Is AI ruining our skills? Early results are in – and they're not good

> Sure, we're all more productive now, but…

I’ve been trying to ask people a different question: sure, we’re more productive now but to me, the AI era is only serving to plunge us deeper than ever into producing more, more, more, faster, faster, faster. And for what? What’s it all for? I became a software engineer because I have a lot of fun writing code, thinking through and solving complicated problems, and experiencing the reward of seeing what I’ve built by hand working for the first time.

Do people really have fun managing a fleet of agents that generate the code instead? Or is it just the rush of producing something extremely quickly, much more quickly than you might be able to alone, regardless of how well (or poorly) it might work? For me, being able to move quickly was never the fun part.

It’s one thing to utilize AI to lessen the drudgework, the boilerplate, but I look at people who have gone all in on agentic development and it just really makes me wonder.

You're either using it wrong, or work somewhere that sucks. I'm having a ton of fun coding with AI.

I feel like I am learning a whole new branch of the programming skill tree. LLMs and their harnesses are like a mew set of constraints to work around when designing systems, but if you get them right you can build bigger, better things than ever before.

I say all of this as someone who spent the last two days rebuilding RBAC for my application after Claude royally messed it up.

if computers themselves are bicycles for the mind, LLMs are cars. or even motorcycles, if we talk smaller models.

- they require specific roads being paved for them. for example, if your tooling is proprietary and not accessible from the CLI, your agent is pretty much fucked. if your tool is not represented in training data (think, `jj` VCS or your proprietary/tailor-made tooling), you require duct tapes such as "skills" and "memories". a bicycle (that is, your own mind + computer) handles such off-roads much better.

- they get you from A to B faster, sure, but along the way you may encounter something curious - a different road to take, an interesting vista. not to mention, bicycles are actually good for your health, and professional drivers suffer from all the sedentary job diseases we programmers do, unless they actively counter it. with LLMs, we get a "sedentary job disease" of skill atrophy, on top of all the other atrophies us coders should counter with a proper exercise set at least three times a week.

- finally, when you crash in a car (Opus/Sonnet, GPT-5.5) or, worse, on a motorcycle (smaller Qwens, DeepSeek, Haiku/GPT-5.4-nano), you crash very loudly and with a high chance of irrecoverable casualties.

Please stop saying we - because many of us didn't ever desire or contribute (outside of having our code / data / IP stolen) to these models or the companies developing them. Many of us weren't willingly singing up to use AI - we were essentially forced to by our employers. Not everyone is more productive now because of AI - many people spend the extra time they save writing code, reviewing code produced by AI.

Yes. It even happens to e.g. professors and the deans of universities.

This is why I think even the fuss about Noam Shazeer joining OpenAI needs to be seen within a context; as good as this hire is, there is no inherent reason to believe he still brings some secret undiscovered magic that others do not have in a more current form.

The "I have people skills; I am good at dealing with people!" character in Office Space was memorably hilarious for a reason. Many people lose the skills that got them where they are from disuse as they rise through the ranks.

intellectual work (or really any discipline with a 'skills tree' that you can progress up or down) degrades over time without practice. same way that, if you don't run for a while, you're not going to be able to hit your last PR when you pick it back up.

it's definitely easier to catch up after some time away than it would be if you'd never developed the skills in the first place or didn't have a natural talent, but you'll definitely atrophy without exercise. every leader i've ever worked for who graduated to a purely managerial/'strategic' position and didn't keep up their IC skills eventually got pretty slow on the uptake.

i appreciate that this study was done (AI and its inverse relationship to human wellbeing is one of the biggest challenges of our time IMO) but this also seems obvious

The ownership class does not really do work. What they delegate (high level plans) is generally easier to do for AI agents than things like software engineering because it does not need to be as precise or executable. However, there the work has very broad scope scope and the roles are very high risk, so it might need a Fable 5 or Fable 6 level vision language model to remove the jaggedness to make it 'safe' enough to drop the humans But what is going to blow up in 2027 are Automated AI Companies. Human CEOs and owners will not be able to compete with these AI-run companies.

