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I was worried about skill atrophy. I recently started a new job, and from day 1 I've been using Claude. 90+% of the code I've written has been with Claude. One of the earlier tickets I was given was to update the documentation for one of our pipelines. I used Claude entirely, starting with having it generate a very long and thorough document, then opening up new contexts and getting it to fact check until it stopped finding issues, and then having it cut out anything that was granular/one query away. And then I read what it had produced.

It was an experiment to see if I could enter a mature codebase I had zero knowledge of, look at it entirely through an AI, and come to understand it.

And it worked! Even though I've only worked on the codebase through Claude, whenever I pick up a ticket nowadays I know what file I'll be editing and how it relates to the rest of the code. If anything, I have a significantly better understanding of the codebase than I would without AI at this point in my onboarding.

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Yeah, +1. I will never be working on unsolved problems anyhow. Skill atrophy is not happening if you stay curious and responsible.
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I have never learned so quickly in my entire life than to post a forum thread in its entirety into a extended think LLM and then be allowed to ask free form questions for 2 hours straight if I want to. Having my questions answered NOW is so important for me to learn. Back in the day by the time I found the answer online I forgot the question
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Same. I work in the film industry, but I’ve always been interested in computers and have enjoyed tinkering with them since I was about 5. However, coding has always been this insurmountably complicated thing- every time I make an effort to learn, I’m confronted with concepts that are difficult for me to understand and process.

I’ve been 90% vibe coding for a year or so now, and I’ve learned so much about networking just from spinning up a bunch of docker containers and helping GPT or Claude fix niggling issues.

I essentially have an expert (well, maybe not an expert but an entity far more capable than I am on my own) who’s shoulder I can look over and ask as many questions I want to, and who will explain every step of the process to me if I want.

I’m finally able to create things on my computer that I’ve been dreaming about for years.

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Some people talk like skill atrophy is inevitable when you use LLMs, which strikes me as pretty absurd given that you are talking about a tool that will answer an infinite number of questions with infinite patience.

I usually learn way more by having Claude do a task and then quizzing it about what it did than by figuring out how to do it myself. When I have to figure out how to do the thing, it takes much more time, so when I'm done I have to move on immediately. When Claude does the task in ten minutes I now have several hours I can dedicate entirely to understanding.

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You lose some, you win some. The win could be short-term much higher, however imagine that the new tool suddenly gets ragged pulled from under your feet. What do you do then? Do you still know how to handle it the old way or do you run into skill atrophy issues? I’m using Claude/Codex as well, but I’m a little worried that the environment we work in will become a lot more bumpy and shifty.
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> however imagine that the new tool suddenly gets ragged pulled from under your feet

When you have a headache, do you avoid taking ibuprofen because one day it may not be available anymore? Two hundred years ago, if you gave someone ibuprofen and told them it was the solution for 99% of the cases where they felt some kind of pain, they might be suspicious. Surely that's too good to be true.

But it's not. Ibuprofen really is a free lunch, and so is AI. It's weird to experience, but these kinds of technologies come around pretty often, they just become ubiquitous so quickly that we forget how we got by without them.

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> the new tool suddenly gets ragged pulled from under your feet

If that happened at this point, it would be after societal collapse.

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I don’t even wanna think about that scenario, maybe he gets averted somehow.
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The "infinite patience" thing I find particularly interesting.

Every now and then I pause before I ask an LLM to undo something it just did or answer something I know it answered already, somewhere. And then I remember oh yeah, it's an LLM, it's not going to get upset.

