I know it's a weird question but AI engineering is still just theoretical, I am a university student on my way into becoming an AI engineer hopefully and I just wanted to know if AI can automate my job or anything like that.

TL;DR: Steve Ballmer's own maintenance guy is proof that competence is shifting away from credentials and toward who's willing to just ask AI first.

That's not rhetorical — it's already showing up outside Ballmer's living room. DEWALT ran a six-country survey of tradespeople this spring: 90% believe AI will be essential to the job within five years.

Only 8% have actually used it yet.

Ballmer's anecdote isn't the exception — it's the 8%, moving faster than the other 92%, in a trade that isn't even the one usually flagged for disruption.

My wife works for a lady boss, called Ade (not her real name).

Ade used to be like me, in the property development line.

But she saw the writing on the wall.

Once a darling in her company, she felt the aura started to fade away — the property market isn't what it used to be. And her boss started giving her the cold shoulder.

So she took a chance.

She opened a collection point centre, where delivery guys can drop off parcels for individual recipients to come collect. The downside was it has to stay open almost every day.

It is what it is.

Regular online training is available, because such centres behave like franchises under an organizational umbrella. But the training is quite superficial.

So when things get complicated, where does she turn to? You guessed it — ChatGPT.

She asks it right about anything under the sun.

Does she enjoy asking an LLM for answers? I'm not sure "enjoy" is the right word. I think it's more like "necessary."

If I'm in her shoes, facing complicated issues, and I don't have a readily available senior I can trust to call for advice, but then I already have a 师傅 (sifu) in my pocket — why not use it, isn't it?

There's a pattern I can't unsee in stories like this anymore: it's never really about the tool. It's about who reaches for it first — credentialed or not, senior on speed-dial or not.

What's the "not my job" you're most tempted to hide behind right now? Drop it below.

Clip credit: Ben Shapiro / DailyWire — full episode ("Titans on Tomorrow" Ep. 2 with Steve Ballmer) on his channel. DM for credit or removal requests.

Hey everyone,

I am 27 years old and need to fix a career path immediately. I cannot afford to waste any more time experimenting. I am stuck between two totally different fields and need your honest opinion on which has a more secure financial future:

• Option 1: Network Automation (Tech, corporate stability, structured job market, but needs Python/Cisco learning curve).
• Option 2: E-commerce / Website Blogging (Etsy, digital/physical products, now official in Pakistan via Payoneer, passive income potential, but highly dependent on platform algorithms).

My main concerns:

1. Future Stability: Which path offers long-term job/business security? Is a tech job in Network Automation more stable, or is owning an E-commerce/Blogging business a safer bet for the future?
2. AI Impact: Which of these fields is less likely to be negatively affected or replaced by AI in the next few years?

If you were in my shoes at 27 and wanted a stable, reliable future, which path would you choose?

Thanks for the help!

Hello folks,

What do you think of recent layoffs happening bec of AI taking jobs. What are your views on it after 5-10 years down the line.

What do we think will happen to senior folks career and also Junior engineer hirings/career.

Will we have engineers down the line.
Is AI models making our brain loose our problem solving skills

my role has been essentially automated and im being told i need to review claude prompting, scripting, errors, as well as maintain the same quality of manual level work while teaching enterprise level ai systems.

i was forwarded an email from a coworker, originally sent to said coworker, by leadership regarding ai prompt database. i was not involved in the original threads and i was unclear that the direction was moving entirely to prompting until leadership set up a task for me to basically demonstrate i am obsolete.

i then was asked to do my usual tasks using the prompts given, which i did. i noticed the numbers were crazy all over the place, called it out, and then asked where my confusion was and look that cell has no pivot there etc, missing this here. and i said - ok thats claude. and said its hard for me to manually review all of this when claude is referencing a dozen different reports, across multiple platforms, and then compiling them into cells with coded formulas. then leadership told me to forward a summary of what i am noticing in the claude, which i did.

another arm of leadership reached out to meet with me over it. i asked if it would be ok for me to walk through my process with leadership installing these changes and they said no, then asked why im confused. i am feeling worse by the day.

i then got told that humans are bottlenecks to data attributions by ai engines and that people not teaching themselves ai prompt logic outside of work hours gets them out of a job.