Yes, but what happens to the professions and classes you've mentioned that wasn't looked at in this study is that new skills developed. For instance, something was assuredly lost as programming on average deviated from low level programming, but new skills and optimizations were gained. Fewer people knew how to construct a real-time bitmap from scratch, but more advanced software was being built on average as people were armed with greater and more manageable abstractions.

Having run into quite a few managers who used to be programmers who can barely do fizzbuzz after a few years of managing: yes, I think it's pretty similar. Much of your brain is "use it or lose it" and that's not using it.

I do think there's more than enough room to claim that LLMs are probably significantly worse than that kind of human delegation though, in part because you have such a rapid cycle time that not-incredibly-rich people can't afford from humans.

AI needs a great deal of handholding which is different than just offloading tasks. You spend a lot of cognitive energy playing a slot machine hoping the RNG works out this time.

There’s definitely a skill to using AI but it just doesn’t generalize very well.

  if this same effect happens for very wealthy and/or very senior executives?

Yes, I'm 100% sure. It's for the same reason: if you don't actively use a skill - it atrophies; there is no workaround.

The difference is what you delegate to. An executive delegates to people like himself. A computer user delegates to another kind of existence so those think don't think the same way the user does.

Programming normally highlights this difference. LLM programming makes it much less apparent but its still there, LLM are not thinking the way humans do and therefore struggle to solve many problems humans easily solve. So letting all human programming skills rot and just use LLM will halt our progress unless we reach AGI before our programmings skills are mostly gone.

This is why the rich and powerful often seem so out of touch. There's no one around them willing to tell them they're wrong or push back on bad ideas. It doesn't just ruin skills but fundamentally distorts one's perception of the world.

>Because we have no moral or social pressure to not delegate everything?

"We" depends on where you are. Countries like Japan or Germany have maintained a gray collar, rather than a blue/white collar culture for exactly that reason. You will find business owners on the workshop floors frequently because there is an understanding that divorcing management from tacit work is going destroy leadership ability. That's the basis of vocational work culture, having general expertise across all domains of your job rather than being a kind of over-specialized idiot.

> Or are AIs fundamentally different, and if so, why?

Literally: the context window.

With the human you have a window that possibly extends up to _years_. With your language model you have maybe a few megabytes which is always preceded by instructions from the model maker.

The main skill you need to reach that level is the one they always keep practicing: shmoozing. Thinking is not required as an executive, so you cannot lose what you never had.

And being born wealthy requires zero skill or practice.

> we are being challenged at the very fundamentals of our ability to think deeply and widely and persistently. That has never happened before like this.

Social media and content algorithms come to mind as an early wave that changed the landscape here that defines the horrible status quo leading into the AI era.

These days it's trivial to slide into an echo chamber and very hard to break out of the silo.

There might be a double-edged sword here where AI, trusted by most people as an omniscient oracle, can offer the only pushback we encounter on positions we picked up passively by scrolling social media, Youtube, TikTok.

For example, ask Claude, ChatGPT, and even Grok about the "space lasers" that started wildfires in Hawaii in 2018, something people like Marjorie Taylor Greene floated on social media. It quickly debunks it as bullshit.

Now, maybe it will pan out such that everyone will have their own AI that tells them what they want to hear. But so far I've watched people abandon arguments on Twitter because Grok rejected their claim. So it feels like there's a glimmer of hope.

Human mind as much as body needs challenge. That's the only way for growth, heck even sustaining some higher cognitive levels.

Nurses, doctors and family members know damn well how life trajectory nosedives for somebody ie suddenly bound to bed, when stimulus and doable challenges are reduced to minimum.

llms remove challenges, or minimize them. I can't image any added value for any engineer apart from cost cutting for employer. Sure, next come folks who are doing 10x compared to before, and some actually do. Even there, I have my doubts. For rest of us, its not good and won't get better unless they price it out of most markets.

> That has never happened before like this.

You should possibly spend some time reading what people used to say about the invention of Radio and Television.

> It is quite extraordinary and breath-taking at times to see the agents in action;

So is any magic trick. The unsettling notion that it may all just be an illusion that you've failed to correctly understand doesn't seem to weigh on people.

> its almost hard-drug like in its potential long-term psychological effects.

