As someone who is relatively young and thus inexperienced, this is to a large extent the million dollar question. Or, rather, the question of which skills are important is.
A lot of the people I know who are just a few years younger than me learned / are learning at university and even grade school with the use of LLMs. This, to me, is terrifying. They are forming a foundation of knowledge and skills so fundamentally different to that of people my age and older.
This is not the difference between googling vs. finding a book in the library. This is the difference between being forced to think through a question and answer vs. not thinking through it at all.
I fear that the prioritization of LLMs in so many aspects of society and the workplace encourage this, and that we don't yet have enough guardrails to protect ourselves against this atrophy.
That is a long way to say, I also tend to fall on the side of caution. I do my best to use LLMs only for things that I can not do AND do not feel that I am likely to need to be able to do in the future. Or for things that I am super confident in my ability to do and thus know right from wrong and can just use LLMs to speed myself up.
I think that as long as people have a strong foundation (though it is unclear in what is important..) than using LLMs is not the end of the world. I am more worried about a future in which we won't have a useful BS meter to check them with.
I am 52 years old. My “skills” aren’t “I codez real gud”. My skills are that I know how to take business stakeholders from “we don’t know what the hell we want and we have conflicting priorities” —> empty AWS account and empty git repo —> to full implementation architecture + code either by myself or leading a team.
Enterprise development has been commoditized for well over a decade. This is where most developers work - enterprise dev. Why am I going to waste time keeping skills relevant that companies don’t value unless you go into BigTech or adjacent (been there find that) where most developers will never get .
Anecdote: I worked for a company based in Knoxville with a satellite office in Atlanta where I worked from 2014-2016. They paid developers between $115K - $135K in Atlanta then. They just posted a job on LinkedIn with the same requirements as they were back then for $140K fully remote.
Just to keep up with inflation that should be over $180k.
Just to quick Google search shows that is still average in Atlanta.
The problem isn't "skill atrophy" — it's which skills matter more in a changing world. If LLMs genuinely do something better, let them do it and focus on what they do badly.
What I'm exploring now:
1. How to convert tokens to value more efficiently
2. How to orchestrate a large LLM team instead of babysitting one session
3. How to parallelize work and make sure nothing blocks others
4. How to accelerate both productivity and quality control
5. How to make the system evolve itself
To achieve these, it requires much more skill and knowledge, not less.
I’d be really interested in other’s workflows regarding this.
I’m finding the pressure at work to be faster and more productive gets in the way of actual learning.
I’m starting to believe that code will not matter soon, as long as it works, then everything will just be a single natural language interaction to make a change.
I was concerned once I started using agents and built a tool that I use a lot when I'm building that helps me engage thoughtfully with what I'm co-creating with Agents called Intraview.
Allows Claude to create code tours I can navigate with the Agent, give feedback, and iterate together. It's a nice inner-loop step to internalize what's changing and why.
The big thing for me was switching off LLM autocomplete. I found myself typing a few characters then hovering my finger over Tab while I waited for it to catch up, instead of just typing a line I already knew how to write. So now I only use an LLM by choice when I actually need it.
I use LLMs as a coding assistant. I don't vibecode. The result is that I'm actually improving my skills much faster and better than before, while also working far more productive.
Staying in the loop and learning new tech from docs and on discord. Don't instinctively reach for Ai first, use it when you know it will actually save time
You practice doing challenging things yourself. Self-sufficiency is the name of the game. If you have already delegated your future to LLMs you are fucked and your skills will atrophy.
The best balance is give tasks to LLMs that consume large amounts of time but are either not challenging or heavily repetitive. My example would be handing off writing test automation cases but retaining all original authoring for experiments and design decisions.
As someone who is relatively young and thus inexperienced, this is to a large extent the million dollar question. Or, rather, the question of which skills are important is.
A lot of the people I know who are just a few years younger than me learned / are learning at university and even grade school with the use of LLMs. This, to me, is terrifying. They are forming a foundation of knowledge and skills so fundamentally different to that of people my age and older.
This is not the difference between googling vs. finding a book in the library. This is the difference between being forced to think through a question and answer vs. not thinking through it at all.
I fear that the prioritization of LLMs in so many aspects of society and the workplace encourage this, and that we don't yet have enough guardrails to protect ourselves against this atrophy.
That is a long way to say, I also tend to fall on the side of caution. I do my best to use LLMs only for things that I can not do AND do not feel that I am likely to need to be able to do in the future. Or for things that I am super confident in my ability to do and thus know right from wrong and can just use LLMs to speed myself up.
I think that as long as people have a strong foundation (though it is unclear in what is important..) than using LLMs is not the end of the world. I am more worried about a future in which we won't have a useful BS meter to check them with.
I am 52 years old. My “skills” aren’t “I codez real gud”. My skills are that I know how to take business stakeholders from “we don’t know what the hell we want and we have conflicting priorities” —> empty AWS account and empty git repo —> to full implementation architecture + code either by myself or leading a team.
Enterprise development has been commoditized for well over a decade. This is where most developers work - enterprise dev. Why am I going to waste time keeping skills relevant that companies don’t value unless you go into BigTech or adjacent (been there find that) where most developers will never get .
Anecdote: I worked for a company based in Knoxville with a satellite office in Atlanta where I worked from 2014-2016. They paid developers between $115K - $135K in Atlanta then. They just posted a job on LinkedIn with the same requirements as they were back then for $140K fully remote.
Just to keep up with inflation that should be over $180k.
Just to quick Google search shows that is still average in Atlanta.
The problem isn't "skill atrophy" — it's which skills matter more in a changing world. If LLMs genuinely do something better, let them do it and focus on what they do badly.
What I'm exploring now:
1. How to convert tokens to value more efficiently
2. How to orchestrate a large LLM team instead of babysitting one session
3. How to parallelize work and make sure nothing blocks others
4. How to accelerate both productivity and quality control
5. How to make the system evolve itself
To achieve these, it requires much more skill and knowledge, not less.
Love that idea of compounding your skills and driving that into a new area!
I’d be really interested in other’s workflows regarding this.
I’m finding the pressure at work to be faster and more productive gets in the way of actual learning.
I’m starting to believe that code will not matter soon, as long as it works, then everything will just be a single natural language interaction to make a change.
Thats all that employers ever cared about
I was concerned once I started using agents and built a tool that I use a lot when I'm building that helps me engage thoughtfully with what I'm co-creating with Agents called Intraview.
Allows Claude to create code tours I can navigate with the Agent, give feedback, and iterate together. It's a nice inner-loop step to internalize what's changing and why.
Im waiting for things to start breaking
The big thing for me was switching off LLM autocomplete. I found myself typing a few characters then hovering my finger over Tab while I waited for it to catch up, instead of just typing a line I already knew how to write. So now I only use an LLM by choice when I actually need it.
Yea, I'm afraid of that too. AI atrophies the brain.
https://www.rxjourney.net/how-artificial-intelligence-ai-is-...
I use LLMs as a coding assistant. I don't vibecode. The result is that I'm actually improving my skills much faster and better than before, while also working far more productive.
What is your Workflow?
Staying in the loop and learning new tech from docs and on discord. Don't instinctively reach for Ai first, use it when you know it will actually save time
How do I…
You practice doing challenging things yourself. Self-sufficiency is the name of the game. If you have already delegated your future to LLMs you are fucked and your skills will atrophy.
The best balance is give tasks to LLMs that consume large amounts of time but are either not challenging or heavily repetitive. My example would be handing off writing test automation cases but retaining all original authoring for experiments and design decisions.
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