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I am not sure how many other people on here are old enough to remember, but I first learned to program before I had the internet. I had to read books, and then if I was trying to figure out how to do something, I would have to figure out which book to look it up in, and then figure out where in the book to find it and how to apply it to my situation. It made me learn a ton, because I would have to read a lot of books to even know where to look; I had to do my own ‘scraping and indexing’.

I remember as the internet took off and you could just search for things, I thought it made programming too easy. You never had to actually learn how it worked, you can just search for the specific answer and someone else would do the hard work of figuring out how to use the tools available for your particular type of problem.

Over the years, my feelings shifted, and I loved how the internet allowed me to accomplish so much more than I could have trying to figure it all out from books.

I wonder if AI will feel similar.

I use AI for very little but I do like using it for stuff I'm just not very interested in but have to get done.

For programming, I don't like it. It's like a master carpenter building furniture from IKEA. Sure it's faster and he doesn't have to think very hard and the end result is acceptable but he feels lazy and after a while he feels like he is losing his skills.

The best days of computing for me were what you remember. A computer was just a blank slate. You turned it on, and had a ">" blinking on the screen. If you wanted it to do anything you had to write a program. And learning how to do that meant practice and study and reading... there were no shortcuts. It was challenging and frustrating and fun.

All fair, but I think a different interpretation could be that AI allows you to vastly expand the scope of the possible, such to create a situation again where things are challenging and frustrating and fun.

I've always felt a little odd saying, "Back in my day we had to understand the cpu, registers, etc." It's a true statement, but doesn't help in any way. Is that stuff still worth knowing, IMHO? Yes. Can you create incredibly useful code without that knowledge today? Absolutely.

There are some people who still know these things, and are able to use LLMs far more effectively than those who do not.

I've seen the following prediction by a few people and am starting to agree with it: software development (and possibly most knowledge work) will become like farming. A relatively smaller number of people will do with large machines what previously took armies of people. There will always be some people exploring the cutting edge of thought, and feeding their insights into the machine, just how I image there are biochemists and soil biology experts who produce knowledge to inform decisions made by the people running large farming operations.

I imagine this will lead to profound shifts in the world that we can hardly predict. If we don't blow ourselves up, perhaps space exploration and colonization will become possible.

> Can you create incredibly useful code without that knowledge today?

You could do that without that knowledge back in the day too, we had languages that were higher level than assembler for forever.

It's just that the range of knowledge needed to maximize machine usage is far smaller now. Before you had to know how to write a ton of optimizations, nowadays you have to know how to write your code so the compiler have easy job optimizing it.

Before you had to manage the memory accesses, nowadays making sure you're not jumping actross memory too much and being aware how cache works is enough

I don't think it's odd. Sacrificing deep understanding, and delegating that responsibility to others is risky. In more concrete terms, if your livelihood depends on application development, you have concrete dependencies on platforms, frameworks, compilers, operating systems, and other abstractions that without which you might not be able to perform your job.

Fewer abstractions, deeper understanding, fewer dependencies on others. These concepts show up over and over and not just in software. It's about safety.

I dont use it a lot but when I do it's pretty much 2 patterns

* "search on steroids" - get me to the thing I need or ask whether the thing I need exists, give me few examples and I can get it running.

* getting the trivial and uninteresting parts out of the way, like writing some helper function for stuff I'm doing now, I'll just call AI, let it do its thing and continue writing the code in meantime, look back ,check if it makes sense and use it.

So I'm not really cheating myself out of the learning process, just outsource the parts I know well enough that I can check for correctness but save time writing

> I had to read books

Same here. Except that as native french speaker there simply weren't that many quality books about programming/computers that I could easily find in french.

So at 11 years old I also learned english, by myself, by using computers (which were in english back then) and by reading computer books.

And we'd exchange tips with other kids in the neighborhood who also had computers and were also learning to code (like my neighbors who eventually, 20 years later, created a software startup in SoCal).

I learned to program on a Commodore 64 using books I could get from libraries and some magazines like Compute!'s Gazette. I got online very early via BBSes (originally on a 300 baud modem for my C64) and was on the internet by the mid to late 1980s.

I never had the feeling that being able to search for things on the internet made things too easy. For me it felt like a natural extension to books for self-learning, it was just faster.

LLMs feel entirely different to me, and that's where I do get the sense that they make things "too easy" in that (like the author of the OP blog post) I no longer feel like I am building any sort of skill when using them other than code review (which is not a new skill as it is something I have previously done with code produced by other humans for a long time).

As with the OP author I also think that "prompting" as a skill is hugely overblown. "Prompting" was maybe a bit more of a skill a year ago, but I find that you don't really have to get too detailed with current LLMs, you just have to be a bit careful not to bias them in negative ways. Whatever value I have now as a software developer has more to do with having veto power in the instances where the LLM agent goes off the rails than it does in constructing prompts.