That might have more to do with how the owners of these products choose to market and deploy them. Perhaps if they peeled back the covers just slightly your euphoria would change to dread. There's an Upton Sinclair moment coming.

I’m curious if someone coming into that fresh, without having had the mental exercise of, for example, grappling with data structures and (lower-level) algorithms in practical applications by hand, could achieve a mindset that useful and productive?

When I was in design school, as much of our work was in physical media — graphite, cut paper, paint, vine charcoal — as was practicing great kerning and getting experience with the digital tools. Even though you still had to make the individual strokes and choose appropriate tools in the digital realm, there was still a perception of the process that was obviously lacking among those that came from strictly digital backgrounds. It’s similar to seeing someone who’s only worked with photo references try life drawing — there’s an entire part of the cognitive process not being used when you’re drawing something that’s already 2D. Sure, they can learn, but unless they’re forced to, they’ll probably just keep taking a picture and drawing that. But image generating, even with extremely granular inpainting and such, is so different it’s not even comparable. I’d hesitate to say that someone with a lot of experience doing very advanced image generation would be dramatically further along than a complete beginner if they learned to draw which is not true of the photo reference artist, and even less true of a purely digital artist that did life drawing on a tablet.

Kind of like how millennials, many of whom always had access to technology, but also experienced dial-up-era computer use, are generally more technically savvy than the your stereotypical “iPad kid” that can’t even traverse a directory structure.

The question is what higher level skills there will be to focus on?

I am not convinced that there are tasks, like project management or architecture, that the Ai is inherently worse at.

>But maybe I've also been able to spend more time on a higher level skill? Maybe the doctors got worse with the images but had more cognitive resources to think about the patient's context?

That's not the way the economics behind this work.

Supposing the AI priests are right (they aren't) and using AI creates a thought surplus on the user, freeing cognitive capacity to think of higher things. What do you think will said user's boss want to do with that surplus? Let the user develop higher-level cognitive abilities? I don't think so.

The doctors in the article performed worse post-AI: suppose AI saved them so much time that they did 100 exams in the time they used to take doing 10 exams. What will their employers do with that freed up labour time? They'll of course have the doctors do more exams and perhaps fire some now-redundant doctors that are no longer needed. The surviving doctors are left deskilled, doing the same or more work, and society gets worse quality medical care. But hey, its not all bad - the employer gets to save on labour, and shareholders will be happy.

In the eyes of many ceo’s, you are slowly becoming useless.

You’re fucked once you have to start getting AI to produce code for languages you’ve never actually worked in.

You will have to write code to understand deeply what goes on at the low level. Without a solid understanding of the low level, you won’t truly know what optimal solutions look like on a high level. You will be flying by the seat of your pants, churning out code that works but has bad low level quirks sprinkled through the code base. The AI will say it’s fine, but you’re just building up shitty software. Feels like shit, run likes shit.

Once someone new comes along who has worked with the language manually and can get AI to produce effective high quality code, you’ve lost competitive advantage. They can build way better versions of whatever you do. You’re finished. You’re a low quality engineer.

We never learned how to use IBM punch cards. Writing functions by hand for modern languages is fast becoming anachronistic.

I don't know this applies to you, but I've had several friends who convinced themselves they're exploring the frontiers of science, and it always turns out that their conversations spiraled into some sort of weird quantum-metaphysical gobbledygook.

LLMs are sycophants, and in long conversations, their sycophancy produces a positive feedback loop: the context window contains affirmations of incorrect interpretations / analogies, so the chatbot continues down that path because, well, that's the most likely completion of previous text. And before you know it, you're discovering the hidden fabric of the universe, which is always some Minkowski fractal spacetime tensor lattice manifold with subharmonic DNA nanotubes.

That is to say, unless you have a robust way to evaluate what you're learning, and to confirm that you're actually learning, I'd tread carefully.

> Im learning new things at a pace I never imagined at 40 years old.

You aren't learning anything. Learning involves doing.

We've known this for ages: simply reading a maths book without drilling on the problems will not get a student to pass.

Best case scenario, you're reading stuff. For users of coding agents, they're not even doing that.

You're not learning them. You're being told about them and given a hammer to leverage them with mediocre to low skill level.

