he was right, but I’m kind of enjoying having both writing and AI around.
PISA exam scores are a lagging indicator with many years of lag. I doubt the reason of that is AI. Mobile phones? Social media? Any other multi causal reason (poor eating, anxiety, low testosterone, whatever), most likely, but not AI.
If you think that’s a lagging indicator, the many reports from teachers and from self reports from students and even adults trying to learn also point in the same direction. See what’s happening with exams and homework exercises.
Education itself has lost access to the tools that were making it cheaper and easier to teach.
Learning something is a side effect of overcoming friction. AI removes friction.
Doesn’t that depend on the friction?
I’m using ChatGPT to learn German. I can immediately adjust its responses and language level(it says I’m at A2/B1) and tell it how I want to study.
I find it to be a far superior tool than anything else I’ve used.
Has everyone memoryholed the COVID Pandemic?
That wasn't a proximal cause.
May as well introduce another factor to make it even worse ¯\_(ツ)_/¯
People have been using chatbots to cheat on schoolwork for a few years now
The pitch is learning useful things (if not skills) but we end up using schools as storage for kids, for indoctrination and as a business model. The ratio gradually changes.
We end up with shit results and where they arent shit students are rushed though as if to prevent them from thinking about the materials.
We have libraries full of unused education formulas. Some 2000 years old. Then there is nutrition, sleep and other work/rest ratios, physical health.
How expect results without learning to teach and learning to learn?
Onto what should one anchor learnings if the suroundings are always the same?
I never hear a word about spaced repetition in school. Its so basic i must conclude they knew nothing about what should have been their area of expertise.
When things get bad enough we will [finally] have reason to improve.
Maybe the great work of Salman Khan is merely a hint?
We know about those things and they don’t work the way you have laid out. For example spaced repetition is ideal for memorizing words, but less useful for working through a math problem or creative writing (relatively speaking.)
MOOCs were something I personally hoped were the solution to scaling education. However it didn’t work out, with courses having single digit completion rates.
This is for free, high quality, immaculate pedigree, learning material available at any time and any place.
Years of additional research had to be done to figure out how to raise completion rates, which creates more complexity on systems and delivery.
Unfortunately, that improvement is now moot, because LLMs obviate the friction and effort.
The point of doing a homework exercise is to provide learning friction for students.
LLMs obviate friction.
I would add Bloom’s 2 sigma problem to the mix.
> When we have plummeting scores for the PISA exam across the world...
COVID generation.
The pandemic was barely 3 years ago, and stretched over 1-3 years depending on where you lived.
It will likely have a material impact on most developmental statistics for another decade.
> For example, in Machine Learning our projects are sometimes extremely long and repetitive. Because before AI, it was a valuable skill to be able to recall APIs quickly (what is the method to drop duplicates in a dataframe again?).
> But today that's no longer the truth, and for the better. I am happy students don't have to go over the same repetitive low-value processes that I had to go to. Students can now focus on more high level valuable tasks: understand the domain, compare evaluation methods, compare models, balance tradeoffs, present solutions/reports, etc.
You honestly believe that students that don't have the tenacity to stick with learning a simple set of verbs and grammar are going to have the tenacity to learn concepts steeped in jargon?
I do mean learn, which AI use has been repeatedly shown to be detrimental to.
What a great perspective to have! Completely agree with you and I want to add on to it by saying mentors will always be valuable because students have always had access to information even before AI, if you think about it. It's organizing and packaging it in the right format that's always been the key issue.
" It's organizing and packaging it in the right format that's always been the key issue."
LLms dont help here either.
Part of learning is about struggle. Seems many here want to disregard that fact and just run to the LLM lmao. Yeah you can do that - the knowledge won't really stick.
Sorry, I think you misunderstood, I'm saying the same thing, LLMs don't package information in the right format, but good mentors do.
But it becomes different knowledge. You learn how to manage an LLM to create the thing you need instead of writing code to do the thing you need. Still a learned skill. In some cases, still a struggle.
The initial creativity is still with us, not the LLM. It's the Art/Craft thing - we have the Art, the machine does more of the Craft (and it always did do a fair amount of the Craft).
I'm seeing folks who couldn't (for whatever reason) work out how to code, starting to produce some amazing stuff with the LLM doing the coding now. It's their creativity, their project, their vision, still. The fact that they didn't write the code is meaningless.
That is teaching familiarity with AI tools, having given up on the thing the student was supposed to learn.
From what I’ve seen, the ability to prompt quality output with AI is entirely proportional to experience and skill level.
Yes. And I want to hire people who can tell when the LLM is right and wrong.
>But today that's no longer the truth, and for the better. I am happy students don't have to go over the same repetitive low-value processes that I had to go to.
It's a real shame a leader of an education company doesn't value the actual learning process. Those "low value" processes are the building blocks to understand and master high level concepts. I'm not spending my day to day thinking about the low level memory allocation in my job, but that knowledge and work helps immensely in how I approach the higher level assignments and wider architecture. And I still kick myself because my assembly knowledge is is only 1.5 semester's worth.
And yes, I still look up how to construct an array in C++. Not really because my memory is bad (okay, kind of), but more for the practice of reviewing API's and parameters and maybe making new revelations. I probably knew internally some 12 years ago I could set an initial capacity in one of the array's constructors. I didn't really "understand" the value in that until one random work day 4 years later as I was working through some in-house container packages.
