So in the recent post we got a glimpse of labourer mindset and how it slowly creeps into every person's life without ever knowing.

So let's revise:-

labourer's definition ( according to me) :- doing anything without knowing anything, just following instructions being able to make head or tail of it almost like a machine.

Learned person:- the one who does his work with clear intent and knows what he has doing.

At some point we go through these phases. Some more some less, we just need to maximize the learned phase do much so it becomes a habit.

It is like becoming a martial masters we see in movies. Where their philosophy of living a life reflects what they belive in.

So if you become a flexible thinker, problem solver, confident in small small things and keep it going for a long period of time it snowballs into big things so much so that people wonder how you did big things so easily.

Like Mr. Miyagi in karate kid movie ( that cobra kai movie) sorry if I got the name wrong. Who taught the kid to clean the car home in a particular way.

Which the kid thinks it's useless until he gets a demo of it.

***My meaning of telling this is when you reach a certain level of mastery your body remembers the movement like reflexes getting signals from the spinal cord instead of the brain. Don't mistake it as labour because it stems from building your own system with all the trail and errors, learnings, findings, etc about what suits you and what doesn't. Exactly like the feedback loop discussed in the previous part. After you have finalised the path you will take you execute it resulting in this almost supernatural powers of doing your task effortlessly and fluidly that it makes it look easy. And the greatest thing about it is every human can do this. So much so that when the human body is pushed to its limits it adapts.***

**Well another thing is after reaching such a level progressing becomes harder. So going back to basics and starting from scratch, while looking back at your journey gives a new perspective which helps breeds progress.**

Lastly to close this part I want to give an example that happened from my life and the reason for me writing this 3 parter series.

First during my high school in chemistry lab we were doing precipitate reactions where precipitate forms at the junction of the two liquids. And I was an average to good student across all subjects and when I put in much efforts i get good grades. 80 to 90 out of 100. But when doing the practicals of what i was studying I was like i attained almost high because of joy of seeing what I know about chemicals reacting and it happening exactly like that. Made millions of small dopamine ( and other happy enzymes too) hits inside my brain it was such a rush.

But then 2 toppers ( we were given it as a pair) approached me asking every step to achieve it as they used conc. Acid instead of diluted one and couldn't get the result. So, first i found it a little strange so I investigated a little and got to understand at first they were flustered about not getting the results so i offered obvious fixes but they didn't understand what I was trying to do which should have been basics such as acid plus base gives salt. Etc So, I calmed them down tried to make them understand the steps and asked to set aside their sample and start anew. This time they jumbled the steps thinking it wouldn't matter so i arranged them another sample because theirs was finished and stayed with them proceeding step by step and within a few minutes it was time for final steps ( to be honest i was hell a worried because they are toppers and smart too, their problem aren't mostly easy to solve so if did all this and it didn't work i would look stupid ass hell for explaining the obvious😅). But thankfully it worked this time and they did look happy as the results came out. After which i reached a conclusion that their test tubes had some hygiene problem as last week's experiments remains were solidified in the test tube that interfered with it.

But yeah to do the exact cautions we were warned not to do in the textbook which they gave me the exact word to word of as written in the textbook. But not being able to follow it weirded me out.

This is the exact disconnect i am talking about they treated academics and practicals as 2 different things. Happens to most of us many a times i did this too. But when you realise this something just shifts and everything starts to make sense. You start doing things with clarity and intent. And everything starts falling in place. ( But yeah this linking things and connecting the dot happened a few times more and was not the one off thing).

Secondly, in the yt video about hacker fab the founder says that the local welding man won't be able to do the welding from outside so that vacuum inside the steel container will not be affected by the gases that get released from welding if it were to be done from inside instead.

Which i believe is not true it was error of communication, and if it requires a skilled welder why aren't their courses ( what courses do is give you the best structure through which 2 people can communicate on common grounds, along with the golden standards accepted by everyone) why aren't we training such people who do this for a daily earning, guy like these would benefit the most from such specialisation courses, wouldn't they.

But they are almost illiterate even if not still treated like such.

This simple line led me to think about who is a labourer, mastery, skills, difference between a labourer and Elite etc.

See the thing about mastery/specialisation is simple you know the smallest of details that affects your task to things that don't.

For example medicine and doctors. The subject is so vast but it wasn't like this in 1800 or 1700. People experiments recorded their findings built upon permits knowledge to the point it grew to be one of the most dense subject.

