My main point against using AI is that I do not want to depend basically on anything when I'm in front of the screen (obviously not including, documentation, books, SO and alike).
I closely see people that are 100% dependent on AI for literally everything, even the most trivial daily tasks and I find that truly scarly because it means that brain effort drops drammatically to a minimum level. To be stolen mental effort is not a minor thing.
Giving away that at least for me means to become a dependent zombie. Knowledge comes basically from manual trial/error almost daily.
Technology being technology if anything has shown us that we can be pushed and manipulated in every single conceivable way. And in my opinion depending on AI is the ultimate way for companies to penetrate and manipulate a very delicate ability of a human being: to think and wonder about things.
I spent most of the time confused and frustrated, straining painfully against the problem. I spent most of my 7 hour session this way, and the task was successfully completed.
But I was startled by the difficulty. I began to worry that I had given myself some kind of brainrot from disuse. Then I remembered, my goodness, it always felt that way, if I was ever doing something new. That's just what it feels like, grappling with a problem you haven't seen before.
It was always as hard as that, I was just no longer used to the feeling. You get used to the difficulty, and then it feels normal.
Or indeed: you get used to its absence, and then it suddenly feels overwhelming and "wrong" !
I think maintaining the capacity to tolerate difficulty and discomfort is a "muscle" well worth preserving.
In the real world, reliance on syntax autocomplete and checks was never an issue. The important thing has always been understanding the core concepts of the language and the runtime, e.g. how the event loop works with Node.js and how to write asynchronous and event driven programs.
I'd say it's far more tiring working that way though, you're breaking the satisfaction loop so you never really get the dopamine you used to get coding by hand, when you had a problem figuring it out was like solving a puzzle and you feel satisfaction at the end of it. With AI it feels most of my day is spent being a QA than a puzzle solver and its exhausting and even when it solves difficult problems for me the LLM slot machine is far less satisfying than if I'd figured it out myself.
Helps me keep sane tbh. And keeps the edge sharp.
It doesn’t matter if I was quite competent in it… the mechanical bits fade fast.
Doing llm assisted work is going to be like pouring bleach on my brain. I can feel it. The more I use it the worse it will be for me.
I can still formulate what I need, and problem solve just fine, but all the nuts and bolts evaporate.
This is the important statement, although I'd swap the word "knowledge" for "experience" here. You can gain "knowledge" from books, but only trial & error will give you experience to know "which" knowledge to use in which situations.
And what's important about this in the context of working with AI is the "error" part.
You have to experience errors to become truly experienced. And part of the experience is to recognize when you're about to make an error - to avoid it.
AI-driven processes mess up our natural trial & error learning curve in multiple ways:
- the AI push forces us to ship features faster (cause if we don't, our competitors will), reviews are sloppier, we discover errors later on, the feedback loop gets longer...
- using AI to debug and fix errors means we spend less time understanding what the error was about, which means we learn less about how to avoid the error in the first place...
- AI itself sounds overly confident, so reading its outputs without previous experience you may be less likely to recognize when it's making an error, which makes it harder for you to recognize when you're making an error trusting it...
On the other hand, this last point I tried to make is also why I don't think avoiding AI completely is a good strategy. Whether we like it or not, AI is becoming a part of developer's workflow. And as such, we also need to learn the trial & error process of using AI - what makes AI make errors and how to prompt it to avoid that.
Someone on HN put it well the other day: everyone wants to deliver AI results, no one wants to receive them.
It's become my first stop for search because it's doing it in bulk—read 50 results and lead me to something useful.
But I just got Claude MCP connected to my personal email/calendar/etc and I can't figure out what to do with it. It wrote a summary of my inbox that took as long to read as flipping through my inbox. And since it makes no sense to delegate decision making, I'm not sure what the actual work I'm supposed to give it would be.
I suppose people felt the same way in the agrarian revolution and later again with inventions like the plough. Suddenly a lot of people offloaded their food independence onto the work of a few.
What might it open up in our lives to be free of knowledge?
That said, these machines don't run themselves, if we disengage our minds we might get stuck in a dead end with them.
It doesn't seem to me a thing that I could suddenly forget?
Without AI I will feel frustrated that I'm now much slower, but ultimately it's just describing logic. So I'm a bit skeptical of the claim.
My brain effort is also on other things now, such as how to orchestrate guardrails, how to build pipelines to enable multiple agents work on the same thing at the same time, how to understand their weaknesses and strengths, how to automate all of that. So there's definitely a lot of mental effort going into those things.
I find myself thinking more and my thinking is of higher quality. Now I have 30 years of fucked up projects experience, so I know all the rakes I could step into.
The irony is how difficult it is to read this obviously AI-generated article due to its unnatural prose and choppy flow full of LLM-isms. The ability to write is also a skill that atrophies.
Even when AI is understandably used due to language fluency, I’d prefer to read an AI translation over a generated article.
If you don’t care enough to write it, why should I care enough to read it?
Note: My comment is not specific to this comment. I just wanted to express myself at somewhere and this is where I think it may be suitable.
It wasn’t one bottleneck. It was all of them.
Not the nuclear material. The pattern.
Money was never the constraint. Knowledge was.
...
Every day I seem to encounter (and skip over in disgust) a dozen or so AI-generated articles at the top of web searches, but this wasn’t anything at all like those.
how can you tell?
#2 rule of slop: even posts critical of pervasive AI usage and how it's ruining the world can be AI-generated
The problem is a management pattern: removing people and organizational slack because they don’t generate immediate profit, and then expecting the knowledge to still be there when it’s needed.
Short-term cost cutting leads to less junior hiring, and removes the slack that experienced engineers need in order to teach. As a result, tacit knowledge stops being transferred.
What remains is documentation and automation.
But documentation is not the same as field experience. Automation is not the same as judgment. Without people who have actually worked with the system, you end up with a loss of tacit knowledge—and eventually, declining productivity.
AI is following the same pattern.
What AI is being sold as right now is not really productivity. In many domains, productivity is already sufficient. What’s being sold is workforce reduction.
The West has seen this before, especially in the case of General Electric.