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Asking infinite questions about something does not make you good at “doing” that thing, you get pretty good at asking questions
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Understanding is not learning. Zero effort gives zero rewards, I ask Claude plenty of things, I get answers but not learnings.
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I used to speak Russian like I was born in Russia. I stopped talking Russian … every day I am curious ans responsible but I can hardly say 10 words in Russian today. if you don’t use it (not just be curious and responsible) you will lose it - period.
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More fair comparison would be writing/talking about Russian language in English. That way you'd still focus on Russian. Same way with programming - it's not like you stop seeing any code. So why should you forget it?
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Programming language is not just syntax, keywords and standard libraries, but also: processes, best practices and design principles. The latter group I guess is more difficult to learn and harder to forget.
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I respectfully completely disagree. not only will you just as easily lose thr processed, best practices and design principles but they will be changing over time (what was best practice when I got my first gig in 1997 is not a best practice today (even just 4-5 years ago not to go all the back to the 90’s)). all that is super easy to both forget and lose unless you live it daily
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I have also found LLMs are a great tool for understanding a new code base, but it's not clear to me what your comment has to do with skill atrophy.
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Well ultimately the skill I care about is understanding software, changing it, and making more of it. And clearly that isn't atrophying.

My syntax writing skills may well be atrophying, but I'll just do a leetcode by hand once in a while.

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What do you mean “cut out anything that was granular/one query away”? This was a very cool workflow to hear about—I will be applying it myself
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For example, Claude was very eager to include function names, implementation details, and the exact variables that are passed between services. But all the info I need for a particular process is the names of the services involved, the files involved, and a one-sentence summary of what happens. If I want to know more, I can tell Claude to read the doc and find out more with a single query (or I can just check for myself).
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Are you sure you would know if it didn't work? I use Claude extensively myself, so I'm not saying this from a "hater" angle, but I had 2 people last week who believe themselves to be in your shoes send me pull requests which made absolutely no sense in the context of the codebase.
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Yeah, I test everything myself.
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That’s always been the case, AI or not.
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No, it hasn't. I did not have a problem before AI with people sending in gigantic pull requests that made absolutely no sense, and justifying them with generated responses that they clearly did not understand. This is not a thing that used to happen. That's not to say people wouldn't have done it if it were possible, but there was a barrier to submitting a pull request that no longer exists.
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It just happens to be a lot worse now. Confidence through ignorance has come into the spotlight with the commoditization of LLMs.
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In my experience, the people sending me garbage PRs with Claude are the same ones who wrote garbage code beforehand. Now there's just 10x more of it.
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It's good that it's working for you but I'm not sure what this has to do with skill atrophy. It sounds like you never had this skill (in this case, working with that particular system) to begin with.

>I have a significantly better understanding of the codebase than I would without AI at this point in my onboarding

One of the pitfalls of using AI to learn is the same as I'd see students doing pre-AI with tutoring services. They'd have tutors explain the homework to do them and even work through the problems with them. Thing is, any time you see a problem or concept solved, your brain is tricked into thinking you understand the topic enough to do it yourself. It's why people think their job interview questions are much easier than they really are; things just seem obvious when you've thought about the solution. Anyone who's read a tutorial, felt like they understood it well, and then struggled for a while to actually start using the tool to make something new knows the feeling very well. That Todo List app in the tutorial seemed so simple, but the author was making a bunch of decisions constantly that you didn't have to think about as you read it.

So I guess my question would be: If you were on a plane flight with no wifi, and you wanted to do some dev work locally on your laptop, how comfortable would you be vs if you had done all that work yourself rather than via Claude?

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> If you were on a plane flight with no wifi, and you wanted to do some dev work locally on your laptop, how comfortable would you be vs if you had done all that work yourself rather than via Claude?

Probably about as comfortable as I would be if I also didn't have my laptop and instead had to sketch out the codebase in a notebook. There's no sense preparing for a scenario where AI isn't available - local models are progressing so quickly that some kind of AI is always going to be available.

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Not so much atrophy as apathy.

I've worked with people who will look at code they don't understand, say "llm says this", and express zero intention of learning something. Might even push back. Be proud of their ignorance.

It's like, why even review that PR in the first place if you don't even know what you're working with?

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I cringed when I saw a dev literally copy and paste an AI's response to a concern. The concern was one that had layers and implications to it, but instead of getting an answer as to why it was done a certain way and to allay any potential issues, that dev got a two paragraph lecture on how something worked on the surface of it, wrapped in em dashes and joviality.

A good dev would've read deeper into the concern and maybe noticed potential flaws, and if he had his own doubts about what the concern was about, would have asked for more clarification. Not just feed a concern into AI and fling it back. Like please, in this day and age of AI, have the benefit of the doubt that someone with a concern would have checked with AI himself if he had any doubts of his own concern...