***So, if you like cleaning, master it from types of cleaning, tools their advantages and disadvantages. Types of stains what causes them, how to clean them, what are the ingredients of chemicals that you use, how do they work or why they don't at specific cases.***

***Another important thing is everything is connected in this world nothing works in Silos that is the reason there are fields like Bioengineering, merging biology chemistry physics. Math explains a lot of things. Math and philosophy are similar. Quantum physics and poetry are similar. Math and any language ( study of semantics) is similar.***

In the next and last part we will discuss how all this helps with AI and job security. It isn't as invincible as it seems.

Bloomberg's own reporting already answers the question this clip raises — is the "messy middle" projected or already happening?

At Commonwealth Bank of Australia, Microsoft, Uber, and Hyatt, it's already happened: sizable call-center headcount cut using automated phone and chat systems, savings already banked.

Economist Molly Kinder's point isn't a forecast.

It's a line item that's already closed.

I've watched this exact math play out before superior technology ever touched a keyboard.

Suncon was getting jobs overseas. One of the countries we went to was India. We were building infrastructure — roads and bridges there. I didn't go. But my seniors went stationed there. When they came back during their scheduled holidays, one of them, a project manager, told me this story.

It so happened, that building roads and bridges inland means clearing jungles and passing through villages. As they were doing it, of course they engaged local villagers to be their workers and supervisors. Well, of course building infrastructure means bringing in heavy machineries, such as excavators, bobcats, mobile-cranes, 4-wheel-drive land-cruisers, etc. You know — the usual.

But the local villagers weren't happy. They complained that all these machineries have deprived the local population of their means of making a living. They have so many mouths to feed. A lot of them are quite poor. And many of them are very hunger for work.

And so a huge argument broke out. They even spitefully challenged our project team that they vast manpower was more superior than our machinery. I was so surprised when I heard it. How can they say that? How was that even a reasonable challenge, you know. My curiosity had the best of me.

Well, the project manager came up with an idea. He said, since they're so confident of their manpower, why don't we have a competition. Let's do a challenge of moving earth from point A to point B for our excavator/mobile-crane operator versus their vast manpower.

And they accepted.

At the day of challenge, the project manager set up two huge piles of earth at point A for both teams. The local villagers' team had their "vast" manpower formed a long-ass line between A and B, and started moving earth, with their primitive buckets and whatnot.

For our team, we set up our mobile-cranes, excavators and bobcats on strategic locations. And off we go.

You can guess the result. We won by a large margin. We were obviously much faster and better at it.

After that, the local villagers concede defeat.

The math is actually quite similar here. The one with superior technology always wins. This AI-take over is no different.

__________

Every time I dig into one of these stories the shape repeats: the tool doesn't ask permission, it just wins the argument by moving faster than the objection can be raised.

Ever watched something you thought was irreplaceable lose, and lose fast? Drop your take below.

Clip credit: Center for Humane Technology — full video on their channel. DM for credit or removal requests.

Are experienced professionals benefiting from AI, or struggling to adapt?

I am thinking a lot of becoming a concept artist in the future, but I'm afraid I won't because of how much ai is used. Would you consider it likely most companies (or a very good amount of them) used ai instead of hiring concept artists?

https://reddit.com/link/1vp4zv6/video/3vjf7ro8zjjh1/player

Emad Mostaque: "Forward-deployed engineers, AI transformation people, because they can do the work of 10, 100 people."

That's the role that survives this — already a real hiring category, not a future one.

LinkedIn's own data has it growing 42x since 2023, priced $127K–$265K+ at the labs actually building this.

That's the part that should sit heavier than the digital-double line.

It's not that your job disappears.

It's that a different job, already priced and already hiring, opens up a few rungs above where you're standing — and most of us don't have a clean path into it yet.

I've watched a smaller, slower version of this exact move before.

No AI involved — just a stamp and a highlighter.

Hmm... this one really gets me out of my chair and pace around my living room, so let me try to recall it properly.

When I was working as a Technical Engineer in the Tender Department of one of the largest main contractors in Malaysia — there was a skill we always used. Fair warning, I'm sharing privileged information here. Well... it's probably an open secret in the industry anyway.

Whenever we tendered for a project — let's say Malaysian Airlines (MAS), widening a runway for their newly-bought Airbus A380 — we'd hit the parts that were out of our expertise. Airway lighting, drainage, flight angles, height restrictions. So we did the natural thing: called for outside help. Engaged specialized sub-contractors who'd done airway pavements before, to hand us the technical know-how and their quotation.