Learning requires a huge time investment. Using an LLM doesn't shorten that.

You think you're learning things at a pace you never imagined, but all you're really doing is learning superficially. You never really go deep into things, and it "seems" like you're learning faster, but how much can you actually recall of the things you learned? By the way, I'm saying all this because this has been my experience. I can prompt like no tomorrow asking questions, but I forget most of it because it's not deep learning. I'm not actually thinking myself, I'm allowing the AI to think for me.

How exactly is AI helping you with sports? Have you become a better athlete? Have you learned more about the strategy of each sport from the perspective of a coach for example? Care to elaborate?

I actually agree with you; I definitely feel I'm able to use LLMs to learn and explore concepts, but I've always been a self-taught and highly motivated person in the first place. Everything technical that I know, I know because I put in the work to learn it on my own. That's why I wish these tools were being advertised as models that help you do BETTER work, not MORE work. They're using them as excuses to lay off swaths of workers, instead of allowing them to uplift people's skillsets. And, of course, it invited a whole mass of individuals who use them to artificially elevate their perceived skills.

>Im learning new things at a pace I never imagined at 40 years old

Are you learning, or are you simply consuming?

I think we're missing long form studies that show if it's possible to learn deeply from compressed AI generated summaries of topics.

I have the same experience, but there's another dimension I want to throw out: breadth versus depth.

I've wildly increased my breadth of learning. If I'm ever curious about anything, even a passing thought, I can scratch that itch in a way I never could before.

But am I going deep? Acquiring new skills? Eh... I usually go far enough to unblock myself and/or settle a curiosity. I don't think that's good or bad, but it does present a certain set of tradeoffs that are different than going deep.

Are you actually learning them or are you just letting the AI kinda do them for you? There was a time I knew how to take a path integral, but kinda-sorta knowing what something is and how to ask a calculator for it is different than knowing yourself.

Isn't this effectively the same argument an addict would put forward?

One of the challenges here is that the skillset we are in danger of letting atrophy is essentially unbounded. It’s not a specialized tool like a calculator, where you have a well scoped domain of problems you are offloading. granted, in practice many people are using ai for specialized domains (like coding or producing visual designs). But whatever level of abstraction they are currently working at is not, in principle, something that they couldn’t also offload to ai.

The huge problem in this specific case is that to use this tool well you also need the underlying skill to be developed and preserved. It's very different from a power drill.

The difference if this is okay is how reliable the tool is. If it is a calculator or compiler it is okay. The example in the article also sounds okay (machine learning image classification), though I am not sure.

LLM output is unreliable, so we still need to judge it. If I want to be able to judge code, I must have worked with it to a certain extent. So the unreliable tool does not help me much if I don't want to accept the unreliability.

Sure. But if you don't own the tool and it is held by a cabal of centralist (even political state-adjacent) parties, you're having a bad day when computer says no.

> What we gain though is for people don’t possess that knowledge in the first place, now have this superpower.

Indeed. The great innovation of AI is giving people with wealth access to vast amounts of knowledge, while limiting the amount of wealth that people with knowledge can access.

It's completely bass-ackwards.

All the benefits you're describing apply to the present moment; people with knowledge, self-discipline and expertise can leverage LLMs to great effect.

How many people like this will exist in a decade? Two?

I don't think the real threat is at the individual level, but at the societal level.

Building skills over time leads to insights that lead to innovation.

AI does many interesting things, but it doesn't innovate (yet).

The real threat isn't that we'll all lose our skills (possibly) and then lose access to AI (unlikely), it is that AI will remain at roughly currently levels and we'll dull our skills due to reliance on it and innovation will stall because we've offloaded too much of the thinking to the non-innovative machine.

I'm not saying this is what definitely will happen, but it does seem like a very possible outcome.

> I'm sure people got worse at arithmetic after the invention of the calculator

For LLMs, we can see this sentence but replace "arithmetic" with a variable X

I'm sure people got worse at X after the invention of LLMs"

The problem isn't that X skills atrophy necessarily

The problem is that for LLMs, X is "basically all knowledge and communication skills"

Can we really tolerate a society where "basically all knowledge and communication skills" are atrophying?