GE pursued aggressive short-term financial optimization, cutting costs, focusing on quarterly results, and maximizing shareholder returns. In the process, it hollowed out its own long-term capabilities. It effectively traded its future for short-term gains.
The same mindset is visible today.
The core problem is that decision-makers—often far removed from actual engineering work— believe that tacit knowledge can be replaced with documentation, tools, and processes.ti cannot.
Tacit knowledge comes from direct experience with real systems over time. If you remove the people and the learning pipeline, that knowledge does not stay in the organization. It disappears.
You are spot on w.r.t every assertion you've made. When bean-counters took over the ecosystem they optimised immediate profitability over everything else. Which in turn means, in their mind, every part of the system needs to be firing at 100% all the time. There's no room for experimentation, repair, or anything else.
I've commented about lack of slack on several times here on HN because when I notice a broken system now a days, 90% of it is due to lack of slack in the system to absorb short term shocks.
This is a blindspot to many. People working on entrepreneurial projects need to build a lot. They start with nothing. They need (for example) features. There's a lot to do.
Most firms are not that. Visa, Salesforce, LinkedIn or whatnot. They have a product. They have features. They have been at it for a while. They also have resources. They are very often in a position of finding nails for a "write more software" hammer.
It's unintuitive because they all have big wishlist and to do lists and and a/b testing system for pouring software into but...
If there were known "make more software, make more money" opportunities available, they would have already done them.
Actual growth and new demand needs to come from arenas outside of this. Eg companies that suck at software(either making or acquiring) might be able to get the job done.
The Problem, bringing this back to the article, is fungibility. A lot of this "human capital" stuff cannot be easily repackaged. It's a "living" thing. Talent and skills pipelines can be cut off, and vanish.
A danger in Ai coding (and other fields) is that it leverages preexisting human capital and doesn't generate any for later.
I am not so certain:
For example, I think that a lot of my knowledge about the system that I work on could be documented, and based on this documentation someone new could take over the system.
The problem rather is: the volume of documentation that I would have to write would be insane; I'd consider ten thousands of dense DIN A4 pages to be realistic - and this is a rather small system.
So, a new person who could take over this system would have to cram and understand basically all the details of this documentation insanely well.
This insane effort (write the documentation; new workers on the project then have to cram and understand every detail of this incredibly bulky documentation) is something that no employer wants to spend money on: this is in my experience the real reason why it isn't done.
The thought crossed my mind the other day — if I’m asking the AI a question, that’s replacing a human interaction I would have had with a coworker.
It’s not just in coding, it’s everything. With ChatGPT always available in your pocket, what social interactions is it replacing?
The thing that gets me is, we are meant to fundamentally be social creatures, yet we have come to streamline away socialisation any chance we get.
I’m guilty of this too — I much prefer Doordash to having to call up the restaurant like in the old days, for example.
In ideal world (where we don't live):
* Corporation - optimizes for mid-to-short term profits (remove slack, run everything thin)
* Government - optimizes for long term profits (introduce regulations to keep the slack time, keep and attract the talent so state gets better)
* Individual - optimizes for their life time (career, family and tries to leverage market conditions to learn skills and get more opportunities from existing pool)
In the west, government is optimizing for "loads and loads of moooney", because of lobby groups and MBAs controlling the corporations which are pushing these ideas through lobbies
Absolutely agree with this. Most MBAs are taught to optimize and reduce the slack.
It works fine with machinery and materials, but not with humans.
When machinery is optimized and run thin, when one of them breaks, you can get exact same in couple days (you usually prepare for it earlier), but with humans, they train their brain and next person is different from the first person.
Humans also break in different ways:
* They stop caring - you wouldn't notice it immediately, they will close tickets, but give bare minimum thought
* Communal brain will not be trained when there is not enough room for experiments and learning - which reduces the innovation eventually
This is exactly the reason it is difficult for US companies to compete with Chinese companies in manufacturing, because their communal brain have already trained and produced very good talent.
Next is the knowledge, more you outsource, more you lose it
Also when companies grow big enough "business" becomes the main business of the company. By that I mean everything unrelated to the actual original domain, such as playing in the financial markets, doing stock buybacks, lobbying, cheating etc. When your CEO is an MBA and your real market is Wall Street any actual product RD and support is a real annoying cost that just cuts into the profits and thus into the exec compensation.
They did not properly prepare and as a result lost 20% of its territory in days.
Days after that I was back is Austria and could not stop thinking about some of the people I spoke with being dead.
Since that I have also been in Dubai and Saudi Arabia as an entrepreneur and engineer. "What are you going to do when drones are used against your infrastructure?" If you followed the Russian war and first Iranian strike it was obvious that drones were going to be used against them. "not going to happen" again.
The have lost tens of billions for lacking proper preparation. They could have been protected spending just hundreds of millions of dollars over years.
It is about humans, not AI.
Ukraine has been preparing since 2014. Without preparation there would be a Russian talking head right now in Kyiv.
Take millions playing the lottery. To each of them, I can confidently say "you won't win, not gonna happen". For almost all of them I'll be right. There will be one who wins, were I was wrong, and they will say "see, told you so". That doesn't mean my prediction was wrong. It means you are having a reporting bias.
They did though. While nobody actually believed Putin would be dumb enough, the Ukrainian army was still, just in case, extremely busy on preparing defences, organising stockpiles, preparing defensive tactics.
Why would we listen to anything related to right or wrong from you then if you don't care?
The distinction between junior, mid, senior, lead is a facade. It is a soft gradient that spans multiple areas, but is tainted and skewed by the technology du jour.
Technically you don't have to be an employed developer to become a senior developer. It boils down to your personal willingness to learn and invest time building.
What companies seek these days are people having the experience with (dysfunctional) organizational structure and working around the shortcomings of the organizations communication and funding patterns, nothing more.
Does that really make you senior or just politically versed?
The pattern shows up the most whenever failing software pokes holes in perception.
There's the kind that, when given a problem, will jump in, learn what they need to learn to solve the parts they don't fully understand yet, deliver meaningful iterative results, talk to people as needed, keep you posted on their progress, loop in other team members and offer/request help to/from them, take initiative on the obvious missing parts that would benefit the project as a whole, etc.
And then there's the rest.