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Is this the same subset of people who copy/paste code directly from stack overflow without understanding ? I’m not sure this is a new problem.
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It's a new problem in the sense that now executive management at many (if not most) software companies is pushing for all employees to work this way as much as possible. Those same people probably don't know what stack overflow even is.
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In my experience, no - I think the ability to build more complete features with less/little/no effort, rather than isolated functions, is (more) appealing to (more) developers.
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I don't think so. I'll spend a ton of time and effort thinking through, revising, and planning out the approach, but I let the agent take the wheel when it comes to transpiling that to code. I don't actually care about the code so long as it's secure and works.

I spent years cultivating expertise in C++ and .NET. And I found that time both valuable and enjoyable. But that's because it was a path to solve problems for my team, give guidance, and do so with both breadth and depth.

Now I focus on problems at a higher level of abstraction. I am certain there's still value in understanding ownership semantics and using reflection effectively, but they're broadly less relevant concerns.

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It's difficult to copy & paste an entire app from Stack Overflow
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Copied and pasted without noting the license that stack overflow has on code published there, no doubt
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Hey. I resemble that remark sometimes!! quit being a hater (sarcasm) :P
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We've had such developers around, long before LLMs.
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They're so much louder now, though.
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It’s a lot like someone bragging that they’re bad at math tossing around equations.
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If I wanted to know what the LLM says, I would have asked it myself, thanks…
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What is it in the broader culture that's causing this?
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People who got into the job who don’t really like programming
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I like programming, but I don’t like the job.
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Then why are you letting Claude do the fun part?
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Obviously, the fun part is delivering value for the shareholders.
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These people have always existed. Hell, they are here, too. Now they have a new thing to delegate responsibility to.

And no, I don't understand them at all. Taking responsibility for something, improving it, and stewarding it into production is a fantastic feeling, and much better than reading the comment section. :)

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You can argu that you will have skill atrophy by not using LLMs.

We have gone multi cloud disaster recovery on our infrastructure. Something I would not have done yet, had we not had LLMs.

I am learning at an incredible rate with LLMs.

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I kind feel the same. I’m learning things and doing things in areas that would just skip due to lack of time or fear.

But I’m so much more detached of the code, I don’t feel that ‘deep neural connection’ from actual spending days in locked in a refactor or debugging a really complex issue.

I don’t know how a feel about it.

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I strongly agree on the refactor, but for debugging I have another perspective: I think debugging is changing for the better, so it looks different.

Sure, you don't know the code by heart, but people debugging code translated to assembly already do that.

The big difference is being able to unleash scripts that invalidate enormous amount of hypothesis very fast and that can analyze the data.

Used to do that by hand it took hours, so it would be a last resort approach. Now that's very cheap, so validating many hypothesis is way cheaper!

I feel like my "debugging ability" in terms of value delivered has gone way up. For skill, it's changing. I cannot tell, but the value i am delivering for debugging sessions has gone way up

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As someone who's switched from mobile to web dev professionally for the last 6 months now. If you care about code quality, you'll develop that neural connection after some time.

But if you don't and there's no PR process (side projects), the motivation to form that connection is quite low.

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> If you care about code quality, you'll develop that neural connection after some time.

No, because you can get LLMs to produce high quality code that has gone through an infinite number of refinement/polish cycles and is far more exhaustive than the code you would have written yourself.

Once you hit that point, you find yourself in a directional/steering position divorced from the code since no matter what direction you take, you'll get high quality code.

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Yes, you certainly can argue that, but you'd be wrong. The primary selling point of LLMs is that they solve the problem of needing skill to get things done.
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That is not the entire selling point - so you are very wrong.

You very much decide how you employ LLMs.

Nobody are keeping a gun to your head to use them. In a certain way.

Sonif you use them in a way that increase you inherent risk, then you are incredibly wrong.

