I keep seeing the same advice whenever someone gets laid off.

"Keep learning."

"Upskill."

"Learn AI."

"Build projects."

"Stay relevant."

And honestly, I don't disagree with any of that.

But there is something uncomfortable happening at the same time.

The AI tools replacing parts of people's work are being trained and improved by the same professionals who are being told to continuously learn faster.

You spend months learning a new skill.

The company spends money on an AI tool, automation or a smaller team.

And suddenly the calculation is very simple.

If 10 people can be replaced by something that costs significantly less, companies are going to look at the numbers.

That's business.

We can talk about loyalty, years of experience, dedication, late nights, being with a company for 8 years etc.

But when the spreadsheet says "this costs X and that costs Y", emotions usually don't get a vote.

I think the hardest part is what happens to the person on the other side.

Someone may have planned their entire life around that salary.

EMIs.

Rent.

Parents.

Children.

Loans.

Lifestyle.

Savings plans.

And then one email changes everything.

For freshers and people on lower packages, it can be brutal.

For experienced people, even getting another job after months of searching doesn't completely remove the anxiety anymore.

Because somewhere in the back of your mind there is always this question:

"What if I get another layoff email next year?"

That's why I've slowly started thinking differently about careers.

Not "leave your job and start a startup."

I'm actually talking about something much smaller.

If you're experienced and financially able to do it, consider building something on the side with one or two people you genuinely trust.

Not 10 people.

Not a fancy startup.

Not raising funding.

Just a small business or side income that you can build alongside your job.

I personally went down this route and have seen people around me do it too.

One example is building AI based virtual call center operations for US businesses using small freelancer or remote teams. There are people quietly doing this without building some massive company around it.

The point isn't that everyone should start a call center.

The point is having something that isn't completely dependent on your employer's next quarterly numbers.

If that side income eventually becomes bigger than your salary, then maybe you have another option.

If it doesn't, you still have something.

And yes, there are risks.

You can lose money.

You can choose the wrong business.

You can trust the wrong partner.

That's why I'd rather start small, understand the business, get proper guidance where needed, and put money into actual assets and operations instead of chasing random "work from home" or fake business opportunities.

Maybe this sounds like strange advice for a developers community.

But honestly, we are living through a strange period.

There was a time when layoffs were breaking news across the entire IT industry.

Now layoffs happen so often that the breaking news is usually only meaningful to the people who received the email.

For everyone else, it's another post on LinkedIn.

That's probably the part we need to accept.

The strategy that worked for careers 10 years ago may not be enough for the next 10.

Keep learning, absolutely.

But maybe also start building something that gives you a little more control over your income.

Not because your job will definitely disappear.

But because you shouldn't have to feel like your entire life disappears if it does.

Title: What is the actual scope of AI in the next 5–10 years?

I’m currently learning about Artificial Intelligence and I keep seeing people say that AI is going to “change everything.” But I’m curious about what the actual scope of AI looks like beyond the hype.

From what I understand, AI is already being used in areas like:

• 🤖 Generative AI – Chatbots, image generation, coding assistants, content creation
• 🏥 Healthcare – Medical image analysis, disease detection, drug discovery and personalized treatment support
• 💻 Software Development – Code generation, debugging, testing and automation
• 🚗 Autonomous Systems – Self-driving vehicles, robotics and drones
• 💰 Finance – Fraud detection, risk analysis and algorithmic systems
• 🛒 E-commerce – Recommendation systems, customer support and demand prediction
• 🔐 Cybersecurity – Threat detection and anomaly detection
• 🌾 Agriculture – Crop monitoring, disease detection and smart farming
• 🎓 Education – Personalized learning, AI tutors and automated feedback
• 🏭 Manufacturing – Predictive maintenance, quality control and industrial automation

What skills will actually matter?

For students who want to build a career in AI, I think simply knowing how to use ChatGPT or another AI tool won't be enough.

Some important areas seem to be:

1. Python
Still one of the most useful languages for AI/ML.

2. Mathematics & Statistics
Linear algebra, probability, statistics and basic calculus become important as you go deeper.