Within the first few years of someone's career, you can quickly tell which kind they are. It's almost impossible to turn someone from the latter group into the former.
Yes, everything else is a façade. You can be a "senior" developer with 30 years of experience and still be in the latter group. And you can be fresh out of college and be in the former.
Now some people are extremely good at other skills (politics, interpersonal communication, bullshit, whatever you want to call it) and will be able to seem to be in the first group to the people who matter (managers, execs, etc) while actually being in the second group. But then we're not talking about actual software-making skills anymore.
You can also totally be in the first group and be underpaid, never promoted, etc. There's little correlation with actually career success.
This is depressing and seems right. And yet this is something I desperately want to be ignorant of. I don’t want to peel apart my brain for anyone. Working within these kinds of problems is pure pain.
Outside of a sufficiently large organization „seniority“ of a developer doesn‘t make any practical sense. So, technically you can assign yourself any label, but that would be weird thing to do.
A freelancer is measured by portfolio, a computer scientist in academia by publications, an OSS contributor by the volume and impact of contributions. In either case, it‘s proportional to the effort spent on learning and building.
Anyway, regardless of employment status the measure of your professionalism is not defined by only something you can learn from the books. Experience matters a lot: it‘s nearly impossible to succeed in stakeholder management or presentation of your solutions by reading anything. You need practice and feedback. Senior engineers aren‘t those who excel in writing code: fresh CS graduates are supposed to know algorithms better. Senior engineers can contribute at full scale of SDLC themselves and support others. That is much easier to achieve in a professional environment rather than working on amateur projects.
That's incredibly unlikely. Do you need to be an employed surgeon to become a senior (or whatever they call it) surgeon??
I very much doubt you can be senior without having actually spent years doing it professionally. The experience is everything, no book will give you the sort of understanding you need. That's unfortunately human nature, we are not capable to learn and internalize things simply from reading or watching others do it, we absolutely need to do it ourselves to truly learn. Didactic books always have exercises for this reason.
You can learn facts and techniques from books, obviously. But just because you've read a book about Michelin restaurants that you can now be a Michelin Chef.
>In defense, the substitute was the peace dividend. In software, it’s AI.
Before it was AI, the cheaper alternative was remote contract dev teams in Eastern Europe, right?
Also over here, east of 15°E we were fired all the same.
I believe the plan is to quite simply "do less overall unless it's about AI", but everyone was waiting for others to start layoffs first.
I spent six months working part time and the decision makers made it clear that this is preferable for them long term. Beats getting fired, but I couldn't sustain this lifestyle - I'm frugal but not that frugal.
They really, really do not want to spend money. Especially not on Americans and their health insurance.
It's really strange how we're just letting them get away with this. They're on a fast trajectory toward putting Americans completely out of work and without aid, even though they're American companies first and foremost.
My current pet peave is using period instead of comma, as in:
> My people lived the other side of this equation. Not the factory floor. The receiving end.
Ostensibly this is supposed to add gravitas, but it's very often done in places where that gravitas isn't needed, and it comes off as if I'm reading the script for an action movie trailer.
The text has few of the obvious AI tells. The only thing that, to me, looks characteristic of LLM-generated text is the short and terse sentence structure, but this has been a "prestigious" way to write in English since Hemingway.
AI code generators are trolls. They confidently plausible content which is partly wrong. Then humans try to find their errors.
This is not fun. It has no flow.
The history of technology is the replacement of manual processes with automated ones.
Consider a very basic process: checkout of a restaurant.
Writing the price of each item on a sheet of paper, manually adding them and writing the total was replaced with typing in the prices and eventually with just pushing the button for the item. Paper still exists for jotting down your order but within seconds of leaving the table it’s transitioned to computer.
This has enabled lots of desirable advances- speed, accuracy, new payment rails, and increasingly, elimination of the server in checkout- you tap a credit card on a tabletop device.
Did we “forget” how to do checkout? No. We purposely changed it.
But if the internet connection goes down or the backend server powering the cash register app goes down, there is an atrophied and not-regularly exercised skill set (maybe not even trained, IDK) that has to be implemented on-the-fly and it’s slow and frustrating for everyone.
Businesses don’t exercise (or perhaps even train) this process because it’s just not needed enough to warrant the cost.
Military procurement of weapons systems is hardly the place to point to as a technological tradition. There are lots of cases where no one pays the money to keep a production process in place; the reasons are all related to shortsighted “cost savings” or failing to anticipate changing needs.
With coding today, we are seeing the same kind of shift in priorities as my restaurant example. Having humans write code in the 2020 (pre-GPT) tradition was extremely inefficient in terms of time-from-idea-to-implementation.
We’ve found a new way to do the mundane part of that task (the mechanics of translating spec to implementation).
We are figuring out how to do that while preserving quality (and a lot of it is learning how to specify appropriately).
Will we “forget” how to “build” code?
No, but the skills to generate source code by hand will atrophy just as the skills to draw blueprints by hand atrophied with the advent of CAD.
Will we find examples where someone prematurely optimized away knowledge of a skill or process, incorrectly thinking it was no longer needed? Of course.
But the productivity gains we get will be so great on average that no one will go back to doing things the old way.
There will be old-timers and hobbyists who will preserve some of that knowledge; for most it will just be a curiosity.
I agree, as with everything in 2026, the reality lands somewhere in the middle of the discourse online. But pretending this is in practice anything like the check out example is wrong.
CAD still requires you know what to do, and without CAD you can still draw blueprints by hand because you know what the result should be. Checkout is basic arithmetic you can do on a paper or even your personal phone. In both cases it is clear what the process is and what the output should be, and it doesn’t replace knowledge and training and certification.
With coding, none of that is true. By and large, there is a trend of people who don’t know what they’re doing shitting out software, or people who should know better not verifying the very flawed output they get. That is already having negative consequences in people’s lives.
> Businesses don’t exercise (or perhaps even train) this process because it’s just not needed enough to warrant the cost.
Until a crisis hits. Covid and supply chain failures. Iran war and straight of Hormuz. Prolonged War in Europe with no production pipeline available. Banks collapsing after unsustainable overleveraging in supposedly "safe" mortgages.