You can even say that doesn't matter if you know what resize() is, but it's those little bits of learning nuggets that builds you up from a "fine engineer" to a "great engineer". Less the knowledge and more the work ethics built to obtain it.
> before AI, it was a valuable skill to be able to recall APIs quickly
That’a the low value they’re talking about. And all of that stuff is accidental complexity.
To use their example, you need to know that dropping duplicates is a good idea (and why). Knowing what the syntax and api calls to do that is, in my opinion, unnecessary.
That's not accidental, anymore than human language itself is accidental. APIs are designed very intentionally, and a good API's parameters have architectural reasons behind what they include (or exclude).
Even your example has unintentional complexity. A 'duplicate'? What's that? Do we compare the memory it points to? Through use of a custom comparator function?by an id or tag? APIs and entire languages are designed around how we define such seemingly simple terms.
Ultimately a language, be it a programming language or human one, is about communication. I find there to be value in knowing how to communicate effectively, even if employers increasingly disregard the value of such knowledge. Without it, we'll quickly find out why it's fundamentall quickly.
As an educator and author, I feel Molly's pain (Anthropic owes me $60k for pirated books). My course and book sales have dropped significantly. I feel like much of the value in my book-based knowledge is harder to discover in AI agents. (One example might be inspecting SHAP values from XGBoost models and using that as feedback to feature engineering for a linear model (like Logistic Regression)). So I'm afraid more advanced techniques might go by the wayside in the name of delivery speed.
I use AI both in the cloud (I tend to avoid Anthropic...) and with local models.
I've probably written more code in the past year than in my whole career. I can now create what I desire (I just created a telemark skiing game over the weekend based on my Strava segments). I think this has helped my teaching as well. In a recent ML course, I created many interactive examples that in the past were just doodles on my whiteboard, but are now embedded in the notebooks I give students.
I've also taught a few AI courses to clients as well. However, with the inevitable rust/ASM-ification of everything, I'm not sure how long those skills will be valid. I do, however, think that having a human in the loop for ML and data analysis is still important.
The people reaping AI's benefits today generally developed their skills as juniors through old-fashioned struggling in the pre-ChatGPT era -- actually reading docs and articles, trial and error, puzzling over mysterious bugs, and generally doing lots of mental lifting.
How will skill building happen when LLMs and coding harnesses seemingly provide all the answers at one's fingertips?
> How will skill building happen when LLMs and coding harnesses seemingly provide all the answers at one's fingertips?
They don't provide all the answers. And are often wrong/mistaken. But they also produce stuff faster than you can consume it. This is great for when you know exactly what you want and can cheaply test the output and guide the LLM to the right solution. It is expensive (in developer hours) in other cases.
I have been building a new PL+VM this year and had to pause development on a few occasions because I have not had the time to go through the implementation because there are so many modules. But smaller tools (5-10KLOC), you can judge fairly quickly.
So, the answer to your question is: people need to discover the strengths and weaknesses of the tool on their own, decide what kind of expertise they want to attain, and if it is worth the effort.
That's a great question. I don't know what the future will be like, but looking into my crystal ball, I'm not seeing much hand-generated code. Very little (or no) human code review.
Having the taste and business sense to develop the right thing will be important. If it stops working, ask the AI to fix it.
> That's a great question.
People have been asking this for a couple of years already. I have yet to hear a real answer beyond "We'll cross that bridge when we get to it."
While this may be true, there are certain types of development (rockets and kernels come to mind) where you will always need highly skilled people willing to be responsible. LLMs excel at many logical tasks but they struggle with creativity and responsibility.
At least, so far.
How will people learn to ride horses, when everyone drives a car? They generally won't, because that is now obsolete.
How does it work when the skill is _thinking_, which is not so much a skill as a basic component of being a functional human?
The ubiquitous "LLM slop is the car and thoughtful development is the horse" analogy makes me think of Steve Jobs's "Bicycle for the Mind".
https://www.themarginalian.org/2011/12/21/steve-jobs-bicycle...
So I teach a couple of web architecture classes, and it’s been my experience that there is still a desire to learn how to truly build quality systems because they want to learn how to build quality systems.
I think our industry needs to transition to figure out what does it mean to build a quality system in the age of AI? It’s one thing to vibe code an application that works. But would you depend your livelihood on it? Would you get business funding and base the future of your team on it?
I think the challenge of the educational space is to figure out how to teach the judgement to build solid systems without relying on “hand coding”. For me I’ve been working on technology agnostic composable frameworks that help build that judgement. But honestly we are all just figuring this out together.
There will still be a need to be able to train system builders, the question really is what do they actually need to learn to be solid system builders in this AI era. And there’s a strong chance that pure programming language or tech stack learning may not be enough. This is what we educators need to figure out.
> But would you depend your livelihood on it? Would you get business funding and base the future of your team on it?
Yes. I stopped looking at the code about 9 months ago. It's easier/better/quicker to learn how to get the LLM to audit the code.
Investors don't care if the code is LLM-generated, they're mostly assuming that now anyway. The VC's I've talked to recently are screening pitches using an LLM, they're embracing this tech.
If I recruited a new dev to the team now, I would expect them to be able to run multiple agentic coding instances simultaneously. I would not expect them to be hand-crafting code any more.
I agree with you no investor or user cares how the code is built, and actually there’s nothing wrong with using LLMs to code. LLMs are the way to code now absolutely.