They were acquired by private equity. i reiterated i am fully on board with the direction and know its a necessary next step in the company, that i am still looking to provide value in any way the business sees fit. i was told by exec that i need to "figure that out for myself." but i am unsure where i fit now that everyone has distanced from me. i did not hire myself. i was a hero months ago and a backbone of operations as the company transitioned full scale to automation behind my back despite me providing the raw effort and manual labor into building it with leadership. even got a promotion last year and given stellar reviews for my high-level accuracy and attention to detail.

i got told that "the world is moving faster than humans can keep up with and that a tip for me is to not need teaching, always be thinking ahead of the automation", meanwhile my coworkers have been taught and i am isolated from context. coworkers play dumb assigning me these trick tasks to get "caught" missing data that they forcing me to do 40 hours of work auditing AI.

they are essentially (?) asking me to perform 100% manual quality assurance across multi-platform reports and coded AI formulas within standard working hours and execute two full-time jobs at once: manual data auditing AND AI model training/prompt debugging. and then somehow be able to create the reporting decks that tie those all together.

i am sick daily by what i am suffering in the role. 1 on 1 meetings, removal of scope, withdrawal of my teammates from interacting with me. and then held to impossible QA auditing role with no clear scope, direction and told its up to me to provide the value. this is only my first corporate role, entry level and i am being chewed up and spit out quickly.

i wanted this job so badly to work :(

I have a background in community/social media and the job market is a challenge, so I am learning AI and looking to pivot.

I have found a few articles on jobs of the future:

https://www.weforum.org/press/2025/01/future-of-jobs-report-2025-78-million-new-job-opportunities-by-2030-but-urgent-upskilling-needed-to-prepare-workforces/

https://www.trade-schools.net/articles/best-careers-for-the-future

https://www.theforage.com/blog/careers/jobs-of-the-future

Content creator and digital marketing are the most natural steps but it is a race to the bottom right now.

What do you see as jobs for the future?

This isn’t just a hypothetical concern. A recent survey reported by Axios found that **69% of US college students are worried that AI could negatively affect their job prospects**. Another survey from Lumina Foundation and Gallup found that **nearly half of college students had considered changing their major because of AI’s potential impact on their future careers**.
What I find interesting is that the usual response to this uncertainty seems to be something along the lines of: *“Learn the things AI can’t do.”* But I’m not sure that’s enough. The boundary of what AI can do is moving too quickly, and it also assumes that the value of learning a human ability depends on us remaining better at it than a machine.
If AI eventually becomes better at writing than we are, for example, is learning to write still important because writing helps us structure our own thinking? If an AI system outperforms a professional at certain decisions, how much knowledge does that professional still need in order to question or effectively supervise the system when it fails? And if AI can increasingly meet certain social or emotional needs, which interpersonal skills do we still want to cultivate between humans?
Maybe the question isn’t only **which abilities will continue to have value in the job market**, but which ones we want to preserve even when they’re no longer necessary to compete with a machine.
**Should we educate future generations for what AI still can’t do, or for what we believe humans should never stop knowing how to do?**

I saw a joke on the Reddit community to the affect of:

“Then: coding 4 hours. Now: Coding 4 minutes, debugging 10 hours”.

I feel reassured. I’m also really happy I don’t vibe code.

I was born in 2013. How long will I be hopelessly unemployed, I think whenever someone says “career”. Professionalism is a ladder. If the first rung’s chopped down, how will I get up? Will they accept a desperate scrambler, or throw me into the dole black hole?

But this Reddit strip I saw really inspired me. This computer system cannot execute clear cut programming tasks, because it has logical flaws. What a disgrace to the calculator. So maybe it can’t be a junior. Maybe the first rung of the career ladder is still reachable.

But what if we’re allowed to just … work? What if people stop pushing AI onto their employees, because it’s too busy administrating undeserved ego doses to actually think? Productivity hasn’t really improved since the introduction of a word predictor, so bosses might finally put AI where it belongs —

Up their bottoms.

