I get the analogy of the calculator. The thing however, is that in college, we had dedicated time to learn how to not use it: classes without it, exams without it, etc.
In current job market and pressure, we doesn't have time anymore. You need to be constantly delivering the new jira ticket, and the time expected to perform a task now decreased, as it's expected of the workers that now they are "more productive with AI".
I think 'expertise' is a bit of a red herring when what is being discussed is experience.
I've always believed that coding and development is an art and something analogous is the experience of a visual arts student. There's a level of experience required when one applies to an art school. The student builds a portfolio of passion projects and demonstrates a passion and skill along with creativity and other beneficial traits. If they are accepted, they learn the deeper theory, techniques, and more that will aide them in their career. This increases their exposure and overall experience.
Experience for a young developer is going to start with passion projects and be supplemented and bolstered through education in a similar way. You can take shortcuts as an arts student or a developer but you really just end up hurting yourself.
The calculator analogy is more warning than reassurance. Human calculators went extinct. What survived was mathematical reasoning — a different skill entirely. The question isn't whether "coding education" will persist, it's which parts of coding are computation (syntax, boilerplate, API lookup) and which are reasoning (systems design, tradeoff analysis, debugging intuition).
I think the article underweights one skill that becomes more valuable with AI: verification. Knowing when AI output is subtly wrong — the off-by-one that compiles, the race condition that passes 90% of tests, the architectural choice that crumbles at scale. This isn't the same muscle as writing code. It's closer to adversarial testing, code review, and production debugging.
On teams I've managed, I've seen senior engineers miss AI-generated bugs because they trust the output, while methodical juniors catch them precisely because they don't trust it. The junior who builds a reputation as "the person who finds what the AI missed" becomes more valuable than the senior who produces volume without verification.
The pipeline problem is real, but the solution isn't necessarily "more manual coding." It might be training for verification fluency — the ability to read, test, and challenge AI output at a level deeper than surface correctness. That's a teachable skill that doesn't require 5 years of writing code from scratch.
Sorry for the off-topic comment, but what happened to the front page? At the time I’m writing this, 11/30 submissions are related to AI. Maybe my comment is cliché too, but I’m honestly tired of all the AI stuff.
Actually - to disillusion yourself from AI, try dabbling into something you do not know. Try writing a production quality 3D engine. Trust me, a 3D engine has its own domain knowledge besides just graphics. No, seriously. And then see how helpless you feel when you yourself do not have the expertise to judge whether the direction being taken is the right or wrong.
At that time, you wish if there were some pipe through which you could reach John Carmack, Tim Sweeney, Gabe Nawell, Jonathan Blow some Casey Muratori and just ask one thing:
Sir, is this really the right direction?
These tools feel good when you yourself are a domain expert. I have written backend systems and designed REST APIs all my life in multiple languages in Java, Python, Go, Ruby for multiple verticals I'd say I am damn expert at API design including all the layers that go under it and I can confidently give a shut up call to an LLM knowing what I know.
Fuck the bean counters and the greedy parasite execs and VPs. Hug a junior today, society will need them tomorrow because I was a clueless junior once and my seniors were very kind to me that I am able to put bread for my family on the table.
I think that the universities have an opportunity here to be the places where manual code is written so that juniors can gain the coding expertise necessary to become effective with AI.
Many universities are not set up to take advantage of this opportunity because they lean heavily into theory and look down on coding, but some departments will make the pivot well. I hope that ours (Montana State) is one of them.
The argument for universities to be a place to learn to think critically and not learn specific skills is an even stronger value prop in an era where useful skills likely change rapidly.
There needs to be a realization of how important communication skills are to develop and possess. The act of disagreement has skill levels that do not trigger emotional responses, and cause cross understanding to occur. Learning how to convey understanding and gain understanding from others becomes more and more important in a landscape of rapid change. Which we are collectively terrible at, with most companies being miscommunication circuses, with all the stress that generates, needlessly.
The problem is that professors say "learn to think critically", then actually just want the students to learn to sound like them, and agree with them. Actual critical thought has been on the decline for some time.
This is especially true in the humanities and the social sciences. Where truth is hard to ascertain, and therefore it is easier to substitute political correctness for critical thought.