At worse you suffer from cognitive atrophy. Become more dumb and lazy.

If your argument boils down to "individuals just need to use it the right way" then I ask you to kindly use that same framing for driving cars, owning guns, etc. and then rethink your position.

It turns out that when the use of a tool has external consequences for misusing it, it's important that there are structures in place for penalizing the misuse of that tool.

Comparison never made sense to me

1/ When dealing with High level language I am not seeing assembly or the language it compiles to. It's not a leaky abstraction

2/ It's deterministic

The day my markdown file is the thing I deploy on AWS your analogy will stand

I like it when AI metaphors presume determinism.

As jatins says: Why bother with source code? just deploy prompts and specs. It’s rare for C programmers to care about assembly, or python programmer to care about C. Why do you care that much about source code?

You clearly don't know what you're talking about if you think compilers are a good analogy.

How do you measure the bundle of "skills" that comprises critical thinking? And if that's your analogy's distance running, what's the "riding a bike" analogue?

It's not good news if the AI companies have to raise their prices 10x to deliver the same service while paying down the crippling debt they've incurred getting everyone hooked on AI.

If my mechanic started charging 10x more to fix my car, I'd learn to fix my car.

Why are you comparing it to technologies with a positive outcome? Why not to opium, tobacco, or alcohol?

> So we need to be teaching that core lesson to children

Yeah, that has always worked out well.

Happened with all of tech support, really, or at least in my corner of the world: you take your PC to a technician and you receive in return a fresh Windows install, a folder with most of your files (including a copy of "C:\Windows"), and none of the programs or shortcuts you had before.

I don't know what to tell you bro. I type much less code but I haven't stopped thinking altogether. I still write to myself and to others. I read longform. I walk and introspect. I think about high level problems. Any general cognitive decline I ever notice, I attribute to having a bad day or getting old...

I think it’s like shoes. Shoes are generally better than callouses at protecting your feet, providing traction, etc. Almost everyone accepts the trade-off and wears shoes as opposed to going barefoot. To be sure, your feet lose some of their toughness. You may become reliant to some degree on the tool. I know that when my kid started wearing shoes, walking became actually a bit harder and be fell a few times. The shoes were a little clunky and lacked the same sensation. He changed he gait to accommodate, but over-compensated. They took a while to get used to wearing. AI also often feels a bit clunky and lacks the same feel. However, I think some people are confusing the shoes for the feet. The shoes don’t do the walking. The LLM is the words, but not really the ideas. If you stand or pose in shoes, move your legs around and wait for the shoes to take you somewhere… that’s not going to work.

Not worthwhile feels a bit strong (a good FAQ is definitely worthwhile!), but I definitely agree that there is a big difference between any kind of art (writing, playing music, creation of images/videos/etc.) for its own sake and for commercial purposes. AI is terrible for the former but perfectly fine for the latter.

There will always be value in a human writing fiction or a memoir or even a Substack. The human perspective is inherently valuable there. Much less so with ad copy that's just going to get A/B tested ad infinitum until a winner is picked out based entirely on data.

Same with visual art. Art painters aren't going to lose their jobs to AI, but once you've got a robot that can paint a house reliably, house painters are done for.

That’s got nothing to do with llm’s and it’s got nothing go do with ‘how technology is used’.

I’m not even sure why this has to be said.

Universal fact 1) most people lack the self discipline to choose what really benefits them and takes care of their well being. We already know this - obesity rates, excessive screen time etc.

The solution is to control the actions of people. But most of you ain’t ready for that conversation.

Hopefully this is not your case but as an IC the “manager, who didn’t write code for a couple of years” that decides to come back and “help” is one of the worst experiences. Code is usually subpar, uses old idioms, and comes with added pressure. With AI this can become much worse, because of the sheer volume of code that can be thrown at the IC.

It's going to get a lot worse than AI being unintentionally wrong. We're only at the start of the curve for this, but it's obvious that controlling what LLMs show in response to politically-charged topics is huge lever of power for those in charge.

So now imagine you're using Chineses AI/AR glasses that you've come to rely on for "knowledge" and you look at the famous picture from Tianemen square: "Doesn't look like anything to me".

