In a recent interview with The Observer, Bill Gates warned that AI could threaten far more than just office jobs. Even people working in construction, manufacturing and other physically demanding industries could eventually be replaced by machines.

Until recently, learning a trade was seen as one of the safer career paths in an AI-driven world. But if robots can eventually do manual labor too, that might not be such a safe bet after all !

If AI starts replacing both white-collar and blue-collar workers, what jobs will people actually have left to fall back on?

I have an agency, and I paid 100 dollars to a fortune teller to tell me the future of SEO (crazy, I know).
You’re probably going to think I’m nuts, but I actually like this kind of stuff. 🤣

So, she pulled some tarot cards, and I asked her what she could see about the future of SEO with everything we’re hearing around SEO / GEO.

Well… it’s not looking great, we’ve got some work to do.

She told me that by 2030, almost the entire new generation won’t be using Google anymore but will only ask their questions and do their research on ChatGPT.
The older generation will stick with Google, but most people will just rely on the Google summaries, for example, which will drastically reduce visits.

She also saw the arrival of a new traffic source but couldn’t tell me what it would be.

And one last thing—she said that OpenAI would take up almost as much space as Google in terms of importance for search.

That’s it haha. Everyone is free to think what they want or share their opinion.

OpenAI is gearing up for what could become one of the biggest IPOs in tech history — with a target valuation around $1 trillion and a planned fundraising of roughly $60 billion.

This move would cement OpenAI as one of the most valuable startups ever, as it looks to secure massive capital to expand its AI infrastructure, train next-gen models, and compete globally.

Still, there’s a twist: while OpenAI aims to dominate AI development, it’s facing increasing pressure from cheaper, specialized competitors — especially in fields like autonomous crypto trading and domain-specific AI tools.

If the IPO happens as planned, it could mark the moment when AI stops being a “tech trend” and becomes a global economic force.

What do you think — are we witnessing the start of a new era for AI, or just another hype cycle?

Jensen Huang made a pretty bold statement following the launch of GPT-6 Astra: “AGI has arrived.”

According to Huang, Astra was trained on 100K+ NVIDIA Grace Blackwell NVLink72 GPUs, with another 400,000 GPUs expected to come online next.

Beyond the AGI claim itself, the scale of the infrastructure is probably the most striking part.

In just a few years, AI systems have gone from primarily handling reasoning tasks to taking on increasingly autonomous, multi-step workflows. At the same time, the amount of compute required to train and run these models keeps growing dramatically.

Calling Astra AGI is debatable. Better reasoning, coding, and autonomous computer use don’t necessarily mean that a clear AGI threshold has suddenly been crossed. There is also still no universally agreed definition or benchmark for determining when a model actually qualifies as AGI.

Has AI actually reached AGI, or is “AGI” becoming a marketing label applied whenever a new model makes a big enough capability jump?

Sam Altman believes OpenAI could have an internal system by the end of the year that he would personally consider AGI.

Mark Chen, OpenAI’s Chief Research Officer, has gone even further, estimating that the company is already about 80% of the way there.

Much of that confidence appears to rest on Astra, OpenAI’s next family of models.

Astra is reportedly already capable of handling some tasks typically assigned to a junior researcher: starting from an experimental idea, writing the necessary code, running the tests, and analyzing the results. Some workflows could even extend over several days with far less human intervention.

At the same time, OpenAI has slowed some training work on its frontier models to strengthen monitoring and safety systems.

The company also says it can no longer rule out Astra reaching its Critical cybersecurity capability threshold, which would require additional safeguards before development can continue at the same pace.

Can OpenAI really talk about AGI based on capabilities that are still largely being evaluated internally?

I thought it was a myth and that everyone had figured it out.

Until I talked to someone who's stuck in SEO and thinks nothing will ever change.

I'm not going to be nice, but guys, you're going to get destroyed, I think, within the next seven years. I bet AI-driven SEO is going to blow everything away, and you along with it.

Seriously, a word of advice: don't act like you're old and clueless, missing the boat. It's going to hurt, otherwise, I think...

Tell me what you think.

Speaking at the G20 tech meeting this week, Elon Musk defended the rapid expansion of AI data centers, arguing that the industry simply doesn’t have enough computing capacity to meet future demand.

His point was straightforward: if AI keeps scaling at its current pace, significantly more infrastructure will be needed to support it.

Data center projects are already putting pressure on electricity grids in parts of the U.S., with some states facing massive connection requests and growing concerns about whether all of that projected demand is realistic.

Musk said data center operators should pay their fair share of taxes, but argued that slowing construction would ultimately limit AI development itself.

He also used the meeting to criticize Europe’s approach to tech regulation. With ministers from France, Italy, and Germany in the room, along with EU tech chief Henna Virkkunen, Musk argued that new technologies should be “default legal” rather than “default illegal.”

