I don’t think kids should be insulating from AI. The examples in this article suggest for example that some people are dropping out of college and going into trade schools. I get that society needs electricians and construction workers and new software graduates are finding it difficult to get jobs. But having had a moderately successful career building software, I tend to think there is a lot of scope for the $40 trillion white collar economy to be disrupted (re-imagined/made more efficient), so still see potential for software engineering demand to stay high over the next decade as the true ramifications of AI plays out. Am I biased/coping? Is this moving faster? Slower? - What should kids be aiming for according to you? Computer Scientist? Biologist? Finance? Construction?
Optimistically, I hope it filters out the people who were only interested in it for the money.
When I was in school, decades ago now, very few people went into CS compared to other majors. Everyone I knew going into it did it because they loved it. I would have done it regardless of the career opportunities because I want to build stuff.
Interviewing candidates over the years since then, my experience has been there are still very few of those passionate nerds and a lot of people who did it for other reasons, like the money or similar. There is nothing inherently wrong with this. I don’t fault people for it.
Maybe if we get very lucky, it will go back to a relatively few passionate people building stuff because it is cool?
Having an industry’s labour supplied only by those inherently passionate about it is a great way to crush wages and working conditions. Look at what companies like Blizzard get away with because their employees just want to make video games at their favourite dev studio. While they’re a pain in the ass sometimes, I welcome the devs who are only here for the cash.
This is totally leaving out the supply and demand aspect. People like the idea of making games more than working on the plumbing of some accounts payable software, so Blizzard can pay less and treat worse than NicheBoringFinanceCo.
> Maybe if we get very lucky, it will go back to a relatively few passionate people building stuff because it is cool?
I think we basically lost this when software/computer/internet entered the mainstream. Now, like everything else, it has to be bland, unoffensive, and a commodity.
>Optimistically, I hope it filters out the people who were only interested in it for the money.
I hope not, because we don't need software developers to be "starving artist 2.0".
And on that note: I vividly remember people staying away from the video game development industry because it was deemed "passion industry", and that had a really negative connotation of long working hours for asymmetrical return, and more.
I don't look forward for every other software engineering branch to become like that.
Brother, we need to eat. You don't need to go to college to learn about some topic, you can pirate textbooks. You need to go to college to get a piece of paper saying you did. If you were passionate about computer programming, you can do it in your free time while you flip burgers or do whatever you need to survive
Even if people assume the worst impacts of LLMs on white collar work, there is simply not enough demand for electricians and plumbers for that to work, right now these professions work only because the number of people going into them is limited.
The prevailing sentiment on HN is that AI will make coders 10x more productive, but that we'll all keep our jobs and salaries, with the possible exception of people who don't embrace AI quickly enough.
But let me ask you this: has AI made life easier for illustrators, book authors, or musicians? They were affected by the technology earlier on. If they don't embrace AI, they face increased competition from cheaply-produced products that the average consumer can't distinguish from the "real" thing. But if they embrace it, they can't differentiate themselves from the cheaply-produced content! In fact, for artists, the best strategy may be to speak out very vocally against AI, reject it early on, and build a following of like-minded consumers.
I am not quite sure with the controversy at archive.ph/(today) but If this may help anybody, I have used single-file to download from archive.ph and uploaded it to github
Disturbingly, AI is set to replace essentially any position that is useful, to the extent that it is useful and somehow some people still think they should adapt themselves to the system instead of working to adapt the system to them!
Basically all that would be left of desk jobs would be those which have unfair legal powers (including via licenses and credentials) or are pure accountability plays. Like politicians, lawyers, aircraft pilots, corporate accountants... And those jobs will suck because people will be accountable for work that is not their own.
These jobs won't require any skills because most people may be able to go through their entire career without doing any work. But they will get paid a lot just for having being selected for their position... While other people who may be more skilled than them might be broke and homeless.
I'm somewhat skeptical of this "enter the trades" movement. Actually, I am more skeptical of that statement than I am of LLM's replacing white collar work in general. I think parts of coding are being replaced quickly because they are the parts that don't require discernment. Trades likely contain just as many automatable and just as many discernment parts as white collar work. At this moment in history, the automatable parts are being automated in the knowledge based world. People think the physical world is somehow different, but with world models (along the full spectrum of what that means) the physical world will be just as trainable as the knowledge based world.
tldr; Just like knowledge work, most trade stuff is probably mostly repeated (i.e. very trainable) task with a small amount of taste and discernment applied. The repeated will be trainable, the discernment may be trainable. I don't think the physical world is necessarily any safer than the knowledge world.