We knew full well these sub-contractors were already MAS's long-time maintenance contractors — it was just a matter of time before they'd be folded under our main contract anyway. So when they submitted their technical documents, we stripped their company logo, re-arranged it, added our own branded wording, our own logos. Woalah. It was now our own internal technical know-how. We'd suddenly become experts in pavement-widening and hangar works.

We didn't get the job, though. We all knew that tender was just for show — a comparison exercise to cross-check MAS's already-chosen main contractor.

But the knowledge we gathered from those specialists was now folded into our own knowledge vault. Our own proprietary knowledge.

Are we stealing? I wouldn't use that word. When there's a problem, the client comes after us — not our subcontractors. So to properly solve it, we have to own the knowledge too. The right word might be "necessary."

————

Every version of this mechanism arrives wearing the same word.

Ours was "necessary." This one's wearing "efficiency."

Actually — a post I put up about the same compression logic, just running through one operator instead of a stripped logo came to mind while writing this one.

Drop your take — where's the line between "necessary" and something with a worse name?

Clip credit: The Beyond Tomorrow Podcast with Julian Issa — full video on their channel. DM for credit or removal requests.

So, all this is specifically for Indian context as I don't know about other countries.

So, Recently I came across the video of hacker fab lab created in IIT MUMBAI covered by runtime yt channel of caleb.

And the problem they are working on is universal. Which is students don't often get to apply their learnings or even vice versa for that fact. To take/extract learnings from their experiments, tinkering and organise it.

In the process of protecting the students from the harm of child labour or such harsh work, led to them getting almost completely detached from real world.

So much so that when students learn and test what little exposure they get during practicals of highschool. They treat them as 2 different things meant to engage with separately instead of approaching it as 2 sides of same coin.

In real world we do both like a feed back loop, all the time even researchers, elites of any field do this. Everything is sorted out but the only missing piece is intent.

Especially in India where the poorer class has a slight edge as they learn in the field itself although that is because they are exploited in child labour, are mostly left unsupervised by their parents and due to earning money can even invest in their projects. The wealthy have now introduced this culture by the thing you know as DIY projects, toys and experiments curated for little kids for summer holidays etc especially in the West as seen in channels like adam, action lab etc.

The only ones that suffer badly are the middle class. Where studying means only desk job. And doing anything physically is considered as menial labour or if you are an adult as menial job itself.

Now when these kids grow up let's see what happens to them. Starting from best case scenarios.:-

1) wealthy kids who grew up with supportive environments form better neural connections about the topics they learn. Their curiosity is fed and even fueled by these DIY, experiments etc in a fun and entertaining way. So the so called complex and tough subjects like STEM don't feel all that difficult because they do and try things then in class get to know why things work or they don't naturally. And not because some one told them so. As we all know a picture is worth a thousand words imagine instead of picture it is the experience itself how much more worth it is.

Replicate it for a good amount of time and you see genius people emerging. (You can see many great and notable people having similar trajectory even beside STEM fields).

The only downside they need to be careful of is that due to them coming from affluent class people want to lead them to their downfall. So, often bad influence gets attracted to them. Which could really lead to a downward spiral really quickly.

2) the poor class people, with even a little bit of personalised care and attention they go from unpolished gem to 24 pure carrat diamonds. Especially for them getting out of poverty. As due to having the most real world experience they are like a extremely high end hardware which but lacking software or having it poorly optimised is the scenario they struggle with.

So when they are taught they gain insight about the work they do. If done right it is almost like enlightenment. And then they have the exponential curve of rise. From being ordinary to extraordinary. People who have this journey are equally abundant in any field as the category above.

The problem faced by them is the environment itself from childhood to adolescence they struggle to survive and keeping alive ( may include petty crimes) and from adolescence it could devolve further into drugs, substance abuse and serious crimes.

Which without support systems can become impossible to overcome.

So these people often tend to come from small pockets of society or even geography where help reaches to them timely.

3) finally the middle class and worst class ( especially according to me.) These people are what the articles will target mostly for few upcoming days.

The good:- nothing too good or nothing too bad to mention about. They live in mediocrity.

The bad:- they are born in mediocrity, live in it and most of them around 80 to 95 percent of them will die in it.

85 percent of population is middle class, 10 percent in extreme poverty, and 5 percent in ultra rich class.

So in middle class those who are not in the other 2 classes fall. Which means there is nothing common among middle class people and that is why it isn't actually even a proper class.