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I suggest you read the sales pitches that these products have been making. Again, when I say that this is the selling point, I mean it: This is why management is buying them.
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I've read the sales pitches, and they're not about replacing the need for skill. The Claude Design announcement from yesterday (https://www.anthropic.com/news/claude-design-anthropic-labs) is pretty typical in my experience. The pitch is that this is good for designers, because it will allow them to explore a much broader range of ideas and collaborate on them with counterparties more easily. The tool will give you cool little sliders to set the city size and arc width, but it doesn't explain why you would want to adjust these parameters or how to determine the correct values; that's your job.

I understand why a designer might read this post and not be happy about it. If you don't think your management values or appreciates design skill, you'd worry they're going to glaze over the bullet points about design productivity, and jump straight to the one where PMs and marketers can build prototypes and ignore you. But that's not what the sales pitch is focused on.

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The majority of examples in the document you linked describe 'person without<skill> can do thing needing <skill>'. It's very much selling 'more output, less skill'
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Sales pitches dont mean jack, WTF are you talking about?
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Sales pitches are literally the same thing as "the selling point".

Neither of those is necessarily a synonym for why you personally use them

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I see it completely the opposite way, you use an LLM and correct all its mistakes and it allows you to deliver a rough solution very quickly and then refine it in combination with the AI but it still gets completely lost and stuck on basic things. It’s a very useful companion that you can’t trust, but it’s made me 4-5x more productive and certainly less frustrated by the legacy codebase I work on.
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Yeah I whole hardheartedly disagree with this. Because I understand the basics of coding I can understand where the model gets stuck and prompt it in other directions.

If you don't know whats going on through the whole process, good luck with the end product.

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They purportedly solve the problem of needing skill to get things done. IME, this is usually repeated by VC backed LLM companies or people who haven’t knowingly had to deal with other people’s bad results.

This all bumps up against the fact that most people default to “you use the tool wrong” and/or “you should only use it to do things where you already have firm grasp or at least foundational knowledge.”

It also bumps against the fact that the average person is using LLM’s as a replacement for standard google search.

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You're learning at your standard rate of learning, you're just feeding yourself over-confidence on how much you're absorbing vs what the LLM is facilitating you rolling out.
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This is such a weird statement in so many levels.

The latent assumption here is that learning is zero sum.

That you can take a 30 year old from 1856 bring them into present day and they will learn whatever subject as fast as a present day 20 year old.

That teachers doesn't matter.

That engagement doesn't matter.

Learning is not zero sum. Some cultural background makes learning easier, some mentoring makes is easier, and some techniques increases engagement in ways that increase learning speed.

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> We have gone multi cloud disaster recovery on our infrastructure. Something I would not have done yet, had we not had LLMs.

That’s product atrophy, not skill atrophy.

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> I am learning at an incredible rate with LLMs

Could you do it again without the help of an LLM?

If no, then can you really claim to have learned anything?

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I could definitely maintain the infrastructure without an llm. Albeit much slower.

And yes. If LLMs disappear, then we need to hire a lot of people to maintain the infrastructure.

Which naturally is a part of the risk modeling.

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> I could definitely maintain the infrastructure without an llm

Not what I asked, but thanks for playing.

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You literally asked that question

> Could you do it again without the help of an LLM?

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And the question you answered was "could you maintain it without the help of an LLM"
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So, you havent really learned anything from any teacher if you could not do it again without them?
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> So, you havent really learned anything from any teacher if you could not do it again without them?

Well, yes?

What do you think "learning" means? If you cannot do something without the teacher, you haven't learned that thing.

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I mean...yeah?

If your child says they've learned their multiplication tables but they can't actually multiply any numbers you give them do they actually know how to do multiplication? I would say no.

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For some reason people are perfectly able to understand this in the context of, say, cursive, calculator use, etc., but when it comes to their own skillset somehow it's going to be really different.
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Yes that's exactly right.
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That would be the definition of learning something, yes.
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I think this is a bit dismissive.

It’s quite possible to be deep into solving a problem with an LLM guiding you where you’re reading and learning from what it says. This is not really that different from googling random blogs and learning from Stack Overflow.

Assuming everyone just sits there dribbling whilst Claude is in YOLO mode isn’t always correct.

