alt Hacker NewsThe West forgot how to make things, now it’s forgetting how to code
Comments
I still code daily without any coding assistance mostly because I believe this is the way to not forget how things are done, even trivial things.
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.
“Money was never the constraint. Knowledge was.”
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?
> They can’t tell you what the AI got wrong.
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.
I highly question the ability of companies to gauge the level of experience of any dev.
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.
>I read the Fogbank story and recognized it immediately. Not the nuclear material. The pattern. Build capability over decades. Find a cheaper substitute. Let the human pipeline atrophy. Enjoy the savings. Then watch it all collapse when a crisis demands what you optimized away.
>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?
I saw academic rigor fall of a cliff in exchange for 'better job alignment' between end 80s when I had my first class after finishing highschool called 'Formal verification in software' on to beginning of the 2000s when I left giving the first class to new students 'Programming in Java'. All the 'teaching how to think' was replaced with 'how to get a well paying job'.
I write all my own code and then run it by the LLM for analysis and suggestions. I'm probably not a 10x developer, but this has 10x'd my own progress. I make fewer missteps and build a deeper understanding of the problem space. I used to brace myself for a lengthy debugging session whenever testing a new section of code and now it tends to run as expected, more often than not. It may take a few years but I expect people who are using LLMs in the backseat will pull out ahead as the leaders of the future of software.
There's a certain irony in that the article itself is quite clearly assisted by AI. Not a criticism per se as I don't have a problem with AI assistance, but food for thought given the material being commented on.
Every day Peter Naur’s paper programming as theory building gets more relevant
Excellent post. Two stand-out points are deskilling through abolition of apprenticeship (or equivalent progression through the rank and responsibility), and loss of institutional knowledge, especially tacit knowledge stored in individual people. These are people problems more than they are technology problems. Without continuity of process and practice stuff gets lost. Sometimes change really is progress, for example software safety and security practices have progressed over the past 50 years, but other times change is just churn, or choices driven by misaligned incentives which will bite later, as the article describes.
I remember same complaints about junior engineers copy pasting snippets of code from StackOverflow without understanding. And without curiosity to understand, without code review and mentorship from senior engineers they never grew to the senior level. But that is only some of them, others used StackOverflow to learn, did not use the snippets without understanding them first and properly adapting to their context, and they got good coaching in their teams and now have reached senior level from there. I see the same dynamic with LLMs, just more opportunities for both juniors to learn more by following up, and for seniors to to create tooling to enforce better architectur, test coverage and fault resiliency.
People are not perfect. I went to Ukraine just days before the invasion. Travel and Hotels in Kiev had become extremely cheap. You asked the Ukrainians about the possible invasion. "Not going to happen" everybody said."Russia talks always aggressively, but never does anything".
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.
Very frustrating to have an ‘article’ so heavily AI-written take up this much space and attention.
What’s really happening is that we are all forgetting how to think
Needn’t worry, such incompetencies are rooted out by the 8th or 9th round of interviews.
The defense analogy makes absolutely no sense. All the examples are of production shutdowns or reductions. Knowledge was lost because people retired and not replaced at all. None of it was lost to automation.
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.
> The combination of technical skill and the judgment to know when the AI is wrong barely exists in the market anymore.
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.
You could say COBOL has had this "problem" for 40 years also. That's why we need to constantly be inventing new ways of making things. The old ways are always forgotten over time.
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.
Click/rage bait?
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...
The article makes no sense, and stars with a very wrong perspective on things.
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".
First of all this is clearly AI-assist writing (being charitable here).
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.
I wonder if the real problem is short-term thinking in culture and incentivised by markets. By optimising next quarter's profits over investing in long-term growth and capability, things like this happen.
I don’t know. Partly true. I came to web development, when low level things solved: frameworks, ORMs, OSs, databases. I don’t know sql nor c++ well. But I can create a system, a value based on the abstractions. Everyone told me: Ruslan, you don’t know SQL, what a shame! Well I do not have problems and did not have about it.
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.