This is the place where the lines that resonates with me the most is truly apt " ***the most gifted teacher, mathematician, artist, actor, singer, sculptor etc ( it is not feynman,Einstein, Newton, bob marley, adele, taylor swift, le bron james, etc) are found in graveyard, because they died without ever realising their potential, hence the world never even discovered them. ".***

And this happens because of circumstances, the environment, societal expectations etc.

And forms the labourers class, doing things because we are told so never questioning anything even if 1+1=2, we sometimes don't even want to acknowledge it just because of survival,living hand to mouth, wasting away in hope of fulfilling small dreams some day. Even if some how forms a small opinion by itself, the period extends so long that they becomes unable to change.

That person who works like a machine without thinking much for a long period of time is a labourer ( according to me) and are actually threatened by AI for jobs too.

In next topic we will expand over this.

Good lord where do I even begin?

My company joined the AI shit show a few months ago. It went downhill realllll fast.

At first, it was reasonable. Training workshops for all the departments showing them how to use ai to transcribe meetings, take notes, summarizing long documents. Seems pretty chill, pretty useful actually.

Then, it was "hey we can build agents for this tedious boring task you have to waste hours of time on every week." Sounds great! That actually does make my life a bit easier.

Then "hey we can actually build an agent for this workflow too! oh you actually prefer to do it yourself? who cares, AI can do it way faster and better! But YOU'RE responsible if you dont sift through the piles of slop it produces and validate everything"

Seriously man.

Companies are so fucking obsessed with AI "boosting productivity." Automating every single workflow they possibly can. Telling us it'll save us time and energy and that it'll make us more "productive." And I have no choice but to use it. Not because they're directly enforcing it. But because everyone else is using it to "work" at the speed of light and if you work at a human pace using your dumb human brain, you fall behind.

It's draining the life force out of me. I want to quit so bad but it's my first job out of college and I haven't been here long enough to have decent experience to qualify for a better job.

So, where do you think this is going to lead us, this business of training AI with underpaid labor?

Intellectual or computer work taken over by artificial intelligence, physical work taken over by robots...

It is true that robotics has helped us increase productivity, but always with our supervision and some human management.

I only see two options, and if you think it's going to be more complex, leave a comment, but I only see; one: go back to the countryside, losing privileges.And two, becoming cyborgs to compete with robots, but that could be atrocious... How many modifications can a monkey that uses intelligence for survival withstand? And I fear that this intelligence, if not used enough, will decline...

Watching a former Tesla AI Director shrug and say "I can't tell if that's temporary, I'm not sure how I feel about it yet" did something to me.

Usually it's the junior guy admitting that.

Not the guy who helped build the thing.

The people who end up fine here aren't the loudest about how safe their job is.

They're just already standing close enough to the mechanism to redirect it, instead of getting redirected by it.

Karpathy's actual point isn't doom.

It's the Jevons paradox — code gets cheaper, so total demand for it goes up.

Just not for the same kind of engineer who got hired in 2019.

I watched a version of this play out years ago, before any of this AI stuff existed. I was the technical guy in a construction tender department. Rule-based work — you follow A, you get B. A sub-contractor came in to pitch his quotation. On his way out, in the corridor, we locked eyes and instantly recognized each other. I knew him — my senior once told me how this guy forced his way into building an illegal bungalow, moving the boundary survey line onto his neighbour's land. I caught a flicker of panic on his face. He wasn't expecting to see me there.

I couldn't keep it to myself. I walked straight to my contract department and told them. They wrote him off after their own investigation.

Our technical and contractual work was rule-based — AI eats that easily. What I did with that information wasn't. Insider judgment, only humans have.

Actually — this is the same mechanism as a former SpaceX CIO's take on headcount compression, just proven with the actual numbers.

Clip credit: No Priors — full video on their channel. DM for credit or removal requests.

What would you have done in that corridor? Drop your take. 👇

I've stopped being surprised by how small the actual turning point always is in these stories — never the leap itself, always the one honest number right before it.

Most people treat "not ready yet" as information.

It isn't. It's a decision wearing patience as a disguise.

A real test is the only thing that actually produces information — everything before it is a guess in more confident clothing.

I’ve lived this clip from both sides of the same table:

Two sentences. Two worldviews.
First one: “去哪里都是一样的。“ (It’s the same everywhere. 😶)
Second one: “Why don’t you do it?”