So for now I'm stuck in a situation where I feel like for work I am being paid to do I basically have to use LLMs because not doing so is effectively malpractice at this point (because there are real efficiency gains), but for selfish reasons if I could push a button to erase the existence of LLMs, I'd probably do it.

> I never had the feeling that being able to search for things on the internet made things too easy. For me it felt like a natural extension to books for self-learning, it was just faster.

I think this depends on how you are using the internet. Looking up an API or official documentation is one thing, but asking for direct help on a specific problem via Stackoverflow seems different.

Fair point, Stackoverflow didn't exist for quite a while after I started using the internet for information, and while I made as much use of it as anyone for googling answers to questions such as "What does this specific 32-bit HRESULT error code from the Win32 API mean in this context", I'm not sure if I ever posted a single question on the site.

Even people with the Internet growing up still learned largely through books, probably until StackOverflow really took off. One "hack" prior to SO that sometimes goes under-acknowledged was Google Groups. Around 2000, they bought and made free to the public the entire Deja News USENET archive, and suddenly you could search comp.lang.whatever and usually find someone who'd asked (and someone who answered) whatever question you had. And the signal-to-noise ratio was extremely high, given the barriers to entry (technical and financial) to being active on USENET's technical groups in the 90s.

Of course, asking a question was another matter, likely to result in a rebuke for violating the group's arcane decorum. But given how pervasive "RTFM" culture was back then, most "n00bs" were content to do just that (RTFM) until they came up against something that genuinely wasn't covered in some FAQ or manpage.

The pilot analogy hits different when you consider that pilots still train on simulators for exactly this reason — they're legally required to maintain proficiency even when autopilot handles 99% of flights.

There's no equivalent mandate for software engineers. Nothing stops you from spending years as a pure "prompt pilot" and losing the ability to read a stack trace or reason about algorithmic complexity. The atrophy is silent and gradual.

The author's suggestion to write code by hand as an educational exercise is right but will be ignored by most, because the feedback loop for skill atrophy is so delayed. You won't notice you've lost the skill until you're debugging something the agent made a mess of, under pressure, with no fallback.

Yeah. HN is fucked. It’s over with the amount of AI comments. Especially recently with more captcha breaking, etc.

Human posters need to start saying obscene things or making unsafe/violent statements to ensure the comment isn’t just AI generated.

I've seen a lot of posts like this one, but this is the first to encapsulate how I feel so well.

Honestly, I don't really know what to do. I spent my whole life (so far; I'm still very young) falling in love with programming, and now I just don't find this agent thing fun at all. But I just don't know how to find my niche if using LLMs truly does end up being the only way for me to build valuable things with my only skills.

It's pretty depressing and very scary. But I appreciate this article for at least conveying that so effectively...

Re: "reviewing code is very different from producing it, and surely teaches you less" - I feel this so much when reviewing the code one of my coworkers writes. My coworker makes plenty of mistakes and I learned the hard way that reviewing his PRs in a web page is not enough. These days when I have to review his code I download his branch locally and load the entire solution in the IDE. I then track his changes and usually find a few things wrong.

BTW - my coworker is not AI. It is a flesh-and-bones SWE.

We should be very concerned for the next generation. When you have the constant temptation of digging yourself out of a problem just by asking an LLM how will you ever learn anything?

My biggest lessons were from hours of pain and toil, scouring the internet. When I finally found the solution, the dopamine hit ensured that lesson was burned into my neurons. There is no such dopamine hit with LLMs. You vaguely try to understand what it’s been doing for the last five minutes and try to steer it back on course. There is no strife.

I’m only 24 and I think my career would be on a very different path if the LLMs of today were available just five years ago.

Ok imagine you went back 30 years and you had a swarm of experts around you who you could ask anything you wanted and they would even do the work for you if you wanted.

Does this mean youd be incapable of learning anything? Or could you possibly learn way more because you had the innate desire to learn and understand along with the best tool possible to do it?

Its the same thing here. How you use LLMs is all up to your mindset. Throughly review and ask questions on what it did, or why, ask if we could have done it some other way instead. Hell ask it just the questions you need and do it yourself, or dont use it at all. I was working on C++ for example with a heavy use of mutexs, shared and weak pointers which I havent done before. LLM fixed a race condition, and I got to ask it precisely what the issue was, to draw a diagram showing what was happening in this exact scenario before and after.

I feel like Im learning more because I am doing way more high level things now, and spending way less time on the stuff I already know or dont care to know (non fundementals, like syntax and even libraries/frameworks). For example, I don't really give a fuck about being an expert in Spring Security. I care about how authentication works as a principal, what methods would be best for what, etc but do I want to spend 3 hours trying to debug the nuances of configuring the Spring security library for a small project I dont care about?

> Does this mean you'd be incapable of learning anything?

