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.

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.

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.

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

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.

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 chance. Though that's only an example since I think Grok will be fully compromised into Elon's Opinion Generator within another year.

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.

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 it 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 draw that’s only used photo references — there’s an entire part of the cognitive process not being used when you’re drawing something that’s already 2D. But image generating, even with extremely granular inpainting and such, is so different it’s not even comparable.

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.

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 turned out that the 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.

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?

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

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.

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.

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?

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

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?

I like it when AI metaphors presume determinism.

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

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.

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?

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...

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.

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.

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.