But, investors do care about the stability of the system they invested in. And how quickly it can be extended and expanded upon while still maintaining functionality. And they deeply care about scalability. I don’t believe this is a question about whether code is LLM generated. I think this is a question of having the ability to build a system that can be up and provide the value that investors expect. And the way you use AI and your knowledge of systems does play a role in that, especially over time.
And another point: it doesn’t have to be either or. Sometimes the prudent thing is to hand code a specific highly sensitive part of the system while your agents are building other things. The fact that these agents can do things in the background frees us with different possibilities. And also, sometimes hand coding some areas in the code that you are not familiar with builds your knowledge which the ln enables you to guide the agents more effectively later on. There’s benefits of both approaches and both approaches can be done simultaneously.
I tried, and realized that once I closed the tab, I had no idea what code had been written.
I had to go back to writing code to actually have it register.
Learning is friction. LLMs remove friction.
Agreed entirely. It is the birth of true software "engineering" for the masses rather than the pile of coders we had before.
Nobody is mentioning the other side of this. Technology creates all of those jobs too. The field of web dev, and the ability to earn an income from as ebook was awesome. Things change and what we should doing is going in eyes wide open.
Founder of Boot.dev here: the industry is absolutely having a VERY rough time in 2026. Our revenue in particular is actually up in 2026 vs 2025, but modestly low double digit percent) vs 2025 being nearly double 2024. That said, I feel we're an exception in that we have been able to grow, mostly due to a complete doubling down on high quality human content, and trying to build experiences you just can't get from plain text (interactivity, animations, etc). time will tell.
But isn't this (interactivity, animations) exactly the kind of stuff someone already familiar with a concept would turn to AI for yet another interactive visualization that might help develop intuition?
That's at least what I do. Sometimes it feels performative at best, other time I get genuinely new ideas by having a vague thought turn into a tweak able viz.
I tried creating a similar concept at https://www.codembark.com but felt it would be too hard to monetize with the headwinds of AI. I ended up just getting rid of all of the paywalls and just offering it for free.
Thanks for boot.dev, it's the one website I regularly point my students to when they ask about places for supplemental programming education. I hope the genAI bubble doesn't put you out of business like it might do for us in traditional academia.
I'm taking courses at my local college (heavy duty diesel tech) and I'm finding how little use the teachers is for me. I got a digital copy of the textbook, and downloaded all the courses notes, pumped that into claude and made a discord bot that generates me quizes, tracks all my progress, and builds me a study guides off the results.
Superior to any teacher I've ever had, no matter how involved they are. I genuinely don't even see what my teacher is needed for beyond a requirement for me to be there. I can ask the bot "can you clarify X section" at 3am and it'll do in 1 second. In class, the teacher reads the slides, adds some extra points and takes questions. But my bot does all this, completely personalized to me.
Times move on, and I don't see teachers surviving. I'm hoping by next year the college will offer an "at home, self paced course" option. Theres no reason for me to be there.
> Superior to any teacher I've ever had
Have you independently verified your learning?
AI is moving fast, so I'm very open to the suggestion that Claude can do today what it couldn't six months ago. But my experience with folks who are learning from AI, historically, has been that they have high confidence in abilities they are not able to demonstrate when asked to show mastery through conventional problem solving.
I teach many data/ML courses for clients using their data. It is amazing how many insights both the students (as SMEs of the data) and the teacher (as an SME of the techniques) can have when going through certain techniques together. Quite often, we get a "those last 5 minutes more than paid for the training" insight.
I think that is possible with AI (I haven't experienced it), but I also feel like most folks use basic/naive/cursory techniques when using AI because they don't know what they don't know.
This has been my experience as well as someone who uses the frontier models quite a bit, I think it's easier than ever to deceive myself into thinking I'm being productive or learning. I've noticed it in others as well.
Part of it is shear volume of "stuff" that I'm doing on the fly while leaning on AI as a crutch for speed (otherwise why wouldn't I just do it myself), the other part is that it's ephemeral, even if you read all the lines of code, it's hard to beat manually typing them yourself for retention _and_ failing at it, and being forced to teach myself what I did wrong.
All that's to say, I think AI psychosis can happen at a group level.
edit: misread your post.
I do, all the time. I get test, do good and then the college signs off that Im a certified mechanic when Im done.
Maybe its more of a critique on the school, but no one tests you on your ability to disassemble an engine and rebuild it. They simply make you write a test based off terms you learned in a textbook.
This was exactly my experience in high school, university, and now the same in college.
I would of killed for this bot during my math courses in university.
> no one tests you on your ability to disassemble an engine and rebuild it. They simply make you write a test based off terms you learned in a textbook
Out of curiosity, where–geographically–are you going to school?
If you're able to pass you theoretical tests without AI, it's fair to say you're learning what's being tested.
Canada
Its the job of the labour market (firms) to determine who is of value - after they've let the grifters who are well-connected in.
reminds me a lot of my learning process. I read fast, seemingly picked up concepts quickly, can answer some sample questions. I felt fairly prepared, and honestly most classes were a breeze with that.
Then, for better or worse, I was pushed to honors and AP classes in high school. The same methods didn't work there. Things got more abstract and I needed to connect multiple concepts together. Math drills turned into word problems that revealed weaknesses in my older math fundamentals. reciting facts from a required reading wasn't enough; I needed to know what that meant and understand the setting of the book.