Some will probably dismiss your comment as partisan but it is very hard to (honestly) argue that this isn’t the case. “Think critically…” but only about the cliché punching bags of academia: capitalism, Western culture, American foreign policy, The Patriarchy, etc. I didn’t witness any college classes that encouraged us to think critically about socialism, or think critically about Islam, or think critically about non-Western countries’ foreign policy aims, or think critically about third-wave feminism’s impact on society. Instead, even questioning any of those sacred cows usually brands you as “far right” and professors sometimes even get fired for making others “feel unsafe” if they even try.
so universities become trade schools? one concern is where does one get theoretical knowledge required for e.g. going to graduate school and then doing research to push the state of the art. that's one of the reasons universities emphasize theory: it's seen as the first step on the academic ladder, not as a trade school
At some point we will have to stop treating universities as tests to pass, and actually what they claim to be: places to learn. Ultimately it needs to be on the student to want to learn.
Obviously this would be easier if our entire school system before university wasn't seemingly designed too destroy every last ounce of a child's curiosity.
What’s built with all that VC money is already built though; I don’t foresee a future a few years out where we don’t have access to an open-source model roughly as good as the current flagship models for the cost of the compute itself.
Variable costs - electricity etc. Current model is very resource intensive. You know when they build all those Olympic Venues and then once the Olympics is done the ongoing cost is too expensive and then they become derelict buildings.... like that...
> And yet, OpenAI, Anthropic, and many top companies continue to compete fiercely for junior talent.
Are they? I would imagine they have the luxury to pick the brightest candidates, and set them to work on jobs for which their models don't have training data for, such as developing new models. Not writing React code.
I get the analogy of the calculator. The thing however, is that in college, we had dedicated time to learn how to not use it: classes without it, exams without it, etc.
In current job market and pressure, we doesn't have time anymore. You need to be constantly delivering the new jira ticket, and the time expected to perform a task now decreased, as it's expected of the workers that now they are "more productive with AI".
I think 'expertise' is a bit of a red herring when what is being discussed is experience.
I've always believed that coding and development is an art and something analogous is the experience of a visual arts student. There's a level of experience required when one applies to an art school. The student builds a portfolio of passion projects and demonstrates a passion and skill along with creativity and other beneficial traits. If they are accepted, they learn the deeper theory, techniques, and more that will aide them in their career. This increases their exposure and overall experience.
Experience for a young developer is going to start with passion projects and be supplemented and bolstered through education in a similar way. You can take shortcuts as an arts student or a developer but you really just end up hurting yourself.
The calculator analogy is more warning than reassurance. Human calculators went extinct. What survived was mathematical reasoning — a different skill entirely. The question isn't whether "coding education" will persist, it's which parts of coding are computation (syntax, boilerplate, API lookup) and which are reasoning (systems design, tradeoff analysis, debugging intuition).
I think the article underweights one skill that becomes more valuable with AI: verification. Knowing when AI output is subtly wrong — the off-by-one that compiles, the race condition that passes 90% of tests, the architectural choice that crumbles at scale. This isn't the same muscle as writing code. It's closer to adversarial testing, code review, and production debugging.
On teams I've managed, I've seen senior engineers miss AI-generated bugs because they trust the output, while methodical juniors catch them precisely because they don't trust it. The junior who builds a reputation as "the person who finds what the AI missed" becomes more valuable than the senior who produces volume without verification.
The pipeline problem is real, but the solution isn't necessarily "more manual coding." It might be training for verification fluency — the ability to read, test, and challenge AI output at a level deeper than surface correctness. That's a teachable skill that doesn't require 5 years of writing code from scratch.
Don't post generated comments or AI-edited comments. HN is for conversation between humans.
This is a valuable insight, Seniors engineers have often built a career out of building intuitions around when to trust people, not AI.
Sorry for the off-topic comment, but what happened to the front page? At the time I’m writing this, 11/30 submissions are related to AI. Maybe my comment is cliché too, but I’m honestly tired of all the AI stuff.
Been away for a while? It's been like this for at least a year.
5 years ago it was web3. 5 years before that it was Haskell and monads. It’s how things work
It's polluting the world, gobbling up hardware, and making us dumber. And HN and LinkedIn just can't get enough.
People say AI is the new internet. I say AI is the new tobacco.