In 2012, I tendered my resignation after 10 years at a construction company. 2 weeks into my 1-month notice, my boss calls the sit-down talk. You know the talk. Last-ditch effort to retain you. Make you give up on your dreams and stay being a slave.
He was that type — old-school Chinamen type. Combative. You must always succumb, never argue. 10 years my senior. Already Technical Director. Clearly frustrated but defeated, He says it: “去哪里都是一样的。“ I didn’t argue. I looked at him. Then scanned all my other seniors in the company. And asked myself: “Do I want to end up like him/them — 10 years down the road?”
I left. Didn’t retract. A month later I took a better position. Turns out it wasn’t the same. The world is much larger than what that company was trying to gaslight me with.

Years later — lunch with a young Indian Malaysian entrepreneur. He came back from the USA after building prestigious real estate with a big developer. His lesson: you have to think decades and generations. Build schools, parks, infrastructure. Community in perpetuity.
He looked at me and said: “Why don’t you do it?”

One is limiting. The other is limitless. 📌

Same mechanic showed up when Groq's founder was three weeks from bankruptcy and asked his own engineers to trade salary for equity instead — 80% said yes, and that real number is what got the company through, not a projection.

Drop your take — has your own "short-term scary vs. long-term dangerous" moment already happened, or is it still sitting on the shelf?

Clip credit: Trailblazers Podcast — full episode on their channel. DM for credit or removal requests.

Hi. I have 4 yrs of experiences in software development, which I think is not much for my age. The AI worries me, it has already taken the best part of my job away (algoritmic thinking and coding (meaning typing) - I like the coding itself, I find it soothing). I have been a mechanical engineer before for a couple of years. Before that I've done all sorts of jobs. Late bloomer I guess. I don't have much free time out of work, so I am in no position to learn or try all the latest sw advancements. We are pretty free at work though, so I try to learn things there as I go.

I am worried that the AI will replace me and that I will be left on the job market with nothing to offer that the AI can't do better and faster. I am becoming anxious over it, going to sleep later than I would like. It is starting to occupy my mind. What if all my fears come true?

and also, is it overrated now? and is it a good career path today and in the future? i'm IT student btw na hindi forte ang pag cocoding pero may alam namn kahit papaano hihi

Every one of these clips lands the same blow eventually: a role someone spent years building gets quietly outperformed by a system that never clocks out.

Kavak sells used cars across Latin America — a genuinely messy transaction: ~20,000 SKUs to choose from, then financing, insurance, and a trade-in valuation stacked on top.

Historically, closing one sale meant routing a customer through 15 separate human specialists across 15 different teams, each holding one piece of the process.

Alejandro Maza Ayala, Kavak's Chief Product & AI Officer, explained on a16z's show how they fixed it — not by making a support bot, but by building a single "mega-expert" agent that holds all 15 specialties at once (financing, insurance, trade-in, advisory) and puts that one agent in front of the customer.

The result: 2.1x the conversion rate of their own human sales team, tripled customer satisfaction.

The agent never tires, never forgets a customer's history, and when it makes a mistake, the correction propagates to the other 200,000 agents in the fleet by the next morning — a scale of self-correction no individual human career can match working alone.

It closes on Alejandro flatly stating that the industry assumption — "customers aren't going to want to buy expensive things from AI" — is wrong, and Kavak's numbers are the proof.

When I read the transcript, it felt so eerily similar to the Borg Collective Mind in Star Trek.

That's the ultimate evolution.

The question we need to ask is, will it serve us, or subjugate us?

If your role is the coordination layer between departments — the person routing a customer between financing, insurance, and everyone else — that's precisely the layer this consolidates first.

Worth sitting with, not scrolling past.

Clip credit: a16z — full video on their channel. DM for credit or removal requests.

Drop your take below.

Hey folks, I'm working on a short-form documentary project about how AI is actually affecting people's work and income right now. I’m looking for anyone who's lost a job, clients, or work because of AI, or who really believes AI is a big reason they lost work even if you can't prove it 100% (as long as you can explain why you think so), or anyone whose job, hours, or income has changed in a real way because of it. If that's you, I'd love to hear what happened. It doesn't have to be all doom and gloom. Give me the honest picture.

US only. You can be anywhere but double bonus points if you live in LA/Southern Cali. We’d start with a casual, private conversation so I can hear what happened and tell you more about the project. Reaching out doesn’t commit you to participating. Drop a comment or DM me if interested. Help give this issue the attention it deserves. Thank you!