For every optimization and cost-saving measure that is deployed, there should be a backup plan in place. MBA types and "technologists" keep missing this. What is the backup plan for the case where most of the economy activity is built on software produced by business who overleveraged on LLM for code generation?
LLMs are a magnificent tool if you use them correctly. They enable deep work like nothing before.
The problem is the education system focused on passivity (obeyance), memorization, and standardized testing. And worst of all, aiming for the lowest common denominator. So most people are mentally lazy and go for the easy win, almost cheating. You get school and interview cheating and vivecoders.
But it's not the only way to use LLMs.
Similarly, in Wikipedia you can spend hours reading banal pop-slop content or instead spend that time reading amazing articles about history, literature, arts, and science.
As TFA says, the problem is that accumulating knowledge takes time and effort, and the AI hype and expectations on LLM-assisted coding helps with rationalizing ever more short-sighted decisions that squander or hinder that process.
Even if you are the absolute unicorn who gets paid to "code much harder problems" and "learning", the rest of the industry exists to deliver actual products and services.
So unless you nurture some type of https://xkcd.com/208/ fantasy, this is not just about you. The industry as a whole needs to find a way to work with LLMs without automating programming away entirely, and the industry as a whole needs to find a way to ensure that newcomers are able to be productive even if code-generation tools are taken away from them.
I'm not saying you're personally doing anything wrong, but there's a parallel here, when smart and curious people read articles about history and literature and art and science, rather than engaging directly with the real thing.
Or then the next level down, where creating amazing work in all of those domains depends on enough "slack" in the system for people to pursue deep work that will not be immediately profitable.
Do you see where I'm going with that? We (and I'm very much including myself: here I am on HN, instead of reading something more substantial) skim the (Wikipedia) surface, instead of diving truly deep. AIs (right now) are the ultimate surface-skimmers, and our fascination with and growing reliance on them reflects something in our current surface-skimming cultural mindset.
And the premise makes no sense anyway. The only risk of forgetting how to make shells is when other countries are making shells more efficiently. Non-western countries are not going to reject AI-coding, nor are they going to make software more efficiently by hand.
They may keep taking the longer and harder route of a mixture of AI and hand coding.
If they are smart, they will. And I think they are smart.
Coding is different though, coding doesn't have a cost barrier, it has a ability barrier. I think we will loose a lot of people who never were passionate about programming and perhaps go back to a happy equilibrium. AI is only production ready if you have someone who understands software development. AI will improve speed to market if you have the right team, it doesn't remove the need for some to learn to code. You will of course end up with startups using exclusively AI but they will be those who end up with major security breaches or simply cannot scale as the AI goes in the wrong direction for the future. Tbh that's probably a positive as it weeds out the start ups that are focused on buzzwords for funding and not product.
Why is speed-to-market such an important metric? I do not understand the need to mimic the largest players in the industry, nor do I see any particularly profound long term benefits to first mover advantage.
Anecdotally, what I’m seeing right now is the opposite. People who don’t care about programming are joining, while those who do care are getting tired of the bullshit and leaving. The good programmers are the ones leaving, the hacks are extremely happy to use LLMs.
When shit hits the fan, there won’t be many people left to clean it.
Automation is the exact opposite of tying knowledge to people. It's extracting knowledge from people and transferring it to a machine that can continue to produce the goods.
Yes, AI can lead to problems and some of these problems will be related to gaps in knowledge that was thought to be obsolete when it really wasn't. But that's a totally different problem on a totally different scale from what happened with defense production after the end of the cold war.
Nobody is shutting down or reducing software production. On the contrary, we're going to be making a lot more of it.
This kind of forgetting is normal. It's how things work when time and resources are finite. The only problem here is the belief that you can keep capacity to do something without actively exercising it, and thus the expectation that you can "just" resume doing things after a long break, without paying up a cold-start cost.
But you can't, and there's no reason to be surprised. I bet the Pentagon and the EU weren't. They didn't need those Stingers and shells for decades, didn't expect to need them soon - but they knew they could get them if they really needed them, but it's gonna be costly.
I don't get why people think this is unusual or surprising, or somehow outrageous and proves something about society or "mindsets of elites" - other than positive aspects like adaptability and resilience.
This is true at all scales. Your body and brain optimizes aggressively, too. An individual saying "I need to warm up" or "I need to hit the gym a few times and then I'll be able", or "yes, I can, but I haven't done it for years so I need an hour with a book/documentation..." - all that is exactly the same as EU going "yes we can make artillery shells... though we haven't in a while so we need some time and some millions of EUR to get our supply chain sorted out first".
Just as shift in power and the rise and fall of nations is normal.
"Civilization advances by extending the number of important operations which we can perform without thinking about them"
It remains to be seen whether this implies some kind of constraint on human progress. I doubt it.
The rise of coding bootcamps destroyed the historic knowledge and expertise of professional software developers. Waves and waves of people joined the tech workforce, without taking the years of experience required to learn how programming, and professional software development, should work. The result was a lot of really bad code, and a lot of reeeeeally bad product decisions.
Since 2018 I haven't met anyone who has read an entire technical manual on a framework, library, or tool that they use every day. By 2020 I was meeting engineering managers who said they wouldn't let engineers use a technology if they couldn't find StackOverflow snippets for it. I still meet "Senior" engineers who don't understand the most basic professional methods, like how Scrum, Agile, or Kanban actually work, and why you shouldn't just make things up as you go. Hell, the entire industry developed a collective psychosis preventing them from understanding the word "DevOps", because everyone switched entirely to learning by reading false blog posts written by clueless amateurs and upvoted in an echo chamber. If you never learn properly, and repeat misconceptions, you won't do good work.
We neeed a professional software development license, the same way the Trades have licensed plumbers and electricians and framers. We need people to apprentice under a master engineer, so they are guided by people who know what to do and what not to do. And we need formal tests to ensure businesses don't hire clueless people who passed a two week course to write critical software. Of course nobody wants to do this, and that's why it's so necessary.
That presumes that they still build frameworks, libraries and tools with technical manuals worth reading.
It doesn’t seem much like defense industry problems.
Yeah. Companies didn't want to train new employees any more as that costs money (both for paying the trainees and the teachers) so they shifted to requiring academic degrees. That in turn shifted the cost to students (via student loans) and governments.