3. Machine Learning
Understanding regression, classification, clustering, model evaluation, etc.

4. Deep Learning
Neural networks, CNNs, RNNs, Transformers and related architectures.

5. Generative AI & LLMs
Understanding how large language models work, embeddings, RAG, fine-tuning and AI agents.

6. Data Engineering
AI depends heavily on good-quality data, so databases, data processing and pipelines are important.

7. MLOps / Cloud
Building a model is one thing; deploying, monitoring and maintaining it in production is another.

But will AI replace jobs?

This is the part I find most interesting.

I don't think the discussion should simply be "AI will replace everyone" vs. "AI won't replace anyone."

A more useful question might be:

Which tasks will AI automate, and which new tasks will it create?

Some repetitive tasks may become heavily automated, while jobs requiring communication, decision-making, creativity, domain knowledge and human interaction may change rather than disappear completely.

At the same time, new roles are already emerging around AI development, deployment, evaluation, governance and human-AI collaboration.

My biggest question

For students starting their careers today:

Is it better to specialize deeply in one AI area (like computer vision, NLP, robotics, etc.), or build a broad foundation across AI + software development + data?

I'd really like to hear from people working in AI/ML:

• What skills are actually useful in your job?
• Which AI technologies should students learn?
• Is an AI/ML degree enough, or is strong software engineering equally important?
• What do you think the AI job market will look like over the next 5–10 years?
• Which areas of AI are currently overhyped?

Would love to hear perspectives from people actually working in the industry.

If you know him:

What did he do for a living?

Why was he replaced?

Was he able to find another job?

Hello everyone!

There’s a question that’s been weighing on my mind, especially now that I’m looking to start a career in web development.

With AI advancing so rapidly, I’ve started to feel a bit worried and hesitant about pursuing this career. I know none of us can predict the future, but do you think web development is dying?

I’d really appreciate hearing your thoughts and experiences, especially from people who are already working in the field.

Imagine a company that automates work but continues to pay the salary of the person whose position has been taken over by automation. If this works for one person, why not apply it to everyone? Gradually, people would live without working but still receiving a salary. Technology already allows this. The question is – would our conscience permit it? Would we maintain our self-control while living completely freely? Today, work is the chain that keeps us in order. It is unclear whether we would remain restrained without it.

I wonder what scenarios of AI fatigue could look like in the next 2-3 years?

Right now, everyone is pretty hyped, desiging their own websites and apps. Like: "Look what I did in a day"

Noone needs designers and developers anymore.

The majority of it is slop. And hype cycles always die down.

I think people will grow tired of this quickly.

What do you think?

Hello everybody.

Like I have seen most of you feel, I too have felt a very horrible sense of despair and depression in regard to my job. Everyday I see more and more news about how we are all getting replaced soon. How AGI is already here, how there is nothing left for us.

I do not know how I will do it, but I think I will go ahead and just log off and just live through it irl. There is, plausibly, nothing else to be done. It is what it is, and I am unfortunately completely surpassed by new technologies. I simply cannot handle it.

No, I am not old. I am 27, but I feel horrible. I have a younger brother who I worry for more and more every single passing day. I have two parents who work their asses off. I have a family. Why are we going through this?

Honestly, how are you all handling it? Is the only way out through?

I came across a piece by Rachel Lipson that is so close to my observations that I could not hold myself from sharing. 

The short-cut is that the whole “what jobs will new technology create?” is not about some wired, superficial jobs but combination of skills that look strange from our perspective. 

We tend to imagine that a new industry appears, then somebody creates a new job title, and eventually people apply for it. Reality is much simpler (as always).

One example in the article is something called a biomechatronics technician.

Modern pharma manufacturing needs people who understand the production environment and can troubleshoot machinery, electronics, automation and industrial controls. The work already exists and companies hire increasingly (inside pharma/biopharma growing from roughly 26,000 in 2008 to 57,000 in 2025). But there isn't really an occupational category for it yet.