Yes. This strikes me as obvious. People don't have the sort of impulse control you're implying by default, it has to be learnt just like anything else. This sort of environment would make you an idiot if it's all you've ever known.

You might as well be saying that you can just explain to children why they should eat their vegetables and rely on them to be rational actors.

I see it as being more personality/interest than impulse control. A curious/interested person would try and get involved and be a part of it, someone uninterested will just say what's the point and get by having the work done for them.

It may very well have stunted my learning. What’s the point of absorbing information when you have a consortium of experts available 24/7?

Saying what you said about it being down to being how you use LLM comes from a privileged position. You likely already know how to code. You likely know how to troubleshoot. Would you develop those same skillsets today starting from zero?

Supposedly because AI has limits and you still have to know what you're doing so you can guide it and do it better.

If that's not true, then what's the problem with not learning the material? Go do something more productive with your time if the personal curiosity isn't good enough. Were in a whole new world.

>Saying what you said about it being down to being how you use LLM comes from a privileged position. You likely already know how to code. You likely know how to troubleshoot. Would you develop those same skillsets today starting from zero?

This is true, and I can't answer that 100% confidently. I imagine I would just be doing more more/complicated things and learning higher level concepts. For example, if right off the bat I could produce a web app, Id want to deploy it somewhere. So Id come across things like ssh, nginx, port forwarding, jars, bundles, DNS, authentication, etc. Do this a 1000 times just the way I wrote 1000 different little functions or programs by hand and you'll no shit absorb little here and there as issues come up. Or maybe if whats hard a year ago is easy today, Id want to do something far more incredibly complex than anything anyone's been able to imagine before, and learn in that struggle.

Programmers in the 90s were far more apt at understanding CPU registers, memory and all sorts of low level stuff. Then the abstraction moved up the stack, and then again and again. I think same thing will happen.

Also, you can't say Im in a privileged position for already knowing how to code and at the same time asking what's the point of learning it yourself.

As an older person, I'm not worried. The world changes all the time. People are put people in difficult situations, and they have to adapt. "Oh no, how will people learn things?" is not that big of a struggle in the grand scheme. We're not burning books or giving people lobotomies. People can still learn if they want to, easier than ever before. Businesses will adapt, people will adapt, by necessity. Things will be very different, sure. But then we get used to the difference, and it becomes normal.

Kids today couldn't imagine how people used to live just 100 years ago, like it was the dark ages. People from that age would probably look at kids 10 years ago and think, these poor children! They don't know how to work hard! They don't know anything about life! They're glued to these bizarre light machines! Every age is different.

At the beginning of the internet, I used to save all webpages where I’d find info, just in case I would be stuck without a connection or if the website removed it. I had parts of the MDN.

The internet never fell. I bet it’ll be the same with AI. You will never not have AI.

The big difference is the internet was a liberation movement: Everything became open. And free. AI is the opposite: By design, everything is closed.

Reviewing code is absolutely different from writing it, and in my opinion much harder if the goal is more than surface level understanding.

This is what I am still grappling with. Agents make more productive, but also probably worse at my job.

> For example, to add pagination to this website, I would read the Jekyll docs, find the right plugin to install, read the sample config, and make the change. Possibly this wouldn’t work, in which case I would Google it, read more, try more stuff, retest, etc. In this process it was hard not to learn things.

How is this any different than building Ikea furniture? If I build my "Minska" cupboard using the step-by-step manual, did I learn something profound?

Firstly, if you're doing those steps, you're building your own tutorial, not just following the exact steps in a manual provided with the software. The sample config won't be exact or perfect for your setup, so you'll need to say least figure out how to adjust it to your needs.

That said, I think you're still leaning things building IKEA-style software. The first time I learned how to program, I learned from a book and I tried things out by copying listings from the book by hand into files on my computer and executing them. Essentially, it was programming-by-IKEA-manual, but it was valuable because I was trying things out with my own hands, even if I didn't fully understand every time why I needed the code I'd been told to write.

From there I graduated to fiddling with those examples and making changes to make it do what I wanted, not what the book said. And over time I figured out how to write entirely new things, and so on and so forth. But the first step required following very simple instructions.

The analogy isn't perfect, because my goal with IKEA furniture is usually not to learn how to build furniture, but to get a finished product. So I learn a little bit about using tools, but not a huge amount. Whereas when typing in that code as a kid, my goal was learning, and the finished product was basically useless outside of that.

The author's example there feels like a bit of both worlds. The task requires more independent thought than an IKEA manual, so they need to learn and understand more. But the end goal is still practical.

If you've never put a cupboard together, you would have learned what the different parts, what size of screws to use (in the rough sense),... You may have forget it right after, but when someone ask you to help them, you will be a bit more proficient than someone with no experience.