People call it a red flag for scams if you are supposed to pay your employer for training or whatever as a condition of getting employed... but the degree mill system is conveniently ignored.
With LLMs this is no longer true - the thing can vibe a great deal before anyone notices that they have 100.000 lines of code doing what a focused, human reviewed and tested 10.000 lines can do. And as this goes on, it becomes increasingly more difficult for anyone to actually dig into and fix things in the 100.000 without the help of LLMs (thus adding even more slop on the pile).
I'm going to steal that one and add it to Stross': "Efficiency is the reciprocal of resilience."
The other that really resonated was something that I read before along the lines of… we think that once humanity learns something, that knowledge stays and we build on it. But it’s not true, knowledge is lost all the time. We need to actively work to keep knowledge alive
That’s why libraries and the internet archive are so important. Wikipedia, too
If you REALLY need something long-forgotten, then you have lazy-load it back into being at significant cost. That's the price of constant progress.
COBOL is a bad example, but higher-level languages vs. assembly is not. If you write a lot of C you really don't need to know assembly.... until you stumble across a weird gcc bug and have no clue where to look. If you write a lot of C# you don't really need to know anything about C... until your app is unusably slow because you were fuzzy on the whole stack / heap concept. Likewise with high-level SSGs and design frameworks when you don't know HTML/CSS fundamentals.
As the author says maybe AI is different. But with manufacturing we were absolutely confusing "comfortable development" with "progress." In Ukraine the bill came due, and the EU was not actually able to manufacture weapons on schedule. So people really should have read to the end of "building a C compiler with a team of Claudes":
The resulting compiler has nearly reached the limits of Opus’s abilities. I tried (hard!) to fix several of the above limitations but wasn’t fully successful. New features and bugfixes frequently broke existing functionality.
It feels a lot like someone has a cursory understanding of American politics, and thinks the US is somehow representative. It's not, it is an outlier by every statistical measure. If you want to understand the world, you need to start by forgetting everything you know about the US.
And just like offshoring dev work, we may see the rebound effect when there's all kinds of poorly written LLM outputs in production and companies are running around trying to re-hire high quality devs to fix all these fires that they themselves started.
Another reason is that LLMs train on the existing code we already know, don't expect new programming languages or frameworks this means that the software engineering skills that exist today will be relevant for a long time.
I think engineering skills will still remain relevant due to taste and proper judgement. A model trained on everything and the kitchen sink has probably not the fitting bias for given specific problems in my project. Accepting too much AI generated code without steering the ship will result in some drift of taste and ultimately make some mediocre project like done by people without good domain knowledge and without good taste. It might even be short term a business, but it lacks the long term excellence, that sets projects with good judgement apart from the common rabble.
You mean the world?
Deepseek was being glazed here, Im sure chinese programmers use it like CC
Even "First/Third world" has been fraying at the edges for decades since it was originally about political alignment.
The junior hiring collapse compounds this. Senior engineers develop judgment partly by watching juniors make mistakes and correcting them. Remove that loop and you don't just lose future seniors — you quietly degrade the current ones.
The 0.18% recruiting conversion rate mentioned here tracks with what I see in compliance and security engineering too. "Can you tell when the AI is confidently wrong?" is now the most important interview question, and almost nobody can answer it well.
I thought I'd go back for a Masters/PhD but then Trump mercurially defunded lots of STEM grad programs. Ngl, I found myself stuck. Zero job openings, zero PhD program openings. It's all so frustrating.
I also remember, that EE for a while stopped using the term "jellybean parts". Turns out that most jellybeans are produced in Asia.
This article passes blame to AI for developers not learning because they are not being actively hired. You do not need to be hired to learn something. You need to learn something in order to be hired.
It's minor but this is just wrong. If you're going to hire 4 candidates, there could be 2,253 perfectly qualified candidates even if only 0.18% get hired. The conversion rate is meaningless; it just tells us how many jobs were on offer. There is no way that the skills this fellow wanted were so rare and difficult that only 1/500 candidates could possibly handle the job. Humans even in the 1/20 mark are pretty competent if you're willing to train them and legitimate geniuses crop up at around 1/200.
The west is not merely forgetting to code. It is creating systems that can code. They aren't standing still. They are progressing to a higher level of production.
But I do think there’s another thing going on quietly in corporate America currently that will have major ramifications for companies that have prioritized using AI and that is a loss of technical excellence in general.
I can’t put my finger on it but sometime around 2023 or so there was a noticeable falloff in technical competence at companies I work with because the higher ups went all in on a generative AI future. No longer were they investing in training new hires and having rigorous certification standards. Instead people were encouraged to use AI tools to answer questions and would regularly pass off the output to more knowledgeable workers for refinement. These people clearly had no idea whether what they were sending out was accurate or not but it looked and felt like real work.
I think there will be a consolidation across the tech industry and AI will not be a differentiator and only those who are actually competent will succeed but right now AI is allowing a lot of incompetence to go undetected throughout a lot of organizations.
I see a talent pipeline collapse in next 5 years. "Software engineering is over coding is a solved problem" as being chanted by semi literate media and the AI grifter's marketing departments would further scare away the allocation of human capital to software engineering easily commanding 3x rise in salaries due to resource shortage.
Well then train them, instead of selecting 0.18% of applicants and calling it a day.
It's not some innate, immutable property - people can be taught even in adulthood.
Also it's not like they'll work for a year and switch jobs - not in the current market.
"Maybe AI gets good enough, and the bet pays off. Maybe it doesn’t."
Of course, we are all wondering if AI will be good enough in 5 to 10 years such that you don't have to look at the code (at all). If so, then very few programmers will be needed it seems. If not, its possible that roughly the same number will be needed.
It seems oddly binary to me since as soon as you need to understand anything about the code, you have to effectively onboard yourself to a foreign codebase and develop the needed context.
I had idea what might be the difference between the groups. I think for the latter group the code is important part of the goal. They see software as rather ends than means. Not entirely of course.
And the first group considers artifacts that the software produces to be the goal. So as long as AI written software is capable of producing valuable artifact they are willing and eager to go with it. And AI does that.