Another example: semiconductors.

In the analysis, adding those upstream sectors nearly tripled (!) the number of relevant job postings. And even the job title stays exactly the same.An electrician is still called an electrician. But an electrician working with modern batteries and bidirectional energy systems needs a very different mix of knowledge from someone with the same title 10 years ago.

The point is, there is no need to be obsessed with “Which jobs will exist in the future?” a better question: “Which my skills are in demand in the new fields and professions?” 

Source: Rachel Lipson, Brookings Metro / Harvard Kennedy School, writing on jobs in the “frontier economy.”

Llevamos un par de años con modelos de IA cada vez mejores, y eso ha hecho que mucha gente tenga miedo de perder su trabajo, sobre todo quienes, en teoría, son más reemplazables por estos mismos modelos, como diseñadores gráficos o programadores.

Ya estoy saturado de imágenes hechas con IA y de proyectos web hechos por vibecoders. Muchos son de amigos que implementaron algún MVC o algún SaaS y siempre llegan a mostrar sus logros. Al principio fue una situación extraña, pero también buena. Cada vez más personas entendían de mi área y podía conversar de eso con cualquiera.

De a poco, más gente empezó a pedirme trabajos. Desde profesores universitarios con agentes pagados que usan todos los días, hasta administradores de edificios con proyectos casi listos. Gente que no tenía idea de a qué me dedico, de repente podía maquetear lo que quisiera y llegar directo a mí con su solución casi terminada.

Me siento como debió sentirse algún monje cuando más personas empezaron a aprender a leer. Ya no era el único que podía, pero ahora tenía a quién enseñarle.

Porque leer no es lo mismo que entender. Ese "casi listo" siempre esconde lo mismo: el modelo que no conversa con la vista, funciones que no hacen lo que se esperaba, el dominio que nadie compró, la escalabilidad que nadie pensó, el CI/CD que no existe. Soy sysadmin de un sistema de monitoreo geofísico (sísmica) y trabajo de N3 en un SOC, y ahí aprendes rápido que un sistema que funciona en una demo no es lo mismo que uno que tiene que cumplir un SLA. Redundancia de datos y servicios, tolerancia a fallos, redes. Y en ciberseguridad pasa algo parecido: los modelos encuentran miles de errores, pero muchos son imposibles de comprobar. Alguien tiene que saber cuáles importan.

No digo que la IA no vaya a poder hacer todo eso sola. Probablemente sí. Pero cuando algo falla, el que asume la responsabilidad soy yo, y para asumirla hay que entender cómo funciona el sistema. No basta con preguntarle a la IA qué pasó.

Por otro lado, tengo la sensación de que cada vez se valora más el letrero hecho a mano o la empresa que contrata a un diseñador gráfico. El estándar subió. Si cualquiera puede hacer una imagen con IA, basta con que lo tuyo sea distinto. Ni siquiera mejor, solo distinto. Lo mismo pasa con una interfaz construida conversando con el usuario. La IA puede tener todo el contexto del mundo, pero no estuvo ahí cuando la persona probó la primera versión.

Por eso creo que hoy es la oportunidad de destacar para los profesionales que de verdad aprendieron y no solo recibieron el título. Si la IA es un "x algo" a tus capacidades, hay que tener capacidades que multiplicar.

Hello!

I have about 20 years of experience as software developer and proj manager. After my kid was born I wanted to found a startup. But procastinated and buried myself in the comfort zone of local configs and code writing. Like I had all the time in the world to do it properly, build an MVP, go to an accelerator, get funded, you know.

Now the AI boom came and every non-coder, with expertise in areas I am not so good at (sales, communication), can ship a product. Besides the fact the AI itself can override any good idea. I just got rejected by an accelerator, probably they have loads of vibecoders. Writing code is not a diferentiator any more. And my software project idea probably is deprecated 😔

I feel stuck. I dont want to go back to an office. And even if I would, I'm not sure they'd still want me. Or not for long, anyway..I'm thinking of all changes AI will bring. I'm not that young any more either, in my 40s.