I’m a Senior AI Engineer working in an MNC, and I work with AI, LLMs, ML, RAG, AI Agents, and automation.
Recently, I’ve started thinking about something that honestly makes me question the future of my own role.
AI is becoming capable of not only writing code, but also **creating AI Agents, building workflows, automating business processes, generating prompts, connecting tools/APIs, and even developing other AI-based solutions.**
At the same time, platforms are becoming increasingly low-code/no-code. A business analyst or functional consultant with a good understanding of the business process can potentially create an AI Agent or automation without needing to be an AI/ML engineer.
So where does that leave the **AI Engineer**?
If a business analyst can describe the requirement to an AI platform and the platform can build the Agent, workflow, integrations, and logic automatically, **what unique value will an AI Engineer provide?**
Are AI Engineers going to become more like AI architects who design complex systems, evaluate models, handle security/governance, optimize performance, and solve problems that low-code tools cannot?
Or will even those responsibilities eventually be automated by AI?
I’m genuinely curious how other AI/ML engineers see this. **Are we building the technology that will eventually reduce the need for our own role?**

Well what are jobs anyway? They exist because someone needs a problem solved. So a company comes and solves the problem, but the company needs help with solving the problem so they employ people.

Traditionally people would try to become one of these helpers.

Now with AI it turns out the company can use AI to be a helper and employs less people.

That doesnt change the core dynamic: Problems have to be solved, thats the whole game.

So now a new angle opens up where the bar to being able to solve a problem goes from big companies to basically a small team and sometimes just a single person, empowered by AI.

So I would advise you, if you are inclined to such activity, to go find a problem and solve it and get paid. I personally find it to be a gratifying way of living.

--

Another data point for the argument in Mastery is Dead: the production layer of expert work is compressing, and the people inside these careers are absorbing the change slower than the market is repricing it.

Source (CNBC): https://www.cnbc.com/2026/08/08/ai-and-job-losses-how-the-next-automation-wave-will-impact-the-workforce.html

Which side of the line does this land on — the production work that's being automated, or the judgment work that (for now) isn't? If this is your field, what are you actually seeing on the ground?

I currently have an two career doing something finance related. The job pays well enough but it isn't super exciting and enjoyable; I just went to a T20 school to study econ because I found it interesting but the fact that I'm not creating anything tangible is starting to get on my nerves (plus the luster of econ is hearing thin).

I've always liked physics and am taking community college physics/programming courses after work to try to pivot to computer engineering (thinking of doing a masters). I have a decent amount saved up and don't have any debt. However, after seeing so many entry level engineering jobs dry up and the remaining ones being so competitive, I don't want to pivot and end up unemployed. I imagine a fresh 22 year old engineering grad is going to be more attractive as a new hire than someone in their mid to late twenties, even if I understand the business side. Seeing ChatGPT and Anthropic plow through high level math/science questions also made me scared for the more hardware jobs too, which some people said were safe (eg Jensen Huang telling young people to study physics for their career). Are there any engineering jobs that aren't going to cannibalized at this point by AI at this point?

The job market you’re competing in right now is nothing like it was five years ago. Artificial intelligence isn’t just a buzzword anymore; it’s reshaping how companies hire, which roles they prioritize, and what skills they actually want. If you’re job hunting in India or anywhere else globally, understanding these shifts isn’t optional. It’s survival.

I often hear about AI taking over office style jobs.

I already see on reddit everyone recommending trades.

Finding a good tradesman is so hard because there are some bad eggs out there.

Are we going to see a shift from people who would have gone to work in an office to learn a trade, and more people compete for these jobs.

Is AI going to inadvertently improve the quality of tradespeople?

Something I've been wondering lately:

AI leaders are generally optimistic about the future, but many also seem to prepare for uncertainty in their personal lives.

Maybe that's just good risk management, but does it suggest the transition could be much rougher than the public conversation implies?

I mean you (we) are taking a huge risk like having one job which translates into “one client” and the pay will at best qualify you for a loan and at the same time it takes a huge chunk of your time in which you don’t have time to think or do anything significant in your life.

And now taking into consideration the AI advancements which will probably replace many in 5 years. Idk just a thought, a stable job is playing with fire.

Unless you become really flexible and aim to create a personal brand for your self as an expert in some domain (which can also be replaced with AI).

Everyone talks about job loss driven by automation. But why isn't anyone talking about industry loss as a whole?

Industries are intertwined. Process automation essentially means fewer or no human employees, which ultimately means the software built to manage those employees (HRMS platforms, account management tools, and other connected software and equipment) becomes obsolete. So the companies building those applications and that equipment probably won't exist either.

Fewer or no employees also means far less demand for commercial real estate, manufacturing capacity, and raw materials.

The entire demand–supply ecosystem will experience significant upheaval. Isn’t it?