If the result of my code is finetuning of a neural network, I don't really care how it happened. I can benchmark it afterwards and know if the code that AI made for this purpose was good or not. I can inspect the code, investigate it, pinpoint ideas I don't like, suggest some ideas to try that I believe could give better results. I can restart, or try doing same thing few times in parallel trying different harnesses and models. All in service of the result, that is not code.
If you have a program that needs to do something and are willing to try AI to write it, think foremost about how you can rephrase the problem so that the output of AI written program becomes an artifact that can be independently verified, how to turn desired behavior into an artifact to evaluate.
As it was said - the future is here, it just distributed non-uniformly, so somebody is still and will be for some time sailing, manufacturing things and writing code.
- Knowledge of how to make Fogbank etc. was lost when the people retired and or died. AI will make things worse, especially for code.
In reality if they'd used AI, the knowledge in it would still be there as it doesn't retire or die or need paying a salary. I guess you have to keep a copy of the model file.
The article seems AI written with punchy sentences and mixed up logic.
What’s really happening is that we are all forgetting how to think
It's kind of insane how much knowledge a human being needs to have to build certain technologies and it's taken for granted.
AI might make the knowledge easier to acquire but it's still a lot of knowledge that people have to internalize.
Good, knowledgable employees are not fungible. The in-house culture that built the engineering takes an entire generation to build.
The winner-take-all MBA class of the 1980s to the 2000s and the congressional leadership developed during this era are squarely at fault and their policies need to be replaced.
For the actual problem, I fear this can't be solved by warning people, the pain will need to be felt. The system we live in, basically free market capitalism, cannot do anything else except local optimization. Maybe it's for the best, I don't know. The alternative of top down planning wouldn't have this problem, but it would have other problems. I work for a mid size somewhat luxury brand, and the major goal right now is cost cutting and AI for efficiency everywhere instead of using it to create better products or better ways to reach out customers. When I think about who will buy our luxury products if all jobs were optimized out of existence, I don't have an answer, but again I think the pain will need to be felt to change course.
I see this as a sign of increase in productivity, the important software will still have a human centered development team, but we don't need another dev team on say, tinder for dogs.
Did I forget everyone's phone numbers when cell phones came out? Yes.
But this is different. Coding is my passion. I was doing it before I got paid to do it and I'll be doing it after they no longer pay people to do it anymore.
The outsourcing was shedding more of the trivial jobs, while trying to keep key positions at home, but increasingly, it also started to lose the key positions too. It's possible that AI can make it so that the key positions will be harder to justify to outsource... but, who knows... maybe not.
This is weird, but does seem a common result.
-> AI generates a ton of code fast, but then the human takes a long time to review. Every time the prompt changes. The AI takes a few minutes to generate code that the human will take hour to review.
The reviewing is taking longer than if human just did the code. So why is it so difficult to go back to coding instead of prompting.?
I'm far removed from the conflict in Ukraine, but from the reporting it seems like they are making extremely good use of well understood, inexpensive technologies like drones with mundane munitions.
I'm sure Stinger missiles have their place in the battlefield there, but a $120K stinger doesn't seem like a very good countermeasure against a few thousand dollar drone.
So, counterpoint: We also need to understand how to embrace the changing face of software.
Probably we are going to be fine with AI abstraction too. People will use it, stuck with problems, dig deeper, learn, improve, same as we had with frameworks and its source code.
To the extent that AI is analogous to automation in manufacturing, and "writing code" to working on an assembly line, it's hard to argue the West is any thing other than a global leader in "software tool & die", so to speak.
- Knowledge of how to make Fogbank etc. was lost when the people retired and or died. AI will make things worse, especially for code.
In reality if they'd used AI the knowledge in it would still be there as it doesn't retire or die or need paying a salary. I guess you have to keep a copy of the model file.
The article seems AI written with punch sentances and mixed up logic.
We’ll see, but right now I now see developers 24/7 hooked onto their agents and in the future we will experience a de-skilling problem which clean code, best practices, security and avoiding NIH syndrome will be all flushed down the toilet.
Software developers have been learning what they needed to know to do the job the whole time. That’s pretty much the job description.
What you need to know has changed a lot recently. Like always.
> The combination of technical skill and the judgment to know when the AI is wrong barely exists in the market anymore.
That’s certainly not true. I’d take a hard look at my hiring process if it was performing this inefficiently.
[...]
Money was never the constraint. Knowledge was.
[...]
Now map that onto software. A junior developer needs three to five years to become a competent mid-level engineer. Five to eight years to become senior. Ten or more to become a principal or architect. That timeline can’t be compressed by throwing money at it. It can’t be compressed by AI either."
Well said!
I love this articles who all the coders read but none of the management.
If possible, be a mercenary and put a high number on your expertise, so we can solve this management blind spot faster.
If you can't, let your life/work's passion be "not starving to death", and try to change it politics-side.
>
> In defense, the substitute was the peace dividend. In software, it’s AI.
Same thing that happened to the unfortunate Dr. Jekyll!
In the end of the day, Russia burnt through their entire Soviet stocks in roughly 2-2.5 years, while US spent a very small proportion of theirs and Europe, maybe about half. And now consumption on both sides is similar with expenses on the Western side to feed that machine being almost invisibly small. Nothing bad happened.
Shells are not needed once they are not in needed. Code does not: customer need is always there.
Before forgotting how to code, The West will first get round up by their own Monsanto, voluntarily.
> Salesforce said it won’t hire more software engineers in 2025.
Some headline somewhere reported this, but Salesforce plenty of engineers (in the US at least) in 2025. One of them is a junior engineer on one of my scrum teams.
What America did with developing Shale Oil to become viable, so quickly is one example.
So there was this: "I run engineering teams in Ukraine. My people lived the other side of this equation. Not the factory floor. The receiving end. While Raytheon was struggling to restart production from forty-year-old blueprints, the US was shipping thousands of Stingers to Ukraine. RTX CEO Greg Hayes: ten months of war burned through thirteen years’ worth of Stinger production. I’ve seen this pattern before. It’s happening in my industry right now."
The filter flashed the warning on the telltale signs and I stopped reading. Now I've got the puzzle I don't want to do. Did someone trying to argue against "AI assisted" coding use an LLM to author that argument?