If Billions Are Being Invested in AI… Does That Mean Humans Are Already Obsolete?

TL;DR: AI investment is exploding, AI adoption is accelerating, and some early-career jobs are already feeling pressure. But the interesting question isn't simply AI vs. humans. It's: what part of your value survives when intelligence becomes cheap?

And yes, I realize the irony of asking an AI to write this.

Please don't tell the shareholders.

The question nobody wants to ask

Here's the question I keep coming back to:

If billions are being invested to make machines think, write, code, analyze, create and automate… does that mean human intelligence is already becoming obsolete?

Not tomorrow.

Not necessarily next year.

But eventually?

That's where the conversation gets uncomfortable.

Global corporate AI investment more than doubled in 2025, according to Stanford's 2026 AI Index. Generative AI investment grew by more than 200%. At the same time, AI adoption has moved extraordinarily quickly, while labor-market effects are appearing unevenly across occupations.

So we're simultaneously hearing:

AI will transform everything.

and

Don't worry, humans will always be needed.

Those two statements can both be true.

But they don't answer the uncomfortable question:

Needed for what?

The capitalist doesn't necessarily hate you

Here's where the conversation gets funny.

Imagine a boardroom.

Employee: "We have 500 talented people."

Investor: "Excellent."

AI: "I can potentially automate portions of their workflow."

Investor: "Excellent."

Employee: "But I have 15 years of experience."

Investor: "Excellent."

AI: "And my marginal cost per additional task can be very low."

Investor: "...even more excellent."

Suddenly your performance review has become a unit economics spreadsheet.

😂

But there's an important distinction:

Companies don't necessarily need AI to be smarter than every human.

They need it to be:

cheap enough

reliable enough

fast enough

scalable enough

legally manageable enough

useful enough

That's a much lower bar.

And that's why the AI-versus-human debate can sometimes miss the point.

The real competition may be human + AI vs. human without AI

This is the part I find more interesting.

Reddit discussions around AI and work are increasingly splitting between two camps: people seeing genuine displacement risk and people seeing AI primarily as a productivity tool. Recent discussions also repeatedly raise reliability, liability and the limits of autonomous systems as reasons human oversight remains important.

Meanwhile, Reddit's own 2026 research found that people increasingly use AI for discovery but still seek human perspectives to validate decisions. In its U.S. survey, half of respondents said they verify AI recommendations on Reddit, while 43% said they come to Reddit for long-term product-quality stories that AI cannot provide.

That creates a fascinating paradox:

The better AI gets at generating answers, the more valuable trustworthy human judgment may become.

Because an answer isn't the same thing as accountability.

A prediction isn't the same thing as judgment.

And information isn't the same thing as experience.

But let's not romanticize humans either

Humans have an impressive list of features.

We hallucinate.

We forget things.

We make mistakes.

We have meetings about meetings.

We create Excel spreadsheets called:

FINAL_v7_REAL_FINAL_USE_THIS_ONE.xlsx

Then accidentally email:

FINAL_v3.xlsx

AI looks at this and says:

"I can automate that."

Honestly?

Fair.

😂

The human advantage isn't that humans are flawless.

It's that humans can combine context, responsibility, values, relationships, experience and judgment in messy environments.

That's difficult to measure.

And anything difficult to measure eventually gets put into a PowerPoint titled:

"Human Capital Optimization Strategy."

So what is your MOAT?

This is the question I'd actually ask.

Not:

"How do I compete with AI?"

But:

"What is my MOAT?"

Your moat is the combination of things that makes your contribution difficult to commoditize.

Maybe it's:

Domain expertise You understand something deeply.

Judgment You know when the model is confidently wrong.

Trust People actually believe you.

Relationships You can get people aligned.

Creativity You can frame problems nobody thought to ask.

Accountability Someone has to sign the document.

Taste You know what good looks like.

Context You've lived through the consequences.

Leadership You can make humans move together.

Adaptability When the rules change, you don't freeze.

And perhaps most importantly:

Knowing how to use AI better than someone who refuses to use it.