That's a great analogy - everybody knows you forget pretty much everything after a few years away from the line. It should be seen like one of those studies that proves smiling is correlated with happiness. :-)

Idk man my system design game is better than its ever been because I put in the effort to use these tools and recognize they can't do software design better than I can and because I've increased the scope of what I'm building I often have to think more deeply about the problem up front. A typical speccing sessions lasts a few hours for me on big work before I have AI start writing that work where I'm just going back and forth on what I want, points of consideration for performance, usability, structure etc pushing back on where AI (always) chooses the most naive way it wants to do something.

Every time I see an anecdote like this, A it reaffirms my belief that FAANG devs are fairly mediocre on the whole (not saying this is you, obviously there are good FAANG devs) and B it reaffirms my belief that the developers who kind of give up their thinking like this are really using the tool wrong or didn't really care about the work before AI either so its now just a quick means to an end.

I recently did a manual exercise to force myself to keep my skills from decaying too much after about a year of using agents exclusively. My ability to go from a blank slate to software was indeed in the toilet, but my ability to reason over and edit code seems to be surviving fine. I suspect that your LLM-pilled coworkers' judgment issues are related to laziness that LLMs have enabled, rather than an inherent property of LLM use.

You're making the right call there. I've felt it, seen it around me personally. That study is terrifying.

I'm no code ninja at the best of times. It's scary to hear that's happening to top engineers.

I need an exit strategy. Anyone else come off AI?

Are you actually seeing any signs that we’re going back to how software was written before, and needing those skills in the same way? Because I sure am not seeing that right now. As someone who vibe codes 100% and has become managements favorite, while being more or less allowed to break the platform every other release I know my skills are atrophying. But it’s taking me different places in my career entirely. There’s a path to managing other engineers now that opened years before it would have previously. Even writing this makes it sound ridiculous, but that’s what’s infront of me right now. There is an entirely other set of skills that I’m interested in sharpening now. Definitely no more sitting down several hours per day and meeting about system design and integrations with others.

> two senior engineers in my org (in a FAANG) who vibe-code the most have lost literally all of their skills.

Unfortunately FAANG incentives this behaviour with their token leaderboards and general push for velocity over anything else (other than goog maybe)

The article is saying that using AI degrades certain skills when AI is not available. You're claiming that AI is making people less effective even when they have access to AI. I'm skeptical of your claim.

The article's claim is probably true, but not really an argument against AI. Using keyboards degrades my ability to write by hand but that's not a good argument against keyboards. AI will become another tool that allows us to operate more effectively and at a higher level of abstraction. Just like keyboards and Python.

Now, we still occasionally need people who can write assembly (and do calligraphy). But mostly we don't.

This is the most important point: it seems like AI tool use undermines one's ability to use the AI tool.

I did stop because I noticed the severe atrophy after using them for a year. Never again.

As someone who was self taught as a programmer and has a reasonable high level understanding of some CS concepts but not lots of experience applying them, and no good mentor, I’ve found working with an LLM really englightening. Asking Claude to think about “good ways to structure this” or asking how similar problems get solved in industry or high profile projects has really helped me design better solutions and avoid painfully reinventing wheels (recent eg was for a plugin type architecture).

I think a lot of academics and researchers who code but aren’t software engineers or CS majors are going to benefit, provided they take the time to prove what the model does and are curious about whether it’s doing something sensible!

Relative to a 1% coder hand rolling something then yes it’s AI slop etc. but it’s prob still raising the bar generally.

Another tactic is to use LLMs to help you learn. That's another way to approach "It has never been easier to get better than others."

Avoiding tool use because you're afraid you won't be able to use the tool responsibly is not likely to be a winning strategy in the end. Learning to use the tool well is much more effective.

My friends can't ride horses as well as they used to, they've been using cars to get around too much.

Sure horses are more efficient, but cars are faster and more convenient, and allow you to get a lot more done.

Also cars will get better in our lifetime, horses are horses.

You miss the point, the point is that by using AI, our skills (let say "coding in Rust") are diminishing and even without reading this article, we can feel it to some extent already if we aren't lying to ourselves, especially very heavy AI users.

We do however create new skills, skills that might be more relevant for the future, but still, it is controversial.