But this is HN, I can also just move on to the next story.
Not really since they are always pushing for more wars.
If the author sincerely believes the thesis that AI makes you vulnerable / dumb, they are either incredibly hypocritical. But more likely, they're just cynical and trying to get traffic to their website. And you're not getting back the time you spent reading this and arguing with it.
It’s a 85/15 rule. These big companies hire hundreds, possibly thousands, of developers but most of them cannot code. Some of them struggle to write emails. About 15% of those people provide 85% of the value.
Here is where it all went wrong. The goal of software, the only goal, is automation. That means eliminating human labor. The goal of these big companies is hiring, which is mostly the opposite of eliminating labor. That conflict results in people who cannot do the jobs they are hired to perform and whose goals are to retain employment in preference to automating anything.
Worse still is that you can’t talk about if 85% of the people doing that work find this very subject completely hostile.
It is difficult to get a man to understand something, when his salary depends on his not understanding it. Upton Sinclair.
Now? Seems like code quality is outdated and uninteresting all of a sudden. Everything is about agentic coding, harnesses, paying hundreds of dollars to Anthropic to let their LLM do the coding for you or perhaps using a 128 GB Mac to run a local model. Do you know your code base? Doesn't matter, if there are any bugs in the future Claude will fix them! Tokenmaxxing is the new paradigm, who cares about the end result as long as it's runs for now and passes all (AI written) tests!
But don't suggest these people shouldn't get $100k+ salaries, after all, they still "software engineers" in their minds, they're running the agent orchestration harness in the terminal after all, not everyone anywhere in the world could do that! They're special and deserve to be well compensated for their hard vibe coding work!
This industry is rotting from the inside.
I got my highest-paying numerical programming contract (in the US) just because I knew (from high school math table experience) how to use LUTs to calculate a lot of useful stuff i.e quarter squares.
Modernization is great and all. However, it's disappointing to know lots of new programmers are oblivious of the fundamentals.
But civilisations have always forgotten things and then had to re-engineer them. We only recently recreated Roman-equivalent concrete; knowledge required to create the Saturn V rockets had to be re-engineered; we can't recreate medieval stained glass exactly, or Viking Ulfberht Swords; we would struggle to create Betamax tape today.
Many of the examples I found (as expected) relate to military or commercially sensitive technology that did not get written down (for obvious reasons).
It also reminded me when I read Thomas Thwaites' "The Toaster Project: Or a Heroic Attempt to Build a Simple Electric Appliance from Scratch", where to make a smelter from scratch he relied on a 450 year old book ("De re metallica" by Georgius Agricola), as well as a friendly Metallurgist.
We already lost the widespread ability to write assembler in an artisinal way. Now we have AI we will also be lazy about how we write individual bits of artisinal code. So what? Yes it will cost more (in time and money) when we need to re-engineer, but how much would it cost to keep alive all the knowledge and skills we might possibly need in the future?
We had better make sure we write down and preserve the recorded data though :)
AI has been an effective coding tool for, what, 2 years at most? We've collectively forgotten all of our skills in those 2 years? Really?
https://en.wikipedia.org/wiki/Manufacturing_in_the_United_St...
There will always be specialists who can really debug stuff. Mechanics, etc. Time moves on, and we need to move with it.
I’m amazed at this “end-of-world” crap. People use AI to write this shit, to make it even crazier.
Can we stop repeating this nonsense headline please? We did not stop manufacturing things.
Manufacturing is a huge industry in the West. https://en.wikipedia.org/wiki/Manufacturing_in_the_United_St...
The US manufacturing sector is the biggest it has ever been. Exports are at all time record highs. The only thing that declined about manufacturing is the jobs. We build way more than we ever did but with far fewer people.
What we did do is decide that basic items aren't worth it. Our capacity is limited, our labor pool is limited, expenses are high, it doesn't make sense to make trinkets when we can make complex high precision parts and devices.
But no, we did not forget how to make things. We chose to use our capacity in a smarter way.
But now that the time has comes for us to automate and change, we’re all up in arms and using ridiculous arguments like this post to fight it.
The hypocrisy is mind blowing
I mean beyond the obvious hacker news bias.
If you like it nobody will remove it to you as a hobby. But the artisanal aspect of coding as a production mechansim is dying, and it was about time.
Right now, silicon dominance is what's keeping silicon valley afloat. that and the power of the American consumer base. The world is having to adapt to not relying on the US for consumption due to tariffs among other things. Not only that, attempts to curb competition from China by restricting chip exports, and imports of their tech (I don't disagree in principle with either) has led them to be more self-reliant and invest more on domestic R&D.
All this to say, there is no way around winning, and the fact of the competition is also real. You can't deny the competitive advantage proper use of LLMs brings. It's also hard to deny the destructive power of LLMs to societies.
In China, companies are heavily regulated by the state. This means being competitive against the west is a state matter, it also means harming citizens is somewhat tolerated if the economic benefit to the whole country is good, but companies chasing their own profit at the expense of the public good isn't tolerated. I don't agree with their way of doing things, but the only thing limiting their victory over the west is their hesitation and intolerance to all things outside of the SE-Asian sphere of influence. But then again, the anti-migration trend of the US also removes that slight technical advantage the US always held.
There are many problems that can't be solved by LLMs, and expecting developers' value to be the number of lines they type is silly. It doesn't matter so much if you use LLMs or don't use them, what matters is results. Westerners attitude in general is to resist LLMs. This is partly a result of (in my opinion), not realizing that there is non-western competition. It is absolutely possible to use LLMs to ship high-quality, performant and secure code, you just don't take the dumb approach of letting LLMs do everything and a human "reviews it"; how exactly depends on each development team and company.
Keep in mind, that for decades outsourcing developers offshore -- where usually sub-par code is tolerated because of lower cost to ship -- has been a prevalent trend. If companies can't get Western devs to learn to use LLMs, then they can just ship it offshore to companies that do use it. That didn't lead to the west forgetting to code, and LLMs won't either.
What will hopefully happen is you'll get less developers learning to code, which means the developers that do the work, will get paid better (it's been on the downturn) so long as they learn to sue LLMs.