Hasn't the US already minimised the cost of all the construction work that are "the parts that don't require discernment" to minimum wage who-cares-if-they're-documented-or-not day workers?
Robots are expensive, software is not. I can instantly duplicate software 1 million times and run it in parallel, I can't just produce 1 million robots. Physical world is always harder.
Even if we get robots who can, say, build roads start to end, there is still a HUGE gap between that and it actually being used. There is a hard floor, too. Robots are made of physical things, physical things have scarcity, and there's no way around that to our knowledge. Even if you can build the robot for 1 cent, the material cost will still exist.
The difference is the physical aspect of the trades. The design for wiring can be (and already has been) automated, but you physically need an electrician on site to pull the wires. So I can see a hollowing out of the engineers, but not the actual electricians.
That being said, the absolute focus on trades from the fed right now just reeks of the wild pendulum swing. It used to be 'go to college to get a good job' then we had too many college grads. In ten years we'll have a glut of people trained in the trades with no prospects.
It just keeps swinging back and forth and somehow Joe Regularworker keeps losing.
I'll say invest totally in domain knowledge now. The value of knowing how to invert a binary tree from memory has dropped to approximately zero. Web development as we knew it for the past 20 years is completely dead as an entry level trade. The power is shifting to people with useful knowledge and expertise that isn't about twiddling bits.
I think this is true today, especially with complex domains, but I foresee a future where more and more walls fall. If you are in college now, go deep on a domain. If you are entering in 10 years, I have no idea.
Domain knowledge as in non public aspects of the work you/ your workplace does. The AI tools are very good at whatever is public but very clueless about proprietary domains .Let's say you make CRUD apps about some confidential domain. Now the CRUD skills might be commodity but the confidential domain is even more important.
As long as there's internal documentation, which virtually every serious shop has, it can be processed and combined with AI. There are startups selling this product already. I've seen first hand some very narrowly focused domain knowledge becoming more accessible when you can ask the chatbot and the thing is right. It works.
Come to think of it, domain knowledge should be an LLMs strong suit as long as you can provide the right documentation, which is working pretty well already.
Right now the main issue I see with AI is that it doesn't do well with scaling. It's great for building demos and examples but you have to fix its code for real production work. But for how long?
In ERP software there are MLOCs without any technical documentation. And nobody would spend a dime to create one. So, the deep expert knowledge on how business processes are supposed to work (in full detail) and how they are implemented is mostly in the heads of a couple of people.
AI is most excellent at reading and understanding large codebases and, with some guidance docs, can easily reproduce accurate technical documentation. Divide and conquer.
But everyone at the company has that private domain knowledge. The only thing you're bringing to the table that anyone in any other role doesn't offer is the commoditized skill set.
Right, and you'll not keep everything out of materials like AI
generated meeting notes for every repeat of every process so
the company doesn't really need many experts in its existing
operations.
Can't speak to the OP, but lots of technical work (and frankly many trades are also technical) doesn't lend itself to text based documentation and teaching. Software, translation, non/fiction writing (like marketing and sales) all do. I think LLMs will take a significant part of those businesses, because I don't believe there is a Devon's Paradox for code -Tractors- Agents.
At the same time medicine, hardware design, good industrial, and specific domain knowledge (problems you solve in assembly or control loops) that are fundamentally proprietary and aren't well documented will continue to have value even when LLMs make solving the problems around them easier. Those might have increased leverage, at least for this round of LLMs. Now, maybe they succeed in World Models, but that is not today.
Really, I don't know what "kids these days" are going to do. I couldn't have predicted the influencer boom 15 years ago, but I also think there are geopolitical risks that are probably bigger than that shift, and "synergized" with the push to AI Everything, it doesn't look like a good time to be a learning/working human.
Pre-LLMs, algorithmic knowledge was used as a proxy for skill difference at interview stage. In the workplace, you could google the implementation details and common gotchas. This was valuable knowledge.
Post-LLMs, the value of this (as differentiator) has dropped to zero. Domain knowledge (also known as business knowledge) is the obvious area to skill up on. It simply means knowledge about the area your organisation is working in. Whether it is yogurt delivery logistics, clothing manufacturing supply chain systems, etc. That's the real differentiator now. Anyone can invert a binary try in 5 minutes using an LLM. But designing a software system knowing well the domain your organisation is in is invaluable.
Right, bridging the gap of knowledge by getting closer to that of the clerical workers of the company, because pure software knowledge is no longer as valuable. That will probably make your salary closer to theirs, and that'll be a pretty big adjustment.
When I was in school, decades ago now, very few people went into CS compared to other majors. Everyone I knew going into it did it because they loved it. I would have done it regardless of the career opportunities because I want to build stuff.