But the nice thing about a cupboard and its components is that they are real objects, so the remembrance is done with the whole body (like the feeling of a screw not correctly inserted). Software development is 90% a mental activity.

I find the opposite is true for me. In my wheelhouse I can use an agent to do a thing, and I can be very critical of the implementation. Outside of my wheelhouse I actually learn quite a lot by watching the agent solve a problem. Since I do have a strong background I am still able to judge the overall approach and identify obvious stupid things the agent tries to do. I would say the code quality is probably a bit worse in those situations than I would have ended up with, but takes about 1/3 of the time. The most difficult part is opening a PR and worrying there might be a couple stupid blips left that I missed, didn’t affect the implementation, but my coworkers are going to look at and ask me wtf I was thinking

  > I do read the code, but reviewing code is very different from producing it, and surely teaches you less. If you don’t believe this, I doubt you work in software.

If I am fixing bugs in my own (mostly self-education) programs, I read my program several times, over and over again. If writing programs taught me something, it is how to read programs most effectively. And also how to write programs to be most effectively read.

> If I am fixing bugs in my own (mostly self-education) programs, I read my program several times

I think here lies the difference OP is talking about. You are reading your own code, which means you had to first put in the effort to write it. If you use LLMs, you are reading code you didn't write.

I read other people’s code all the time. I work as a platform engineer with sre functions.

Gemini 3 by itself is insufficient. I often find myself tracing through things or testing during runtime to understand how things behave. Claude Opus is not much better for this.

On the other hand, pairing with Gemini 3 feels like pairing with other people. No one is going to get everything right all the time. I might ask Gemini to construct gcloud commands or look things up for me, but we’re trying to figure things out together.

If I need to change someone's code, I also read it. several times.

>hundredths of them

Man, it would rule so much if programmers were literate and knew how to actually communicate what they intend to say.

It's obvious from the context here what the intended meaning was. Everyone makes typos sometimes.

Man it would rule so much if programmers could manage not to be assholes by default so much of the time.

It's ironic that the more ignorant one is the one calling another ignorant.

Alright I've had my fun with the name-calling. I will now explain the stunningly obvious. Not a thing anyone should have to for someone so sharp as yourself but there we are...

For someone to produce that text after growing up in an English speaking environment, they would indeed be comically inept communicators. Which is why the more reasonable assumption is that English is not in fact their native language.

Not merely the more generous assumption. Being generous by default would be a better character trait than not, but still arguably a luxury. But also simply the more reasonable assumption by plain numbers and reasoning. So, not only were you a douche, you had to go out of your way to select a less likely possibility to make the douche you wanted to be fit the situation.

Literate programmers indeed.

Not everyone has English as a first language.

I think this author could consider thinking of the AI as more than just a task rabbit that allows us to not code, not think, not understand.

If the LLM is indeed such a master at complex coding tasks that we don't understand, why not ask it some questions about how the code works?

You can even ask directly about the concern. "I am worried that by letting you do everything I am not learning how the system works. Could you tell me more about what you did and how I might think through it if I needed to do it myself?"

Whether we want to accept it or not, we’re now QA. That’s not derogatory, at all.

But I don’t think the answer here is to double down on reading the code and understanding that deeply. We’re rapidly moving past this.

I think the answer is to review the code for very obvious bad choices. But then it’s about proper validation. Check out the app, run the flows, use it for real. Does it _actually_ function?

Or that’s what is working for me. I cannot review all the LOC and I’m starting to feel like I don’t want.

> reviewing code is very different from producing it, and surely teaches you less

Maybe he meant "reviewing code from coding agents"? Reviewing code from other humans is often a great way to learn.

I interpreted this as not as good a way to learn.

I learn the most from struggling through a problem, and reading someone’s code doesn’t teach me all the wrong ways they attempted before it looked like the way it now does.

Exactly. And vice versa, one of the biggest benefits of code review is calling out pitfalls you, the reviewer have ran into that the reviewee isn't aware of. LLM addicts won't have any experience with what works/doesn't work, so their reviewing will be pretty useless

I was thinking in situations where a coworker might send me something to review, and I might have thought "hmm, I wouldn't have done it like that, but this is a great way to do it too". Also, a good source of teachable code is to participate in a programming contest, and then review the repositories of the teams who scored better than me after the contest.

I agree that if I don't already know how to implement something, seeing a solution before trying it myself is not great, that's like skipping the homework exercises and copying straight from the answer books.

This is why tutorials in programming don't really teach much because you get the finished version. Not all the wrong steps that were taken, why they failed, what else was tried.

These steps are what help you solve other issues in the future.

  [...] since I work at an AI lab and stand to gain a great deal if AI follows through on its economic promise.

This is why I still haven't embraced agents in my work but stick with halfway manual workflow using aider. It's the only way I can keep ownership of the codebase. Maybe this will change because code ownership will no longer have any value, but I don't feel like we're there yet.

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