When you've run out of ideas just portray "the west" as some monolithic portrait in some decline-porn fan fiction as clickbait.
The Fogbank example is the most chilling part. It's not just that they lost the people — they lost the ability to know what they didn't know. Nobody could even write down what was missing because the knowledge was never formalized in the first place.
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.
Reminds me of this post:
This is why a comprehensive computer science degree is necessary. Seeing and working only with the trees leads to destroying some forests, eventually.
Chinese models run around $2 to $8 dollars per million tokens - Claude is 10x that cost - when will the bean counters move to chinese models, USA bans these models for national security reasons - Anthropic, Openai, Meta, X all move to China where the models will be cheaper
Yes. Just like globalization created companies like TSMC, AI will do the same. Software engineers who don't rely on LLM code generators will have a moat because they can do it cheaply and sustainably.
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.
"the west" ?
You mean the world?
Deepseek was being glazed here, Im sure chinese programmers use it like CC
The west hasn’t known how to write code for the 20 years I have been doing it, at least at major .com brands.
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.
I don't agree with "the west forgot how to make things", it moved supply chains for cheap consumer goods to asia, but in the B2B space a lot of things are manufactured in Europe: companies like Bosch, Volkswagen, ASML, Alstom and Airbus are cranking out extremely complicated machines that last many years in demanding environments. It's just a different level of value-add vs. low cost electronics (for instance).
I have forgotten all about Apache Wicket - will this cause the downfall of western civilization?
Space programmes have this issue too - everything had to be relearnt and un-obsoleted for Artemis Moonshots
If the system treats you as a number, you should become a mercenary.
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.
Speak for yourself. I now dare to code much harder problems and learning is bliss. No more having to sit down to dig needle-in-haystack through horrible documentation or random Stack Overflow posts.
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.
I disagree with the premise - interesting but I interpret the same fact pattern differently.
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.
thankfully with code and coding agents - the tacit/tribal knowledge always lives via the codebase itself unlike atoms based manufacturing processes..
There was a time when companies had terrible development practices and could forget how to build, test, and deploy software, but is anyone seeing that now? We have much better development practices nowadays.
It doesn’t seem much like defense industry problems.
Do you think this is a tooling problem or more about incentives and how engineers are trained now?
How do you become a senior engineer if no one hires you as a junior anymore.
We’ve been automating every single industry that we touched for decades without a single word, bringing up tepid responses like “it’s capitalism” or “business is business” when called out on it.
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
>The combination of technical skill and the judgment to know when the AI is wrong barely exists in the market anymore.
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.
> Optimized for minimum cost with zero margin for surge. On paper, efficient. In practice, one bad day away from collapse.
I'm going to steal that one and add it to Stross': "Efficiency is the reciprocal of resilience."
> Leadership qualities. Our last hiring round tells you how rare that is: 2,253 candidates, 2,069 disqualified, 4 hired. A 0.18% conversion rate.
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.
This is some convoluted BS built on the premise that wars need to make sense, economically or otherwise. No, wars do not need to make sense. If a person, a dictator or a president, unilaterally starts a war that forfeits the lives of both the dictator's (possibly fabricated) enemies and its own people, that person is knowingly committing murder. Logically, such a person should be handled with at least as much prejudice as a lone wolf that opens fire on a crowd. So we need to fix our legal systems to be better at preventing wars, not our economic systems to be better at fighting them.
Talking of military stuff: it's not a problem really. No one can keep the non-needed capacity in existence, it's not even possible if no one consumes the product. Make sufficient buffer stocks to have time to re-learn the process when needed, and that's it. There is no realistic way it could work any different, otherwise it's like: maintain entire Cold War era production capacity and keep it idle or working at 5% workload, just to be able to ramp up when needed? But it means keeping almost all of the Cold War budgets still flowing. Wasn't going to happen - and of course, in Russia it also didn't happen, and couldn't.
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.
It's a great story, and a nicely written piece.
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 :)
The real issue, in my view, is not AI itself.
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.