My grades suffered and you can argue the "academically optimal" way would have been to not take so many advanced classes. But those experiences definitely helped me to critically think better. Eventually (My English and History appreciation would come much later. Math and Science trained me well).
It is also a shame how much the quality of the teacher can affect this experience and perception of education as a whole. I wonder if those enthusiastic to replace the teacher ever had one that fit their needs?
And are you learning whatever you are learning for personal gratification or hoping to use that skill for survival? I am asking because the way I see it, just like the teachers, everyone is becoming useless.
The issue is a shitty teacher or curriculum.
Teachers and schools need to let LLMs do the things they are better at, and concentrate on having instructors do the things that LLMs cannot. Teachers that only read from the slides have always been a problem.
Your instructor should be having you dismantle an injector pump or bleed an air locked injector rail. You can read a book about how to do that, but you won’t really know how to do it until you’ve done it for reall
I agree. However, the majority is theory. It's probably 80% theory, 20% practical.
Correct but more so the lack of access to great teachers.
LLMs are not the solution to providing the best teacher at scale that people think it is.
I thought the same until I had kids. I realized that kids generally want to learn, but they usually think what the teacher is telling them is not the best thing to be learning. No technology, not even AI, overcomes the student's ego; in fact, technology rarely even tries to address that issue. I think this often applies to adults too. Teachers continue to be necessary to help students achieve an appropriate level of humility to be able to learn.
You clearly have enough humility in your field to be able to soak up knowledge. That's great for you! I suggest your dedication is rare and teachers continue to be essential for society.
> Teachers continue to be necessary to help students achieve an appropriate level of humility to be able to learn.
I never saw a teacher that managed to do that. Not to any of my classmates, nor to me.
I don't know if my statement would apply to grade school kids. They have completely different requirements. I'm mainly referring to post secondary.
I think you Chesterton's fence'd teachers.
This comment is disgustingly depressing
Formal education has more than just an instructive role. In fact, it's everything but the instruction. Reciting content to learners doesnt necessarily help them learn.
Teaching should turn into conveyance of taste. The teacher should help figure out what needs to be examined and how to examine; help figure out ways to close the gap between the textbook and reality. AI can't do those things well yet, and perhaps it never will be able to.
Sadly, the truth is that in school, you're only rewarded for what you vomit back up on the test. Rote memorize some formulas and facts, copy those back on the test and you're now a certified mechanic/engineer/doctor/whatever. That's exactly what got me through math courses in university.
Sucks, but its true. In my case, if there was a test that required me to disassemble an engine top to bottom, claude would be mostly useless.
In my experience, that was pretty much true until I started doing small discussion-group-style graduate classes. But those are necessarily capped by staff-to-student ratios.
I agree with this point.
Maybe all education will get more and more similar to e.g. learning an instrument.
You can get everything from YouTube videos, sure. But a good teacher will help with things like knowing how to get a good repertoire for your skill set, what bad habits not to develop that will cripple your ability to learn more complex pieces over time, etc.
I think expertise in hard subjects will only become more and more valuable (as always), and thus harder and harder (and more expensive) to achieve.
Not for the person who's making it and accruing the benefit!
The perceived (i.e. self reported) benefit.
I have a feeling AI is hitting all the same dopamine receptors as your attention grabbing apps and video games, is highly addictive, and is merely making you feel like you are achieving something. Sort of like DuoLingo.
The problem is, I write my tests and do great! So, this is working. It is exactly what the college is rewarding me for.
If I was using this AI and my grades were poor then I'd agree, that its perceieved but its provably working.
We see the same at my university. It's sadly the reality of it.
We are kind of envisioning that university will be a place for social activities, mingling, rich people meeting partners, etc. So we are moving towards more of that.
Speaking as someone who never learned well from courses and always preferred documentation and 'just doing it': I wonder how much of this drop is 100% LLM usage by devs vs. devs realizing a lot of video content was just padded out anyway.
> a lot of video content was just padded out anyway.
When you hear the phrase "but first we have to go back to..." on YouTube, you're entering a filler section to allow more ad content.
The mentioned 2ality blog by Axel Rauschmayer was an extremely detailed and thorough look at TS and JS specs. So right up your alley. Same with Josh W Comeau.
https://2ality.com/
https://www.joshwcomeau.com/
I for one mourn the loss of these and other blogs and am not exactly sure the trade was worth it. Not with the cretins in charge.
Well as someone who got a ton of value out of tutorials and would go back to the documentation and "just do it," I wonder how much this is really actually just LLMs as we're all seeing out sites bombarded with bots ¯\_(ツ)_/¯
The traffic to my blog and my books (which were free to read online) increased beyond what I can currently afford.
That’s a shame. I’m surprised someone so well versed in web technologies has such a brittle setup. Cloudflare Pages, or if you you’d prefer to stay CDN-less, a $4 VPS, will handle any sort of traffic this blog can reasonably receive.
expensive and brittle are orthogonal
People here seem incredulous that others would learn from a video series, course, or book, but I've always found this content extremely valuable and would continue learning from them even now. I learned the basics of async programming through learning about AJAX from Jeremy Keith's book on the subject, I dove very deep on JS itself from Secrets of the JavaScript Ninja, Cocoa from BigNerdRanch, Much of Swift and SwiftUI from John Sundell's writing, tutsplus, HackingwithSwift, Grid and subgrid from Rachel Andrew's writing. As a largely self-taught programmer, these resources have been absolutely crucial, and in retrospect it was a mistake to conflate the ability to find any information I want in discrete chunks with actually learning parts of a subject. I've also only rarely found University level formal courses to be as substantial in terms of what's actually useful to bring with me into practice. LLMs are more sophisticated in many ways, but if I want to learn something, I need to approach it more seriously than modern tools would have me believe. LLMs are great at letting me skip over the learning part, and they're great at helping me explore the problem space, but they're not what I'd turn to for educating myself on anything I care about, in much the same way that listening to a podcast or watching a documentary does not qualify as education, nor does it replace reading and/or physically practicing something.