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>> I am learning a new skill with instructor at an incredible rate

> Could you do it again on your own?

Can you you see how nonsensical your stance is? You're straight up accusing GP of lying they are learning something at the increased rate OR suggesting if they couldn't learn that, presumably at the same rate, on they own, they're not learning anything.

That's not very wise to project your own experiences on others.

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Actually, it’s much like taking a physics or engineering course, and after the class being fully able to explain the class that day, and yet realize later when you are doing the homework that you did not actually fully understand like you thought you did.
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The challenge is not if you could do all of it without AI but any of it that you couldn't before.

Not everyone learns at the same pace and not everyone has the same fault tolerance threshold. In my experiencd some people are what I call "Japanese learners" perfecting by watching. They will learn with AI but would never do it themselves out of fear of getting something wrong while they understand most of it, others that I call "western learners" will start right away and "get their hands dirty" without much knowledge and also get it wrong right away. Both are valid learning strategies fitting different personalities.

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Also AI could help you pick those skills up again faster, although you wouldn’t need to ever pick those skills up again unless AI ceased to exist.

What an interesting paradox-like situation.

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I believe some professor warned us about being over reliant on Google/reddit etc: “how would you be productive if internet went down” dilemma.

Well, if internet is down, so is our revenue buddy. Engineering throughput would be the last of our concerns.

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>I am learning at an incredible rate with LLMs.

I don't believe it. Having something else do the work for you is not learning, no matter how much you tell yourself it is.

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If you've seen further it's only because you've stood on the shoulders of giants.

Having other people do work for you is how people get to focus on things they actually care about.

Do you use a compiler you didn't write yourself? If so can you really say you've ever learned anything about computers?

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You have to build a computer to learn about computers!
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I would argue that if you've just watched videos about building computers and haven't sat down and done one yourself, then yeah I don't see any evidence that you've learned how to build a computer.
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And, so the anti-LLM argument goes, if you've not built the computer you can't learn anything about what computers could be used for.
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It is easy to not believe if you only apply an incredibly narrow world view.

Open your eyes, and you might become a believer.

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What is this, some sort of cult?
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You mean the cult of "I can't see the viruses therefore they dint exist"? As in "I can't imagine something so it means it's a lie"?

Indeed, quite weird and no imagination.

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No, it is an as snarky response to a person being snarky about usefulness of AI agents.

It does seem like there is a cult of people who categorically see LLMs as being poor at anything without it being founded in anything experience other than their 2023 afternoon to play around with it.

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Who cares? Why are people so invested in trying to “convert” others to see the light?

Can’t you be satisfied with outcompeting “non believers”? What motivates you to argue on the internet about it? Deep down are you insecure about your reliance on these tools or something, and want everyone else to be as well?

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Why do people invest themselves so hard in interjecting themselves into conversations about Ai telling people it doesn't work?

It feels so off rebuilding serious SaaS apps in days for production, only to be told it is not possible?

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Who here said ai “doesn’t work”?
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Using LLMs as a learning tool isn’t what causes skill atrophy. It’s using them to solve entire problems without understanding what they’ve done.

And not even just understanding, but verifying that they’ve implemented the optimal solution.

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It's partly that, but also reading and surface level understanding something vs generating yourself are different skills with different depths. If you're learning a language, you can get good at listening without getting good at speaking for example.
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https://hex.ooo/library/power.html

When future humans rediscover mathematics.

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Yeah I am worried about skill atrophy too. Everyone uses a compiler these days instead of writing assembly. Like who the heck is going to do all the work when people forget how to use the low level tools and a compiler has a bug or something?

And don’t get me started on memory management. Nobody even knows how to use malloc(), let alone brk()/mmap(). Everything is relying on automatic memory management.

I mean when was the last time you actually used your magnetized needle? I know I am pretty rusty with mine.

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> an LLM is exactly like a compiler if a compiler was a black box hosted in a proprietary cloud and metered per symbol

Yeah, exactly.

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Snark aside, this is an actual problem for a lot of developers in varying degrees, not understand anything about the layers below make for terrible layers above in very many situations.
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