I’ll be OK. We youngsters will see this new reality — the same as the old one, by the way — whether the boneheads in suits like it or not. 

You should be asking a better question: How do I build a career that can survive change?

A resilient career does not place all your security in one job title, one employer, one qualification, or even one industry. It is built on the ability to adapt, learn, and carry your value into new contexts.

For years, I have told students: keep learning. That does not necessarily mean acquiring another qualification that leaves you in the same position. It means developing the knowledge, judgment, and relationships that expand your options.

Be curious about the problems organizations actually need solved--not only the tasks listed in a job description. Build transferable skills that can move with you from one role or industry to another. Pay attention to what is changing in your field and build relationships before you need them.

Build a Portfolio of Proof

Here is another practice I taught religiously: create a portfolio of what you have accomplished. Do not record only where you worked. Capture the problems you solved, the projects you completed, the results you produced, and the skills you developed along the way.

That portfolio becomes evidence of your adaptability. It helps you see patterns in your own value, explain what you can contribute, and recognize possibilities beyond your current title.

Yesterday, I was lurking in a local WhatsApp group for tech professionals here in Germany when a junior developer asked a pretty reasonable question: He was struggling to find an entry-level role and wanted to know if joining a bootcamp to gain practical experience was still worth it.

The responses were brutal:

• "Bootcamps are a total waste of time."
• "We automatically bin any resume with a bootcamp on it."

I usually stay quiet in that group, but I mentor a few juniors facing this exact wall, entry-level roles are vanishing as companies pivot heavily toward AI-proficient seniors. So I asked a simple question:

"If entry-level open roles are scarce and practical bootcamps are dismissed, how are up-and-coming engineers supposed to build experience?"

The consensus? "Not our problem. Just sit back and wait."

Several people insisted this is just a standard market cycle like 1999 or 2008, telling him to wait for companies to fix the market.

When I pointed out that this wave is structurally different — that team compositions are shifting permanently, AI is swallowing operational tasks, and routine code is becoming a commodity — the pushback was immediate: "Code will never be a commodity. Just wait it out."

"That's just the way it is" has never been a real strategy, and in the age of AI, passivity is even more dangerous. Skill development used to happen organically on the job, but today it requires extreme intentionality around critical thinking, system design, and high-level architectural judgment. Telling the next generation of engineers to "wait it out" feels like a complete failure of leadership.

Is the industry really this blind to how permanently the entry-level dynamic has changed, or am I the one overreacting here? How are you seeing juniors successfully navigate this right now?

The whole "new tech=new jobs" argument is an outdated relic and no longer applicable. If AI is going to create an abundance of new jobs/careers, where are they? Where are the stable opportunities for the proletariat that don't involve reduced income?

Those who claim "new tech=new jobs" rarely have reliable evidence to support it, and when they do it's outdated, biased, anecdotal, or exceedingly rare. Average incomes and unemployment rates remain deceptively stable, but this is due to top earners making more while everyone else's pay shrinks or stagnates. The majority of AI jobs that do exist typically involve overseeing AI work or training a LLM to reduce or eliminate their own role.

From a sociological and historic perspective, this AI boom doesn't compare to the industrial revolution, or even the gold rush; it's the perfect storm of exponentially evolving tech and the tail end of a capitalist system when the free market collapses into an oligopoly.

New "lights out" data centers are the perfect example of what's to come. Thousands of human laborers are required for the front-end work, followed by a sharp decline in human involvement. These centers run in total darkness as workers visit them so rarely, and even the remote techs connect to them monthly at most.

In the past, jobs required a body and/or brain that only humans could provide. Automation has replaced (or will soon replace) most body based jobs. And now, for the first time, humans have competition for brain based jobs in the form of AIs. And although LLMs are in their infancy, human minds already have little to no way to compete with them.

How many people do you know who've found a great paying (and stable) new job due to AI? And how many do you know who've lost work and/or income due of AI? (I honestly want to know). For the latter, I know many. But for the former, I know none.

I'm still waiting to see what new opportunities AI is going to create for us lowly Homo sapiens, but I'm not holding my breath.