Web development, as much as some would like to think, is and has always been, complex.
I haven't tried learning Rust yet, and I'm sure as hell not going to lean on an LLM at all when I do.
I've written for a range of front-end publications. This year they've all cut down the amount they're publishing, started slopping out articles, or gone quiet altogether. It is rough. Speaking as an author, even those that seem 'fine' at a cursory glance now feel strained behind the scenes. It makes me so sad.
I considered myself to be a web developer in the 90s and early 00s. Then things began changing very quickly into something I didn't recognize. I came from an era that did layout with table tags! I felt like an old dog having to learn new tricks. I chose to pivot into statistics rather than adapt, though I've since come back around via data science and systems engineering.
I don't think what's happening is a uniquely AI phenomenon. If it wasn't AI, it was going to be something else. The ground is always shifting beneath you. It's happened to me in multiple fields through my career. You adapt or you pivot. Like a startup.
For many people who feel negatively affected by AI, my advice to them is to do what I did when my professional disciplines changed to something I didn't recognize: pivot. The great news is that AI makes it really easy to be a beginner in a new adjacent field.
I come from the same era. Learning new languages and frameworks is nowhere near the same ballpark as having the whole ground your business was built on pulled out from under you when it comes to "just pivot."
Fair, though I'd argue businesses are even less entitled to operating the same way long term. I haven't stepped foot in a department store in years. Disney isn't making movies the way they used in Walt's day.
I can get why they're mad about it, but the reality is that chatbots are better/easier to learn from than courses and tutorials.
If I had a question about a new library now, I wouldn't google for a tutorial, I'd just ask ChatGPT.
This implies that you know which question to ask. If people don't know about accessibility, security etc. How are they able to learn? Also, most people don't use AI to learn but to do it for them.
That's a good point, but if you have an always-on agent focused solely on helping you improve your knowledge/skills, it can ask you questions every day and gradually identify gaps in your knowledge and it gets really good at knowing where to push you.
I'm experimenting with exactly that: https://miletus.app
That's where books come in. Read them, explain what you're learning to the AI, and what interests you about it, ask for it to check your understanding. Explain your other interests, ask it to suggest other things to read which will bridge the gaps between what you're learning now and the other things you already know.
I mean, the frontier models are pretty damn good at giving you all the standard conventions on things... The first question I usually ask is "give me the all the modern day conventions for this use-case", and then I start the context building from there. This applies to a lot of things, but I mainly use it when I am coding.
And yet I gave to spend considerable time getting Astra not to use useEffect for no good reason.
You can ask the AI what you don't know.
I think it's twofold, there are less people willing to learn the trade when most of it can and has been replaced by llms.
Learn from bots or get bots to do things?
Honestly both.
I suspect a lot of people who formerly might have been interested in a web dev tutorial now just an LLM to make them a website.
I'm still doing hybrid coding, half LLM half manually. But every new LLM does more and more of the job...
I constantly get dragged into web tech from tangential projects. I still found it valuable to take the time to learn Electron (and update my front end knowledge) properly to do a port of an Electron app for a slightly different context.
I used AI to extract the raw frontend structure of the app because I know I can't design to save my life. And I still need to tweak it quite a bit because the interface was always janky (a desktop app but content is overflowing everywhere, and it definitely can all fit in a typical full screen view). But the act of structuring that stuff into a modern framework and hooking up the logic will still come down to me.
I definitely understand the uncertainty and frustration with a field changing beneath you, and the distastefulness of a lot of the content made with agents. But I think this is going to be a short lived sentiment. I only recently started using claude code because my earlier experiments resulted in more time instructing the bot than working with the code.
This time my approach was better and so was the capability of the model. I can make a small change in one place and have the model propagate the change throughout the codebase. I'm still working directly with the code, and the agent doesn't have to make any important decisions about structure (which remain generally terrible). My familiarity with the codebase is the same as if I had made each edit myself.
It is definitely possible to build faster and better with an LLM and not give up control or the enjoyable part of coding. The energy in this space still seems to revolve around guiding the agent or letting it take over, the key is ignoring it entirely and discovering what works for you.
the older your brain, the less plastic it is! lets remember what it might have felt like for you to write your first BASIC program or hand-code your own HTML website. there was a desire to understand :: HOW IT WORKS? HOW DID IT DO THAT?
just because our old-brains did it "the hard way" and now we have these LLMs that can just make it happen, doesn't mean that our little ones want to/should skip the steps of understanding HOW IT WORKS
me and my kids have been making all sort of silly games and my oldest is starting to wonder HOW DOES THAT WORK, PAPA??? and i'm like, well, let me show you this...
a magical thing! what a time to be alive!!! there is joy, but you have to conjure it!!