What people are having a hard time coping with, is the expectation of needing armies of developers to get things done being an antiquated concept. Computers, and then the internet have done this to many industries. You used to have lots of travel agents in the past, you still do, but very few.
The bigger issue is refusal to learn from history. Concepts like capitalism, communism, market economy, centrally planned economy, etc.. are like half a century out of date. There was no "capitalism" 200 years ago (not in so many words at least). Economists and politicians aren't catching up to changes in technology. Historically, adapting to these changes has been brutal.
I won't claim to predict what will happen, but one way or the other, LLMs won't go away in response to resistance from western workers, similar to how other changes in tech didn't go away like that. Economies will have to adapt or get decimated until they do. In the mean time, there is ample opportunity for the dominance of the west to fade within our lifetime, should that opportunity be taken advantage of by the competition. If China starts being less dependent on local companies, and starts importing a lot more, they can displace US and EU consumption needs, and perhaps even force the west to be producers for their domestic demand. unregulated western companies (from Coca cola to Disney!) have been trying to achieve just that, because of the large earning potential in China. But again, China could take advantage of all that, they could have more influence over the west, but they're too inward thinking. They're so afraid of relying on a hostile west, they're preventing the west from becoming reliant on them completely. But this new image of an ineffective and declining US/West, and perhaps some success over Taiwan, and establishing a solid non-western global trade economy can give them that extra confidence?
What a bright future!
But the rest is a big no from my side.
"In hindsight" - Southpark, please take over.
What if there was a continuation of producing unused weapons during the last 20 years? "Waste of money", "Old tech", "useless" - dilemma.
Also the generalization is awfully misleading: "The west".
Let's say all are suffering from military dementia the same way. Who do think has an easier time to recover? USA or Europe? Europe relied and relies or freeloads on USA in especially military affairs.
As you wrote: some veterans teach building, handling cruse missiles to young guns like having an exciting time with the boy scouts.
Germany? "Never again! Demilitarize Germany." Decades long hatred towards USA was pretty much summed up with the slur "Ami go home!" which was a phrase used to protest US military bases in Germany - and then, when most of them finally left, it was all just fun and games (losers).
So USA has some sort of infrastructure and intellectual property to recover and never stopped treasure it as part of the country's history: Veterans' Days, Unknown Soldier, Arlington - Hegseth did a great job stopping the decline here.
Meanwhile Europe: You couldn't have a hold out in secrecy. Some enquete commission would investigate, and addresses would be leaked and people doxed.
Have a look at the representatives of the Germany Army: overweight nice guys. Sorry to say, but I think there is something wrong with this picture.
Europe has nothing to restart. They never had in the first place. Many tend to forget that the US provided massive supply to all allies during WW2. Russia would have been wiped out if it wasn't for the US logistics and money. After the war there was a joke told by survivors of the Eastern front: The first Sherman got shot on the Eastern front not the West.
Europe was always on life support. France military forces outnumbered Germany at the start of WW2. But they were tired and instead of fighting build a wall so to say. Netherlands and Denmark was taken without any resistance.
And it is the same for programming. How many European companies dominate globally like FAANG? Exactly. None. 30 years of Internet and it is getting lonely at the top for the US.
"The West"? Nope.
During the 80th, while Chucky Cheese was all the rage, in Germany you got massively socially ostracised for showing your interest in computers. Playing electronic handhelds put you up on notice by teachers, demanding correction by the school administration - true stories.
Another one: What do all FAANG like companies have in common? The founders and top managers have a background in CS. What do European managers have in common? They haven't heard of CS so far.
Europe is a mess. US is maybe having a cold start but gets its shit done.
Germany killed of its industrial sector. Energy producers as well. Germany does what Morgentau had in mind but what off the table: no more wars and weapons, just farmers and horses.
USA is save in every regard. It is not that something has been lost. This happens or why do we don't know anything about Rome?
You have to distinguish recovering from losing. Once you were at the top, at least you know how to get there while others in most cases will never get there.
These are different abilities: conserving knowledge and rebuilding it. USA needs to reactivate, while Europe needs to build from the ground up without any starting point - without money, energy, moral support, nothing.
USA is already the winner here. And this pattern keeps repeating. 250 years and what we have is an epoch were USA saw kingdoms rise and fall, USA is the only constant there is.
Treasure it. You are in a save spot despite all the dire circumstances. A blessing in disguise.
？
Putin's propagandist, or just useful idiot.
There will be always a room for good developers.
With all due respect, but many european taxpayers help pay for Ukraine. I am not disagreeing on the premise of the West killing itself via systematic recessions - Trump invading Iran leading to inflation as an example - so a lot of things are going on that show a ton of incompetency both in the USA and the EU, but at the same time I also get question marks in my eyes when this criticism comes from a country that receives money from others. That money could instead go to make EU countries more competitive, for instance. I am not saying this should necessarily be the case, mind you; I fully understand the nature of Putin's imperialism. But we need to really consider all factors when it comes to strategic mistakes with regards to production - and that includes taking up debts all the time. There are always a few who benefit in war, just as they benefit from subsidies from taxpayers (inside and outside as well).
People come and go at rates that would not be sustainable in any manufacturing business.
The opening paragraph is ridiculous. The FIM-92 Stinger is obsolete. It was replaced by FGM-148 Javelin. DACH (Germany, Austria, Switzerland) didn't forget how to make things. They are still world class for manufacturing. (Northern Italy is also economically part of that manufacturing mega-hub.)
There are plenty of NLAWs (much cheaper than Javelin, and only slightly less capable) in EU/Nato stocks to satisfy Ukraine needs against Russian heavily armed main battle tanks. For everything else, you can use one or two suicide drones to kill anything with a motor.
And now to give credit where credit is due:
Looking at his (assumed) LinkedIn profile: https://www.linkedin.com/in/denjkestetskov/
It looks like he was educated in Ukraine, so likely a Ukrainan national. If I were a Ukrainan, then I too would be publishing rage bait like this in an attempt to pressure allies to provide more funding, weapons, and gear.
As a final suggestion, the writer can visually spice up his blog post with one of my all time favourite military photos from Wiki: https://commons.wikimedia.org/wiki/File%3AFIM-92_Stinger_USM...