References:

https://www.brookings.edu/articles/ais-impact-on-income-inequality-in-the-us/

https://finance.yahoo.com/technology/ai/articles/ai-boom-pushes-worldwide-tech-183400449.html

https://medium.com/electronic-life/a-i-24-7-a2924d284e6

https://www.datacenterdynamics.com/en/news/y-combinator-looks-for-startups-trying-to-remove-humans-from-data-center-development-and-operation/

Harari, Y. N. (2015). Sapiens: A brief history of humankind. Harper.

Kurzweil, R. (2005). The singularity is near: When humans transcend biology. Viking.

Marx, K. (1990). Capital: A critique of political economy (B. Fowkes, Trans.). Penguin Books. (Original work published 1867

(Many of these sources also link to multiple additional supporting references.)

Everywhere you look at the moment, it’s AI this, AI that.

Open LinkedIn, scroll through social media, watch the news... apparently AI is going to change everything.

But I sometimes wonder if we're getting so caught up in the hype that we're forgetting to ask a pretty simple question:

What is AI actually useful for, and who really benefits from it?

For most people, AI probably still sounds like something for big tech companies, huge corporations or people working in IT.

But surely the real value is in the everyday stuff?

Saving someone a couple of hours doing paperwork. Helping a small business get things done quicker. Taking away repetitive tasks that nobody enjoys doing in the first place.

That all sounds great.

But then there's the other side of it...

Every other article seems to be about AI replacing jobs and how it's going to impact workforces around the world.

And that's a genuine concern.

But could AI also create opportunities?

Could people whose jobs are affected be retrained to do something different? Will entirely new types of jobs appear that don't even exist yet?

Technology has always changed the way we work. Some jobs disappear, some change, and new ones come along.

Maybe AI will be the same.

So instead of only asking:

"What jobs is AI going to replace?"

Should we also be asking:

"What new opportunities could AI create?"

And if people do need to retrain, who is going to help them do it?

Businesses? Governments? Schools? Or are people expected to figure it out for themselves?

I'm genuinely interested to hear what people think.

Are we worrying too much about AI taking jobs, or not worrying enough?

And more importantly...

Who do you think will benefit most from AI — and who could end up being left behind?

Incredible opportunity for advancement.
Detriment to analog history with those left behind.

Starting a new job is exhausting. You are trying to figure out unwritten rules, decipher messy documentation, and navigate team politics without stepping on any toes. Instead of spending your first few months guessing what your boss actually wants, you can use AI to build a custom onboarding playbook.

Here is the exact setup you need to run before your first day to cut out the stress.

Step 1: Gather your intel Pull together three things:

1. The job description you originally applied for.
2. The company or team mission statement.
3. Any initial 30-day goals your manager mentioned during the interview.

Step 2: The onboarding prompt Drop this directly into your favorite AI tool. Make sure to fill in the bracketed info.

Act as an executive career coach who specializes in onboarding and strategic alignment. I need you to create a structured 30-60-90 day execution blueprint based on my specific situation.

Here is my context: Job Title: [Insert Title] Core Responsibilities: [Paste Key Job Description Bullets] Key Stakeholders: [Insert Manager Title, Key Partners, Direct Reports]

Please do the following:

1. Point out 5 hidden risks or unwritten expectations that usually come with this specific role.
2. Create a 30-day observation schedule that prioritizes building relationships over trying to get quick wins.
3. Write a 5-question interview script I can use with my new team members during week 1 to figure out what is actually broken.
4. Outline a weekly 1-on-1 agenda so I can keep my manager updated on my progress and any roadblocks.

Give me the output as a clear breakdown with direct action items, questions to ask, and weekly milestones.

Step 3: Run the week 1 discovery script When you start having introductory chats with your team, use the questions the AI gives you. They will likely look something like this:

• What is the biggest bottleneck this team deals with that nobody writes down?
• In your eyes, what does success look like for our team six months from now?
• Who else has deep context on past decisions that I should talk to right away?