I used to listen/watch some youtube channels for learning. Especially as a newbie, I used to listen to the channel - Programming with Mosh (5M+ subscribers). I see that he has stopped producing videos regularly. Last one year, he produced only 3 videos. There could be other reasons. But I suspect lack of interest from viewers because of AI.
The real question is who was still buying this type of book in the last decade or two? What value were they getting out of it? Was it being used as reference or training or what?
If you haven‘t been paying attention you will off course miss the good stuff out there.
Rachel Andrew’s (mentioned in TFA) for example has The New CSS Layout (2017) https://abookapart.com/products/the-new-css-layout.html an excellent book I still recommend for anybody who want to learn about modern CSS layout.
But if you are this dismissive of the field of course you will fail to see the value of them.
A lot of people take pride in not being able to understand CSS despite it not being that complicated.
I’ve never understood that but for some reason it is a thing
A lot of people also took a lot of pride in not knowing their editors very well, and just the very basics of git. It's no wonder LLMs are so popular.
A Book Apart shut down and says all copies have been sold. They suggest reaching out to Rachel Andrew directly to see if the book is available elsewhere. (Her website just links back to A Book Apart).
Who's being dismissive? You can't figure out where your customers went if you don't know what value they were getting.
> commodifies knowledge, instead of teaching skills and deep understanding.
I'd gently submit to the author that these are not opposites. Knowledge commodification is good, and so is deep understanding.
Good article.
Around 10 years ago I used to worry a little about keeping up with younger folks. I only really started using computers when I was 9-10, and didn't get the internet at home until my mid-teens. I thought there's probably kids learning JS at age 6 these days... These kids are going to be almost super-human in their technical skills compared to someone like myself who didn't learn HTML until their early teens.
But then around 2020 I realised kids actually have no clue how to use computers because their primary computer is a phone or a tablet. And there only experience with desktop computers are Chromebooks at school.
Now I suspect my generation will be the most knowledgable technical generation by far. The only issue for us is that no one will care.
As someone who used to write a lot of tech tutorials and has published a technical book, for me it's much less a financial thing and much more just sadness that something I spent a lot of my life doing, that used to generate emails every week from people saying thank you for helping them is now just completely worthless. I've spoken about this before here, but I feel like I've lost a large part of myself over the last couple of years because almost everything I used to do in my spare time now seems completely pointless.
This is quite weird that "AI" presumably ruined book sales, since the info from the books were mostly available though the search.
You want it structured? You need the book - "AI" won't solve it for you (well, if we discount cases of word for word reproduction... which we probably shouldn't, but this does not seem to be the argument here).
The kind of people, that read the books, are the kind of people that largely won't settle for a chatbot as a replacement.
Can there be another reason for the sales drop? Unemployment, "death of the junior", wages decline?
Slightly disagee.
Personally, I read way less traditional books when it comes to learning stuff. Especially the “utility”/“tutorial”/“handbook”. Top nitch books talking about general principles I’d still read.
Especially for books that need to teach me a subset of a certain discipline - in the past I’d get 4-5 (or at least samples), and try to find the parts that are of interest to me in a style that fits me. Novadays I’d just ask Claude to explain things in a form that I like, with pretty illustrations from Imgen :)
E.g. I don’t think I’ll read the animal books from O’reilly again. But an equivalend of “Thinking in C++” or “Pearls of programming” of a new field? Sure.
Economic headwinds and the collapse of tech labor would definitely impact people's willingness to learn tech, especially on their own time with books/courses. I'm not sure if it's enough alone to cause yearly 50+% declines, though.
AI for sure impacts ad revenue. It's an absolute mess trying to measure proper web traffic anymore, and it' been shown quite a few times how AI summaries in search impact page clicks.
It depends on whether you bought books to learn or bought books to solve.
There are a vast number of books that I purchased not for any interest in the topic, but to solve a particular problem. I have zero interest in understanding Docker. I find it tedious. But I do have a book on it as I did need to know it at some point.
I wouldn’t buy that book today, as AI means I no longer need to know Docker.
> The income from my book sales went from being enough for me to live off (2024) to zero (2026).
> The traffic to my blog and my books (which were free to read online) increased beyond what I can currently afford. Virtually all of it comes from AI crawlers, so there is no ad income.
I know correlation is not causation, post hoc ergo propter hoc etc. etc. But these circumstantial evidence are too strong to simply ignore... As it stands AI is the obvious culprit. And with the current evidence, it is perfectly reasonable to blame AI and nothing but AI.
Most of the stuff these Ed-Tech companies taught is counterproductive. Much of it was unnecessary solutions to problems that didn't exist. So so many Web tools are things created because their creator didn't properly understand HTML, JavaSript, CSS and the DOM. Then these schools taught everyone these unnecessary things and they become the standard and made things overly complex and give us massive build times for stuff that was never meant to need a build phase in the first place.
LLMs with HTMX and plain old CSS and JavaScript (maybe Typescript) is the future. Getting back to little to no build times and frontends that don't take up 1+ GB of RAM on the clients
What Ed-Tech companies? This article isn't talking about Ed-Tech companies. Axel Rauschmayer isn't an Ed-Tech company. He's an individual author who wrote books about JavaScript, the language. He wasn't pushing these "unnecessary solutions", he was helping developers understand JavaScript, exactly the thing you say is necessary. Josh W. Comeau isn't an Ed-Tech company, he's an individual who writes content about new CSS features like Anchor Positioning[1]. What do educators like this have to do with 1+ GB RAM frontends?