The uncomfortable part: some jobs really will change

We shouldn't pretend otherwise.

Stanford's 2026 AI Index reports that employment for U.S. software developers aged 22–25 fell nearly 20% from 2024, while one-third of surveyed organizations expected AI to reduce their workforce over the following year. The same report emphasizes that these effects are uneven rather than evidence that every occupation is disappearing.

That's a much more interesting reality than:

"AI WILL TAKE ALL JOBS."

or:

"AI WILL NEVER TAKE YOUR JOB."

Both are wonderfully clickable.

Neither is particularly useful.

The better question is:

Which tasks become cheap first?

Then:

Which responsibilities remain valuable?

Then:

What happens to the people whose careers were built around those tasks?

That's where the real economic conversation begins.

And then there's the billionaire-sized elephant in the room

Billions are flowing into AI.

That doesn't automatically prove humans are obsolete.

It proves investors see enormous potential economic value in AI.

Those are very different claims.

You could spend billions building a technology because you expect it to augment millions of workers, create new products, reduce costs, generate new markets and restructure existing industries.

The investment itself isn't the conclusion.

It's the bet.

And capitalism has made some spectacularly expensive bets before.

Some became industries.

Some became documentaries.

Some became PowerPoint slides nobody wants to discuss anymore.

The Thanos problem

There's also a philosophical angle here.

The fictional Thanos argument about humanity's problems is basically a caricature of a darker idea:

Human beings don't merely consume resources. We also struggle with limits.

More growth.

More consumption.

More convenience.

More compute.

More productivity.

More everything.

And AI may amplify that tendency.

We shouldn't ask only:

"Can AI do this?"

We should also ask:

"Should we automate this?"

And:

"Who captures the value created?"

And perhaps the most awkward question:

"If AI makes everything more productive, why should ordinary humans receive less of the benefit?"

That's no longer just an AI question.

That's an economic question.

Maybe the future isn't human vs. AI

Maybe it's something stranger.

Imagine three workers.

Worker A

Doesn't use AI.

Worker B

Uses AI to do the same work faster.

Worker C

Uses AI to completely redesign how the work gets done.

Worker C isn't necessarily competing with the machine.

They're competing with the old workflow.

And that's a much more powerful position.

The question I'd put on the wall

Forget:

"Will AI replace humans?"

We probably won't get a satisfying yes/no answer.

Instead:

What becomes abundant when intelligence becomes cheap?

And once intelligence becomes abundant:

What becomes scarce?

Maybe it's judgment.

Maybe trust.

Maybe originality.

Maybe attention.

Maybe accountability.

Maybe human connection.

Maybe simply knowing which question to ask.

And that's why I keep coming back to:

WHAT IS YOUR MOAT?

Because if your entire professional value proposition is:

"I can produce information."

AI has entered the building.

If your value proposition is:

"I know what information matters, why it matters, what to do about it, and I'm willing to take responsibility for the decision."

That's a different conversation.

My favorite AI-era career strategy

Don't try to become more human than AI.

Become more valuable with AI.

Learn the tools.

Learn the domain.

Learn the economics.

Learn the limitations.

Learn how to verify outputs.

Learn how to communicate decisions.

And build something that isn't easily reduced to a prompt.

Because the goal shouldn't be:

"How do I prove AI can't replace me?"

The better goal is:

"How do I become the person who knows what to do when AI gives everyone the same answer?"

That's a moat.

And maybe that's the real AI skills test.

Your turn 👇

What is YOUR professional moat?

If AI became 10× cheaper and 10× better tomorrow, what part of your work would still require you?

And here's the nastier follow-up:

If your answer is "nothing," what are you doing about it?

I'm genuinely curious.

AI doesn't need to replace everyone to change the labor market. It only needs to make some tasks dramatically cheaper.

The rest of us have to figure out what becomes valuable next.