Honestly, at this point it's an accurate reflection of the reality of tech.
Personalization would solve that.
AI can solve it too.
I don't think you can ignore it. It's the biggest change to tech in 30 years I'd say.
"I'm tired of all this internet talk" in 1990s?
Actually - to disillusion yourself from AI, try dabbling into something you do not know. Try writing a production quality 3D engine. Trust me, a 3D engine has its own domain knowledge besides just graphics. No, seriously. And then see how helpless you feel when you yourself do not have the expertise to judge whether the direction being taken is the right or wrong.
At that time, you wish if there were some pipe through which you could reach John Carmack, Tim Sweeney, Gabe Nawell, Jonathan Blow some Casey Muratori and just ask one thing:
Sir, is this really the right direction?
These tools feel good when you yourself are a domain expert. I have written backend systems and designed REST APIs all my life in multiple languages in Java, Python, Go, Ruby for multiple verticals I'd say I am damn expert at API design including all the layers that go under it and I can confidently give a shut up call to an LLM knowing what I know.
Fuck the bean counters and the greedy parasite execs and VPs. Hug a junior today, society will need them tomorrow because I was a clueless junior once and my seniors were very kind to me that I am able to put bread for my family on the table.
> Try writing a production quality 3D engine.
Actually I tried that and you are correct about this.
With Claude it took me hundreds of iterations and I'm still not happy.
I think that the universities have an opportunity here to be the places where manual code is written so that juniors can gain the coding expertise necessary to become effective with AI.
Many universities are not set up to take advantage of this opportunity because they lean heavily into theory and look down on coding, but some departments will make the pivot well. I hope that ours (Montana State) is one of them.
The argument for universities to be a place to learn to think critically and not learn specific skills is an even stronger value prop in an era where useful skills likely change rapidly.
There needs to be a realization of how important communication skills are to develop and possess. The act of disagreement has skill levels that do not trigger emotional responses, and cause cross understanding to occur. Learning how to convey understanding and gain understanding from others becomes more and more important in a landscape of rapid change. Which we are collectively terrible at, with most companies being miscommunication circuses, with all the stress that generates, needlessly.
The problem is that professors say "learn to think critically", then actually just want the students to learn to sound like them, and agree with them. Actual critical thought has been on the decline for some time.
This is especially true in the humanities and the social sciences. Where truth is hard to ascertain, and therefore it is easier to substitute political correctness for critical thought.
Some will probably dismiss your comment as partisan but it is very hard to (honestly) argue that this isn’t the case. “Think critically…” but only about the cliché punching bags of academia: capitalism, Western culture, American foreign policy, The Patriarchy, etc. I didn’t witness any college classes that encouraged us to think critically about socialism, or think critically about Islam, or think critically about non-Western countries’ foreign policy aims, or think critically about third-wave feminism’s impact on society. Instead, even questioning any of those sacred cows usually brands you as “far right” and professors sometimes even get fired for making others “feel unsafe” if they even try.
so universities become trade schools? one concern is where does one get theoretical knowledge required for e.g. going to graduate school and then doing research to push the state of the art. that's one of the reasons universities emphasize theory: it's seen as the first step on the academic ladder, not as a trade school
They don't know it yet but universities have a role to curate training data, so we can have trustable models.
Agreed, but I can immediately see how painful it will be to monitor whether the work is actually done by the student.
At some point we will have to stop treating universities as tests to pass, and actually what they claim to be: places to learn. Ultimately it needs to be on the student to want to learn.
Obviously this would be easier if our entire school system before university wasn't seemingly designed too destroy every last ounce of a child's curiosity.
AI is cheap right now. Let's re-ask this question when it's priced to recover profit and ROI.
What’s built with all that VC money is already built though; I don’t foresee a future a few years out where we don’t have access to an open-source model roughly as good as the current flagship models for the cost of the compute itself.
Variable costs - electricity etc. Current model is very resource intensive. You know when they build all those Olympic Venues and then once the Olympics is done the ongoing cost is too expensive and then they become derelict buildings.... like that...
> And yet, OpenAI, Anthropic, and many top companies continue to compete fiercely for junior talent.
Are they? I would imagine they have the luxury to pick the brightest candidates, and set them to work on jobs for which their models don't have training data for, such as developing new models. Not writing React code.