[1] https://www.joshwcomeau.com/css/anchor-positioning/
I've personally been using a Phoenix LiveView-like approach extremely successfully, combined with LLM coding. It is extremely, stupidly fast. We are talking about loading an entire multi-window desktop environment in the web on spotty 5G networks in half a second, transferring less than 1MB of data.
I think traditional web frontends might be dead for any applications with servers that can afford to keep server-side state of a logged-in user.
(Notably this includes almost any kind of AI application, because the LLM costs dwarf the web hosting costs anyway.)
And for the stateless ones, there's always htmx
what do you use for this approach? or you just let the LLM come up with the whole implementation without any frameworks?
As a bonus, you can become the president of HTMX.
>LLMs with HTMX and plain old CSS and JavaScript (maybe Typescript) is the future.
1. LLM webpages in my experience have definitely not gotten simpler, nor load faster. It just pushes out more of the same junk underneath without any of the oversight we'd give a human
2. I'm not even sure the webpages are the big resource hog anymore. Chromium itself has had the reputation for eating RAM for well over a decade at this point.
3. In many ways, we did this to ourselves. In the name of shipping faster, we (or perhaps the executives) outsourced solutions that would sacrifice the simplicity of the code for "more mainainable, cross platform" frameworks. Electron was a solution for software companies not wanting a dedicated Windows and Mac (and perhaps Linux) team. React was a very specific solution for one of the largest websites in the world, that the rest of the industry adopted as a trend.
It's over guys. Web Development (1994-2025) will be remembered like elevator operators. What it transforms into at this point is still an open question being actively discovered. But our vocation is dead and gone as it was.
> Web Development (1994-2025) will be remembered like elevator operators.
Good.
Education as we know it is doomed. But we have to realize that all our education systems were shaped by the means we had available to us in the past for imparting education, learning, and testing knowledge at scale, and critically the kinds of jobs we were being trained for. To put it bluntly, the entire system was tuned for producing cogs in a machine. (Or just bricks in the wall, if you will.) Because that is what the world needed.
With AI everything has been upended.
And by "everything" I mean everything: how we teach, learn, test, and most importantly, the kinds of jobs we will have in the near future.
With AI, all the "cogs in a machine" jobs are essentially gone. There is no economic reason to employ people when AI will do 80% (and rising fast!) of the work at a fraction of the cost without pesky things like perks, leaves, raises, promotions, or heck, even sleep. Humans will be needed only for the 20% (and dropping fast!) of work that AI cannot do and to keep it honest.
And unfortunately, to get to that 20% we had to go through years and years of the 80% to "pay our dues" and learn enough to get up there; the exact 80% that is usurped by AI. Not only is education hosed, so is expertise building through on-the-job experience.
But! On the flip side, we can now have a dedicated, personalized, omniscient, always-available tutor! Do we even need school or college? Like, literally a 100% of children are naturally curious and exploratory; just that formal education (shaped by understandable economic pressures) is very effective at beating it out of them. What if we free children from the restrictive rails of rote, conventional education and let them explore wherever their interests take them? They could stay home to spend more quality time with parents who outsource work to their agents.
And AI makes it very easy to just do things, and we learn best by doing, so let them do! Would that not be a good way to nurture motivated, practically skilled talent that is truly passionate about whatever discipline they choose, which will be the exact quality needed to drive them to push the boundaries where AI cannot yet reach?
We have to critically examine with brutal honesty what jobs will be needed in the future, wholly rethink from first principles how we should prepare young talent for those, and start adjusting our society and economics to safely transition to that future. I do not know what that looks like, but I know it will be tumultuous and that we must start immediately.
This is Schroedinger's Future, simultaneously terrifying and glorious.
Some people, specially on HN, routinely complain about ads on free online resources. Well, now there are no ads. The resources are gone. "[T]here’s no incentive for people to make high-quality free content." I wonder if this is what they wanted.
The author posits a situation where big-tech AI firms teaming up with fascists as a hypothetical.
It is already here. That is the current reality.
Ehhem. I think you mean SI.
What does that mean in this context?
https://www.bbc.com/news/articles/cqy4z9pv4w0po
I hate that I'm in deep enough to know what you mean. It really harkens back to an article title that keeps popping up in my head.
"I knew one day I’d have to watch powerful men burn the world down – I just didn’t expect them to be such losers"
I'm surprised it's continued for so long! I've been doing web dev for 30 years and never felt the need to read a text or even watch a video, for me it's just all available in text on the web and always has been because the people building the web are using the web to do it.
I bought some books to support A list Apart, but most of the content seemed to be an aggregation of stuff that authors were already writing about before/after.
curation is very expensive (in time) and nearly impossible to do without already being a SME who knows what's good/bad content. I have spend weeks trying to piece together curriculum for a "free" learning path on some topic I desire to learn. It's exhausting.
In that case, why not just find a good Udemy course after maybe a few hours of research and throw $11 at it when it's "on sale" (I hate the psychology there, but that's a whole other bag of worms) when I just got back from paying $12 at Starbucks?
Of course, I'm not a web dev and don't need full books whenever that tech inevitably comes my way. I love books for my own domain, and several of them are well worth their weight in gold, since all the amazing tech out there isn't just freely available to view with an inspector.
What does education look like 2027 and onwards? My son is graduating soon and will major in Computer Science, with a secondary Art degree.
I have no idea how it will feel to be forced to write code and learn data structures, and SQL, and infrastructure, when it's all right there in 15 seconds with the AI agent.