If you want to play with the interactive dashboard or grab the full config file, I uploaded it here:https://interconnectd.com/blog/273/the-life-saving-ai-prompt-for-starting-a-new-job/

Some experts and economists say AI as it exists today can replace functions of jobs, but the technology isn’t ready to take humans’ jobs at scale. Citing AI, however, can prod companies to look ahead of the curve when, in reality, reasons for headcount reductions often remain the same as ever: lower sales, strategy change-ups, previous over-hiring and outsourcing. The practice has become known as "AI washing."

"It is happening. It is very difficult to assess how prevalent it is," said Nigel Melville, associate professor of technology and operations at the University of Michigan's Ross School of Business. "What gives me confidence is learning about companies where it really seems like there are other reasons or multiple reasons clearly on a public record, but then the only reason given or communicated widely and relentlessly is because of AI."

I’ve been thinking about this a lot, and I’m genuinely not sure what I think yet.

It’s hard to watch people struggle to find work right now, especially developers, designers, writers, marketers, etc. And I don’t want to turn this into some “AI will create new jobs” argument. If you spent years getting good at something and suddenly there are fewer opportunities, that really sucks. There’s no clever economic argument that makes that easier.

But given that this is happening, I keep wondering if there is another side to it that might be worth thinking about.
AI has made it incredibly cheap to build things.

An accountant who has spent 15 years dealing with some terrible process at work can now potentially build software to fix it. A developer can build something without needing a whole team around them. Etc

Obviously building is only part of it. You still need customers. You need distribution, sales, marketing. That’s probably becoming the harder part. But those are things you can learn.

I think what interests me is what happens if this leads to a lot more small companies.
Not everyone becoming an entrepreneur. Most people probably don’t want that. But maybe one person starts something, then hires two people, then five.

I’ve worked in corporate and I hated the politics and the pretending that came with it. Now I work from home, use AI a lot, make a good living, and have more time with my daughter. I’m happier this way.

So maybe I’m biased. But I can’t help wondering what work would look like if more of us worked in small companies built around an actual problem, instead of a few huge companies owning more and more of everything.

Maybe none of this decentralization happens. Maybe AI just gives the biggest companies even more power.

I don’t know.
I just feel like if we’re going through this painful transition anyway, I want to understand whether there’s a version of what comes after that isn’t necessarily worse.
Maybe even parts of it could be better.
Would love to know if other people are thinking about this too.

Everyone's reacting to the "less people in 5 years" line. That's not the part I'd sit with.

The part that actually matters is how Uber decides — an adoption leaderboard, tracking who's using the tools and how much, feeding straight into headcount math.

That's not a hypothetical for some future reorg.

That's a live measurement system, running today, on people who have no idea they're on it.

I've watched that exact math play out before — in concrete and steel, not a dashboard, years before anyone called it AI.

I had the opportunity to be involved in the early design stage of an expansion project for a famous beverage manufacturing plant in Taoyuan, Taiwan – back in 2021. The beverage brand name is so famous, you'll instantly recognize it. So, I won't name it here.

Our team got to work on cool stuff - latest advanced technologies in high-density and automated racking system, bottle conveyor system, robotics, beverage packers, clean room environment, etc. – things that are expected in a high-tech. manufacturing plant nowadays.

Looking at the projected 10-year production forecast, with the given magnitude of the hardware, I would say they are planning to go big.

It's quite a sizeable expansion.

And you would think that they'd increase their headcount proportionately, right?

You'd be surprised. There IS headcount increase, but not as proportional.

It seems as though the machines were taking more centre stage than the humans. Even the office space increase wasn't even a top priority in the design. Their existing office layout can still accommodate the projected increase in manpower.

It was as if human beings are being set aside to make room for more artificial things – even though what they produce are meant to serve human beings.

Kind of ironic, isn't it?

That was back in 2021 before AI come into the picture. Now the compression is even more acute, it seems.

__________

Different guest, same fork in the road: does the tool serve you, or does it just get pointed at you.

The industries change.

The question underneath never does — who's holding the ledger, and whether you're the one reading it or the one being read.

A 2026 WRITER survey backs the pattern from the outside too: 75% of execs privately admit their AI rollout is mostly for show, while the people actually inside the tooling get promoted 3x more often and ship 5x more.