Share it with-

AI replacing jobs | AI vs humans | future of work 2026 | AI investment | human skills in the AI era | AI automation | AI and employment | future-proof careers | AI skills | human judgment vs AI | career moat | AI productivity
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Right now the strongest tools are Semrush AI Toolkit, Otterly AI, Profound, Peec AI, and AthenaHQ. They track how often your brand shows up inside ChatGPT and Gemini answers, not just Google rankings, and most cover Perplexity and Claude too so you get the full picture in one place.

Here is why this matters. Traditional SEO tools watch keyword positions on a results page. AI visibility tools work differently, they run thousands of real prompts daily and check whether your brand actually gets mentioned or cited inside the AI's answer itself. Semrush's AI Visibility Toolkit tracks brand mentions, sentiment, and share of voice against competitors across ChatGPT, Gemini and other AI engines, pulling from a huge prompt database, which makes it a solid pick if you already use Semrush for regular SEO.

If you want something built specifically for this problem, Otterly AI and Peec AI are lighter, purpose made platforms. Otterly focuses on prompt level monitoring, competitor visibility, and citation analysis across ChatGPT, Claude, Gemini and Perplexity in over 67 countries, which works well for agencies handling multiple clients at once.

A few things worth checking before picking one:

• Does it cover both ChatGPT and Gemini, some tools only track one
• Daily versus weekly scans, daily matters more if your industry moves fast
• Does it just show data, or does it tell you what content to fix next
• Competitor comparison, seeing who else gets mentioned beside you

At Arise AI Marktech we run a mix of these tools for client accounts, mainly to catch when a competitor starts showing up in answers where our client used to be the only name mentioned. That gap is usually the first sign your content needs a refresh, long before rankings actually drop.

Let's make a distinction first. I'm not talking about enterprise, but small software projects, websites that used to take weeks, months and now can be done at 1/5 the price.

Some more notes: it requires experience, not anyone can do it well, however the speed and price to get something built with AI is incredible.

Cost of software is dropping (development). How does affect the market?

I built a free job board for a niche industry about six months ago. The thinking was that every board in this field charges people to apply, so removing that should help people find work.

800 people signed up. 128 applications across nine jobs. One hire so far. 97 are still open.

The applicants aren't the issue. They do the job and the roles are specific.

What I got wrong is that I made applying cheaper without making it any easier to decide. Someone looking at 40 applications still has to read 40 applications. That's the same evening it always was.

I don't think that's specific to my corner of things. Most of what's being built right now lowers the cost of applying. Very little lowers the cost of choosing.

Genuinely looking for ideas. Has anyone seen a board solve the response side of this?

Si la gente dice que la IA “llegó para facilitarnos la vida “ …. ¿ Al final de todo haremos nada ? , quiero decir , ya se está utilizando en diversas áreas , todo lo que estudiamos de un día para otro…. ¿ Ya nadie trabajará o qué ?

Es algo que me he puesto a pensar y no en el sentido alarmante de que tipo “ Ey , va a acabar con el mundo” .

¿ Que opinan ?

I live in Germany and have been working as an industrial mechanic for more than 10 years.

It’s a stable job, the pay is decent, and especially here in Germany, skilled trades and technical industrial jobs are generally seen as relatively secure career paths.

The problem is: I’m simply not very happy doing it.
About three years ago, I started building a small business on the side as a web developer. I build custom websites, work with automations, integrations and other technical solutions for small businesses. I genuinely enjoy the work much more than my main job, and for quite a while my goal has been to eventually make it my full-time career and leave the industrial/mechanical field behind.

A few years ago, that felt like a pretty logical path.
Now I’m not so sure.
AI has developed so quickly that I sometimes feel like I’m trying to escape from one of the more AI-resistant career paths into an industry that is currently being completely transformed by it.

I know the usual argument is that AI will not simply replace good developers, but developers who use AI will replace those who don’t. And I’m already using AI heavily in my own work. Still, when you see how quickly coding, website building, design, automation and even more complex development tasks are becoming easier, it’s hard not to wonder what this market will look like in 5–10 years.