Does anyone have any experience with this in 2026 specifically? How are the kids doing?
At least with a medical degree you HAVE to study, and memorize. It's part of the job.
As someone without CS background working in a modest app, I think a lot of it will come down to architecture, supervision and direction rather than grunt code writing.
You need to know about database normalization, about algorithms and techniques, ideate solution to problems etc because as impressive as those 1-shot youtube videos on model release look, once you go beyond that, that's where the value ad comes in my experience.
I didn't mean the job itself. I know what that's like.
I'm talking about learning/training for the job!
I think nobody knows for sure what software development is going to look like in 2027 and onwards.
I am convinced that there is no fundamental difference between artificial neural networks and biological ones. Eventually, anything a human can do, a computer will do better.
Tech companies have poured trillions into trying to make AI program better and it's still worse than any competent human. That does not give much confidence that computers will be able to do everything better than humans can.
> I have no idea how it will feel to be forced to write code and learn data structures, and SQL, and infrastructure, when it's all right there in 15 seconds with the AI agent.
> Does anyone have any experience with this in 2026 specifically? How are the kids doing?
Here's what it looks like from the perspective of Europe's largest tech company as of 2 months ago [0].
0 https://news.ycombinator.com/item?id=49229412
SAP stops most travel and hiring because of AI's soaring cost (404media.co)
102 points | 53 days ago | 68 comments
During the various covid lockdowns I started a YT channel to talk about coding and programming, not necessarily only frontend. When technologies such as ChatGPT started to show me that this kind of education was becoming unused, I stopped creating new content because I felt cheated by those AI bros. This is a comment I posted over three years ago where I was expressing my frustration: https://news.ycombinator.com/item?id=35543668#35548305
I wouldn't go quite that far ("death" of web dev ed). there's still a very large gap in certain areas. Two off the top of my head are systems thinking or org psychology; areas that developers could pivot towards as things get more clanker-driven.
I've reluctantly dipped my toes into using AI for development. I make sure I understand the codebase, and I review every line of code that was changed. Honestly, I don't see what would motivate anyone to learn TypeScript, or React anymore. This is not me glazing AI (excuse me, SI) either. Software will only be vibe coded slop after the people who already know how to read code have moved on, and the industry will deserve it.
I saw a couple of interesting new tech books from Manning and Packt and they were AI slop that just appeared out of the blue. So I held off buying them. There is no guarantee that the authors invested the time in creating the tutorial,book or the course so why would I waste money on that?
Packt has been known to be slop even many years before AI. Very little proofreading / editing, authors rarely being well-known experts etc.
Packt? Avoid, avoid, avoid. This is true. Their stuff tends to be slop grenades thrown over the wall. And as you correctly point out, this was the case before generative AI.
My experience with Manning, OTOH, tends to be good. Most of the material I've seen from them was human-written.
LLMs made it easy to skip the BS. Once you know programmingh you don't need hours and hours of content. Just the mental model for and you're good to go.
If it weren't for the job losses I'd never want to go back to 2015 or so to go back and forth on SO questions and answers and spend days on a boilerplate issue.
Eh, combing the internet for ideas, perusing revision history, and finally discovering the cause of a problem was kind of fun. It was a challenge. It was slow, and I understand why business was frustrated by that, but on a personal level I enjoyed it. It had the same rewards as any other game or puzzle.
Yeah, but who is going to learn programming given how they can "skip the bs"?
CS students, we wrote syntax on paper during exams. Same could be done.
By BS, i mean tsconfig files and caddy boilerplate.
> Most of my peers who had been selling courses and training were shutting down their businesses
“Nobody’s buying your course bro” has been a meme for years
things people didn’t want are disappearing, the people that would actually take initiative in education have another solution. those error-prone chatbots that the article mentions are good enough. most people aren’t trying to get jobs in the profession, they are trying to make minimum viable web products and landing pages that fit on free tiers, and succeeding
After speaking with programming interns, it's most likely because software development as a career is dead now with the advent of AI. Not because people are using AI to learn.
Disruptive technology disrupts.
It sucks for the people caught by the change. Honestly, I’m sorry. But rapid, disruptive change has always been part of working in technology. The industry doesn’t owe any particular job category permanence.
I think the more interesting conversation is what happens to the learning industry now. If AI changes how software is built, then teaching people to become developers has to change too.
We shouldn’t be asking how to preserve the old pipeline of teaching people to write code so they can get an entry level programming job. We should be asking what it means to teach someone to become a developer when AI can increasingly write the code.
The scarce skill may shift from producing code to understanding what should be built, decomposing problems, designing systems, evaluating tradeoffs, debugging complex behavior, verifying AI generated output, and understanding whether the resulting system is actually correct, secure, maintainable, and fit for purpose.
That doesn’t necessarily mean fewer people need to learn software development. It could mean many more people can become capable developers because the mechanical barrier to producing software has fallen dramatically.
The educational model just has to catch up.
The technology changed. The answer shouldn’t be to pretend it didn’t. It should be figuring out how to use it to produce the next generation of developers.
That’s going to be contentious for some people, even a little insensitive. But it’s just how it works in our industry.
the people are good at using AI are the same people who are good at developing software systems. traits like curiosity, knowledge-hungry and desire for continuous learning are not common in the population, so eliminating the coding barrier doesn't magically increase the number of people who can become capable developers.