Interviewing candidates over the years since then, my experience has been there are still very few of those passionate nerds and a lot of people who did it for other reasons, like the money or similar. There is nothing inherently wrong with this. I don’t fault people for it.
Maybe if we get very lucky, it will go back to a relatively few passionate people building stuff because it is cool?
I think we basically lost this when software/computer/internet entered the mainstream. Now, like everything else, it has to be bland, unoffensive, and a commodity.
I hope not, because we don't need software developers to be "starving artist 2.0".
And on that note: I vividly remember people staying away from the video game development industry because it was deemed "passion industry", and that had a really negative connotation of long working hours for asymmetrical return, and more.
I don't look forward for every other software engineering branch to become like that.
I initially pursued my real passion which was math and physics and got a cold water bucket to the face only after grad school.
But let me ask you this: has AI made life easier for illustrators, book authors, or musicians? They were affected by the technology earlier on. If they don't embrace AI, they face increased competition from cheaply-produced products that the average consumer can't distinguish from the "real" thing. But if they embrace it, they can't differentiate themselves from the cheaply-produced content! In fact, for artists, the best strategy may be to speak out very vocally against AI, reject it early on, and build a following of like-minded consumers.
1) The supply of work will skyrocket when everyone will flock there for work
2) Demand will plummet as the white collar people who bought these services will loose their jobs and income
And of course if robotics will get solved to an acceptable degree most of those jobs will also get mostly automated.
https://serjaimelannister.github.io/wsj-article/
and I have also uploaded the github link on archive.org for persistence/archival purposes.
https://web.archive.org/web/20260322213950/https://serjaimel...
I hope that this might help some people and I have another friendly suggestion to please donate to archive.org :-)
Cloudflare flags archive.today as "C&C/Botnet"; no longer resolves via 1.1.1.2
related:
https://news.ycombinator.com/item?id=46843805 "Archive.today is directing a DDoS attack against my blog"
Basically all that would be left of desk jobs would be those which have unfair legal powers (including via licenses and credentials) or are pure accountability plays. Like politicians, lawyers, aircraft pilots, corporate accountants... And those jobs will suck because people will be accountable for work that is not their own.
These jobs won't require any skills because most people may be able to go through their entire career without doing any work. But they will get paid a lot just for having being selected for their position... While other people who may be more skilled than them might be broke and homeless.
tldr; Just like knowledge work, most trade stuff is probably mostly repeated (i.e. very trainable) task with a small amount of taste and discernment applied. The repeated will be trainable, the discernment may be trainable. I don't think the physical world is necessarily any safer than the knowledge world.
Even if we get robots who can, say, build roads start to end, there is still a HUGE gap between that and it actually being used. There is a hard floor, too. Robots are made of physical things, physical things have scarcity, and there's no way around that to our knowledge. Even if you can build the robot for 1 cent, the material cost will still exist.
That being said, the absolute focus on trades from the fed right now just reeks of the wild pendulum swing. It used to be 'go to college to get a good job' then we had too many college grads. In ten years we'll have a glut of people trained in the trades with no prospects.
It just keeps swinging back and forth and somehow Joe Regularworker keeps losing.
Come to think of it, domain knowledge should be an LLMs strong suit as long as you can provide the right documentation, which is working pretty well already.
Right now the main issue I see with AI is that it doesn't do well with scaling. It's great for building demos and examples but you have to fix its code for real production work. But for how long?
At the same time medicine, hardware design, good industrial, and specific domain knowledge (problems you solve in assembly or control loops) that are fundamentally proprietary and aren't well documented will continue to have value even when LLMs make solving the problems around them easier. Those might have increased leverage, at least for this round of LLMs. Now, maybe they succeed in World Models, but that is not today.
Really, I don't know what "kids these days" are going to do. I couldn't have predicted the influencer boom 15 years ago, but I also think there are geopolitical risks that are probably bigger than that shift, and "synergized" with the push to AI Everything, it doesn't look like a good time to be a learning/working human.
Post-LLMs, the value of this (as differentiator) has dropped to zero. Domain knowledge (also known as business knowledge) is the obvious area to skill up on. It simply means knowledge about the area your organisation is working in. Whether it is yogurt delivery logistics, clothing manufacturing supply chain systems, etc. That's the real differentiator now. Anyone can invert a binary try in 5 minutes using an LLM. But designing a software system knowing well the domain your organisation is in is invaluable.
Ain't nobody gonna hire a code monkey - you are being hired based on whether or not you can reason and enable workflows via tech.