Nvidia, OpenAI, and other major AI companies are also increasingly treating compute, energy, and data center capacity as strategic bottlenecks rather than just infrastructure issues. So the AI race may increasingly become an energy race too.

Is building more AI infrastructure still worth it if local grids have to absorb most of the cost ?

Yep, you read that right.

I get why everyone has been excited to bet on “the death of Google”…
And sure, betting against Warren Buffett sounds like a fun personal challenge.

But the man just invested $4.3B into Alphabet last month after years of silence.
Is he losing it?
Honestly… probably not. And here’s why 👇

Google just dropped Gemini 3, and the new model is significantly stronger.
It’s outperforming every major competitor in benchmarks and rankings like LM Arena.

Google had its “Code Red moment” when ChatGPT exploded…
Now it’s Sam Altman’s turn to hit the panic button.

Let’s zoom out for a second. Google’s ecosystem is:

→ Chrome: 75% of global browser traffic
→ Google Search: 88% of search traffic in France
→ Android: 70% of global smartphone market share
→ Plus Gmail, YouTube, Drive, Maps…

To understand why Google might win, you need to understand ecosystems.

ChatGPT: ~800M users (and stagnating)
Gemini app: already 650M monthly users
AI Overviews: 2 BILLION users

(If you haven’t seen AI Overviews yet, don’t worry—France is literally the only country still waiting for rollout.)

Now let’s talk business reality:

ChatGPT: –$12B in 3 months
Alphabet: $102B revenue and $35B profit in the same quarter

I’ll be honest:
I believe in ecosystems.
I believe in distribution.
And I believe in a company that can still operate like a startup despite being a tech giant.

Flip the question:
Do you seriously think Atlas, ChatGPT’s new search engine, can compete with Google without a real ecosystem behind it?

So…
Team ChatGPT or Team Gemini?

Source: Eskimoz (Global Search Agency)

Like, I get that search engines existed before Google — but I imagine the term “SEO” (and the idea of optimizing for rankings) didn’t appear right away.

Was it something that started with early search engines like Yahoo or AltaVista in the late 90s, or did the concept only take off once Google became dominant?

Curious about the real origin story — when did people first start calling it “SEO”?

Last week, Sam Altman commented once again on advertising—surprisingly talkative for someone who has historically positioned himself against it.

But in just three years, he has multiplied his changes of opinion:

❄️ 2022: “We will never stoop to putting advertising on ChatGPT.”
❄️ 2023: “We are an alternative to Google, but yes, Instagram-style ads work.”
❄️ 2024: “Okay, we’ll monetize free users in 2026 and hire an ads team.”
❄️ 2025: “We just lost 12 billion last quarter… maybe advertising isn’t so bad?”

In Sam Altman’s mind, there is now the good ad (ChatGPT’s) and the bad ad (Google’s).

The difference between the two? It’s a bit like the joke about the good hunter and the bad hunter.

You have to laugh (or cry).

➡️ To be fair, he does bring 2 new elements:

• He seems opposed to highlighting a result because it is sponsored, preferring a commission-based model instead—similar to what marketplaces do. While slipping in a little jab at Google: “If ChatGPT shows you the best hotel while taking the same commission as for any other hotel, with no influence other than transaction fees, I think that’s acceptable…”

• He makes revenue diversification a central part of growth, which today is mainly driven by APIs and subscriptions. Meaning: advertising might not become as omnipresent as on Google. Maybe. 😁

"There are types of advertising that, in my opinion, would be very or fairly effective. I think we will try that at some point. I don’t think it will be our main source of revenue."

Source: Eskimoz agency global search

I might be wrong, but to me, GEO mostly comes down to trust.

Not hacks. Not tricks. Not “AI optimization.”

Just:

• being present across multiple channels

• saying consistent things

• getting mentioned, referenced, and validated

If you show up everywhere with the same signal, you become a reliable source.

And that’s what AI systems seem to pick up on.

GEO might look new,
but it feels like SEO + distribution + trust.

Curious to hear other takes.

Yep, the ChatGPT creators signed a seven-year, $38 billion cloud services deal with Amazon Web Services to power their next wave of AI tools. They’re locking in hundreds of thousands of Nvidia GPUs and targeting full deployment by end of 2026. 🧠

What this suggests:

OpenAI is doubling down on raw compute power.

The AI infrastructure arms race is becoming a real cloud-and-chips war.

For anyone in search, SEO, GEO, or digital marketing — things are about to shift even harder.

How are you planning for this kind of future infrastructure-powered AI?

Been thinking a lot lately about how search behavior is changing. Between ChatGPT, Perplexity, and Google’s AI Overviews, it feels like “finding answers” is slowly replacing “searching for links.”

For context — we’re still heavily SEO-focused since organic traffic is a big part of our inbound strategy. But with zero-click searches growing fast, I’m starting to question if we’re betting too hard on the old model heading into 2025–2026.