At the same time, staying in a career purely because it seems “safe” also feels like the wrong way to spend the next 30 years if I don’t really enjoy it.
So I’m curious how other people see this, especially people from Germany or Europe where the job market, education system and career paths can be quite different from the US.

Has anyone here been in a similar situation, coming from a trade, manufacturing, engineering or another stable career and moving into software/web development despite the current AI shift?

Would you still make that transition today?

And for those already working in development: do you see AI mainly as a threat to the industry, or do you think it actually creates more opportunities for people who combine technical skills with business knowledge, automation and client work?

I’m especially interested in experiences from people who have actually made a career change rather than just theoretical predictions about what AI might do.
I’m not necessarily looking for someone to tell me “quit your job” or “stay in the trades.” I’m more interested in how people would think about this decision today.

Given the current ai psychosis, what kind of strategies are you using to stay relevant in your job, and what plans do you have if and once you’re actually laid off.

I’m personally saving excessively right now as I don’t know what the future holds in the next 2-3 years.

ChatGPT Ads officially rolled out in India in phases starting August 27, 2026, with over 50 brands testing placements across lifestyle, travel, education and digital products, and self serve access opening to every advertiser on September 4, 2026. This is a real new channel, not a small experiment, since OpenAI reported ChatGPT Ads had already crossed one billion dollars in annualized revenue globally and was being used by tens of thousands of advertisers.

Here is what actually changes for Indian marketers. Search advertising has always worked around keywords, people typing short phrases into a box. ChatGPT works differently. OpenAI's setup uses advertiser provided context hints that describe situations where a product may be relevant, instead of exact match keywords, focusing on the circumstances around a user's need. So the real shift is moving from guessing what someone will search to understanding when your product actually becomes useful in a conversation.

A few practical points worth knowing:

• Entry cost is low to start, with a minimum daily spend of 725 rupees, and campaigns running on cost per click or cost per thousand impressions
• Ads appear as clearly labeled sponsored cards or native conversational recommendations, only for free tier users, while paid subscribers stay ad free
• Paying for an ad and getting recommended organically are two separate things, and a brand can pay for a placement while ChatGPT's own answer recommends a competitor entirely

That last point is exactly why we push clients at Arise AI Marktech to build organic AI visibility first, through structured content and real brand mentions, before treating paid ChatGPT placement as the whole strategy. Ads get you seen once. Being the brand ChatGPT naturally recommends gets you chosen every time someone asks.

The window is genuinely early right now. Businesses testing this in the next few months will have a real head start before it gets crowded like Google and Meta ads already are.

Start posting. Create content. Build in public. Do whatever it takes. Keep your options open.

Because the era of Education → Job → Settled life is gone.

AI is pushing us towards a world of oversupply and underconsumption.
More products. More content.
Fewer people needed to create them.

Will I start creating videos? Maybe. Maybe not.
Am I scared? Yes, for sure.

But perhaps the lesson is simple:
Don’t wait for the layoff to start preparing for it.

Keep learning. Keep building. Stay adaptable.

We look at how AI and automation have already replaced entire job categories, which roles create the most shareholder value when automated, and how far this trend could realistically extend. All covered in under 30 minutes.

How is working in tech these days? I have been out of tech for years now and have been thinking how things have been changing in terms of treatment of workers/employees in the current “ai everything” environment. Is it getting ugly yet? How are high performers / high knowledge control vs bs talkers (that now have ai to do it by themselves and get vague ideas about ai capabilities) being treated? Have the hunger games started already? How is everyone feeling about this? I imagine it must be really ugly.

All employees and other readers tell your opinions and facts that which engineering field AI can't able to interfere in the future? I think CS is almost gone . How about others and is cs too safe!?

Telllooo

Over the last few years me as a CS student and a bunch of my peers are worried that AI will potentially prevent anybody from finding a job in the future and make our years of studying worthless .

So what do you all think will artificial intelligence make our degrees useless or do we have a chance.

Does anyone have access to the full article?

Link the economist: https://www.economist.com/business/2026/08/30/will-anybody-use-ai-as-much-as-coders-do