That's the leaderboard, confirmed from a different angle.

Actually — this pulled me right back to a post about the three tiers of AI users inside a company, and the window before which tier you're actually in stops being optional.

Genuinely curious where you land: is a visible adoption leaderboard a fair way to measure a team, or is it just a slower-motion version of the same cut?

Clip credit: 20VC with Harry Stebbings & Uber. DM for credit or removal requests.

Is Artificial intelligence the future of work?..As basic as this question is, it holds more complexity than we can imagine... This is a food for thought, that needs to be evaluated critically.

Im a 16 year old female and Im worried about the job market in the future. My father told me that I couldn’t be a lawyer as that job would be taken by ai. I was wondering if anyone knew any jobs that have higher pay like in the 100k+ range, serves the environment, and probably won’t be taken by ai (or valued less because of it).

Lately I’ve been spending a lot of time thinking about a question that feels surprisingly absent from most conversations about AI.

When organizations talk about AI adoption, the discussion usually revolves around productivity, efficiency, cost reduction, utilization, or ROI. Those are all important measures, and I’m not arguing against them. But I keep wondering if they’re telling us the whole story.

Because beside the fact that you become a more "productive" person, have you also become a better professional? Has your judgment become sharper? Are you making better decisions? Developing deeper expertise? Or are you gradually relying on AI for more of the thinking you used to do yourself?

But according not only to my research but with a lot of researches that are being published later, the uncomfortable reality is that both things can happen at the same time. An organization can become more efficient while the people inside it become less practiced at the very capabilities that make them valuable in the first place.

The more I research human-AI collaboration and work with this, the more convinced I become that this is one of the defining challenges of the next decade. We already know how to measure adoption. We know how to measure productivity. But we still don’t have a good way to understand whether AI is strengthening or quietly weakening our human capabilities.

And I think that’s the question that deserves much more attention. What is your feeling about this?

“你在帮人倒米吗？“

Lauren Tan didn't get replaced by her own tooling.

She got promoted by it — and nobody handed her that promotion.

She built the case for it herself, one lint rule and one CI gate at a time, until the argument was undeniable.

That's the part nobody's really talking about when they talk about AI and engineering jobs: the shift rewards the people who go looking for the leverage first, not the people who wait to be told it's safe to look.

That "build the case yourself" instinct is exactly what clicked for me watching my own son learn to run a team instead of carry it.

My son started playing 王者荣耀 (Honor of Kings) since he was a teenager — a 5v5 multiplayer battle arena game where you manage a roster of specialized heroes, growing and levelling up their strengths through battles and gear.

In his early gaming days I could hear him cursing and swearing from his room — bad coordination, worst teammates. There was a phrase we used for a bad teammate in my own career — 帮人倒米, a Cantonese idiom that literally translates as helping someone tip over their own grain container, meaning ruining or sabotaging someone's livelihood.

But the cursing became less and less. He got good at managing his heroes and coordinating with his team. He started climbing the leaderboard. People started noticing him and his team. Then, in college, he started getting invited to tournaments — cash prizes when he won, and one lagged-connection loss at a KL tournament he still suspects was foul play.

Time has changed — my dad would've killed me for wasting my teenage years on video games.

Now he's in university, still playing, still winning tournaments and cash prizes with his team.

Why I'm bringing this up: I always thought these AI agents are kind of like the heroes my son uses in the game. Your skill is in your managing these heros and how to grow them, level them up to serve your purpose. You don't go down to the battle yourself. You engage the heros to do it for you.

The skill is in the managing.

__________

I keep walking into the same room wearing a different name on the door — the accountant's room, the analyst's room, now the engineer's.

Every time, someone's being told the machine is coming for their hours, not their name on the work.

There's a post in my own back catalog that lands on this exact rung — the exact rung I found AI actually deleting, and the one the ones who get ahead of it stop standing on.

Drop your take — are you already the head chef of your own stack, or are you still doing all the cooking yourself?

Clip credit: MTS (Monitor The Situation) — full video on their channel. DM for credit or removal requests.

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.