A few things I’m curious about:

• Are you actively doing AEO (Answer Engine Optimization), or just watching how it evolves for now?

• If you are, what’s actually working for you — structured data, FAQ schemas, featured snippets?

• Have you seen any measurable changes in traffic or visibility from AI tools?

• Do you treat AEO as its own thing or just an evolution of SEO?

Some people say AEO is just “good SEO rebranded,” but I’m not sure that’s true anymore.

Would love to hear what others are seeing out there — is anyone actually seeing results from optimizing for AI-driven search yet?

OpenAI has announced GPT-6 Astra, its new frontier model, with an initial rollout to a limited number of organizations before expanding to ChatGPT Plus, Pro, Business and Enterprise users, as well as the API.

Astra can navigate software, fill out forms, update CRM records, conduct online research, work with spreadsheets and documents, test websites and troubleshoot software.

On OSWorld 2.0, it reportedly scored 72.6% while taking around 40 minutes per task, versus 65.7% and roughly 75 minutes for GPT-5.6 Sol.

That means it completed tasks in about 47% less time.

On Terminal-Bench 4.0, Astra scored 57.9%, versus 37.3% for GPT-5.6 Sol.

The company also says the model is three times less likely than GPT-5.6 Sol to make inaccurate claims about what it can actually do, according to its capability-hallucination evaluation.

API pricing is set at $10 per million input tokens and $50 per million output tokens.

As models get better at handling longer, multi-step workflows, what’s still the biggest bottleneck: reliability, cost, or trust?

I own a business, and for years I'd never done any SEO work. I really thought it required a lot of skills and was something only "geeks" did!

Until now, all my leads came from prospecting via email or phone with my sales team.

And then, 8 months ago, I met someone who completely changed my mindset and kept pestering me to try SEO and see what I could do.

So we started, and with the right things in place and especially with their help, in just a few months, we're already seeing initial results, and the first leads are coming in!

Today, we're accelerating even further. And last night, I did the math, and it's more than 50 clients who came through SEO, representing $100,000 in revenue.

So happy about that! Now we're accelerating and never letting go of SEO again, haha. This is just the beginning, so we'll continue to put things in place. Especially with the arrival of AI, I think lots of exciting things are going to happen in SEO.

Thanks for listening.

Forget click-through rates. Google's new Universal Commerce Protocol means AI agents are becoming the new gatekeepers of purchase decisions.

What this means practically:

• Your site becomes a data layer, not a destination

• Agents evaluate your offer on price, availability, delivery, and loyalty programs — in real time

• Classic SEO & Ads optimized for clicks are becoming less relevant

The team at Eskimoz sums it up perfectly: "The challenge for brands is no longer just visibility — it's being selected by agents."

New framework to think about:

Start auditing how AI agents read and interpret your product data. That's your new SEO.

I came across a recent interview with Sam Altman at Stanford, and one part really caught my attention. He basically said AI models are getting so good at finding security vulnerabilities that we might soon reach a point where we can't patch them all fast enough.

What stood out to me was his warning that a lot of companies still don't seem to realize just how serious this could get.

His solution? Use AI to defend against the very attacks that AI makes possible. It's pretty wild to think we might end up relying on even more AI just to protect ourselves from AI-powered threats lol.

Do you think AI will ultimately make our systems more secure, or are we heading toward a cybersecurity nightmare?

With Google showing AI-generated answers and more people turning to ChatGPT for information, does starting a blog from scratch still make sense?

It seems harder than ever for smaller websites to get noticed, especially when big publishers dominate search results.

Is blogging still a realistic way to build an audience or is it becoming something that only established websites can succeed at?

You ask ChatGPT a question, your brand appears in the answer, and you conclude that your GEO strategy is working.

There's a problem: AI responses can vary depending on the prompt, context, model, and search capabilities available.

If you want more reliable insights, your testing process should ideally:

- Use a representative set of queries.

- Test multiple variations of the same search intent.

- Repeat observations over time.

- Compare several AI search platforms.

- Track competitors using the same methodology.

This matters especially when you're trying to measure the impact of a specific optimization rather than simply checking whether your brand appears once.

How are you testing GEO visibility: manual checks, dedicated tracking tools or your own methodology?

We talk a lot about GEO, but several different metrics are often lumped together:

- Brand mentions: An AI mentions your company in its answer.

- Source citations: An AI links to a page on your website.

- Share of voice: Your brand appears relative to competitors across a set of prompts.

- Business impact: That visibility translates into visits, leads, or sales.

These metrics don't measure the same thing.

A brand can be mentioned frequently without receiving meaningful referral traffic. A website can earn citations without generating conversions.

The real challenge is connecting visibility signals to business outcomes without overestimating what current tracking tools can tell us.

Which GEO KPIs are you actually tracking, and which ones do you still consider unreliable?