Interesting to see LinkedIn climbing the ranking.
I noticed it first-hand on Google AI Overviews.
It often cites professional and insightful posts, even those with very little engagement. I saw posts with just one like from small accounts being cited as the top source.
It seems LLMs get it.It’s not all about virality. Sometimes content quality matters too.
Source: Semrush via Andreessen Horowitz Instagram account
No words needed.
The future is going in one direction only.
Most ChatGPT vs Claude takes are wrong.
They ignore the one thing that actually matters.
It’s not ChatGPT vs Claude.
It’s quota vs quota!
Opus 4.6 Extended Thinking > GPT 5.4 Extended Thinking.
But to make Opus 4.6 Extended useful, you need Claude Max.
There’s no way around it.
On Claude Pro ($20/month), the quota is too limited.
For serious work, it makes Opus 4.6 almost unusable.
Claude Max starts at $100/month!
ChatGPT Pro 5.4 Extended > Opus 4.6 Extended Thinking.
But again,
ChatGPT Pro is $200/month.😅
And GPT Pro 5.4 Extended is available only there.
That’s why this is not a model comparison.
It’s a budget comparison.💰
If you have the budget, ChatGPT Pro is the best option for most tasks, including research, coding, images and videos.
If you compare $20/month plans like for like, ChatGPT still wins.
Not because it has the best model.
But because the quota for complex queries is higher.
And in real workflows, that matters more than people think.
I keep hitting the quota on Claude, I almost never hit it in ChatGPT.
Few extra notes:
• Claude is better with slides, and pptx files.
• The Claude add-in for PowerPoint and Excel is genuinely excellent.
• Claude Artifacts can build local interactive dashboards, which is cool, but for me it’s still a nice-to-have rather than something I’d use in production.
• ChatGPT wins in marketing because it also handles images and video, and apps.
For vibe-coding, Claude Code and OpenAI Codex are broadly comparable.
But even there, the same issue comes back.
If you want the full power of Claude Code, you’ll likely choose Opus 4.6 Extended. And then you hit the quota wall all over again.
Extremely frustrating actually.
My conclusion:
For most people, the real decision is not Claude vs. ChatGPT.
It’s how much you’re willing to spend on AI every month.
That’s it.
Just because you can, doesn’t mean you should.
AI makes everything possible.
But not everything is valuable.
With AI, you can:
→ Build a web app a day.
But should you?
yes
no
→ Create ten perfectly-designed presentations a day.
But should you?
yes
no
→ Ship one agentic workflow a week.
But should you?
yes
no
More stuff no one asked for. 😅
Before falling for FOMO, pause.
Ask yourself:
Is this making me (and my team) actually more productive…or am I just scaling the production of rubbish?
The real edge in AI isn’t doing more.
It’s doing less, better.
Choose wisely.
Meta’s hiring is a reckless roller coaster 😂.
If it happens, Meta’s headcount will drop back to pre-2021 levels.
In other words:
a full reset of the massive hiring spree during the post-COVID tech frenzy.
But wait a sec...
While headcount is going backwards, profits are through the roof. Meta’s net income jumped from $29.1B in 2020 to $60.46B in 2025.
That’s a 108% increase! 🤯 Roughly the same scale of workforce-> Twice the profit!
So let’s stop with the comfortable narrative:
"Tech is just correcting excessive hiring."
Productivity is exploding.
Fewer people.
More output.
If this isn’t AI-driven productivity, I’m not sure what is.
Chart courtesy of Claude: Meta headcount between 2019 and 2026.
Elon is playing ten moves ahead.
While most people are still arguing about his tweets.
It’s now obvious:
AI won’t be won by who has the "best model."
It’ll be won by who controls the infrastructure.
And that’s where things get interesting.
AI data centers on Earth are hitting limits:
Land is scarce.
Energy is expensive.
So what’s the next move?
Space 🚀.
Building data centers in orbit sounds crazy…until you realise it actually solves both problems.
But it’s still too expensive.
For now.
Starcloud is already working on satellites cheap enough to compete with Earth-based compute.
But launch costs are killing the model.
Now enter Starship by SpaceX into the equation.
Once fully operational, the economics of an orbital data center flip:
A 1GW data center in space could cost half of one on Earth.
Let that sink in.
Whoever owns the cheapest path to orbit, owns the future of AI.
And guess who’s in the lead?
Yours truly, Elon 😅.
Tried Starlink for the first time today.
On an airBaltic flight, apparently the first (and only?) European airline offering it. And it’s free.
In fact, I’m writing this post mid-air!
It’s faster than any complimentary WiFi I’ve ever tried, it feels like normal home internet.
A real game changer.
Looking forward to the Starlink IPO. I almost never buy individual stocks, but I might make an exception here.
Cheers from the Baltics!
I would have never made it to my German exam without ChatGPT.
For the past couple of months, GPT became my personal teacher.
And honestly, it was the best teacher I’ve ever had.
Since I moved to Zurich, I’ve tried everything:
group classes, intensive study-abroad programs, private tutors, online learning apps.
Nothing really worked.
Until something dawned on me.
I use ChatGPT all the time to learn how to code or improve my writing.
So why wasn’t I using it to learn German?
I guess my mind was still stuck in the old playbook:
courses, textbooks, learning apps.
So I created a project.
I gave it detailed instructions about my current level and what I wanted to achieve.
I uploaded exam templates and regulations so GPT understood exactly what exam I was preparing for.
Then I structured the chats like chapters in a book.
Each chat focused on one grammar topic, with tables, examples and exercises.
Not huge conversations. Just quick prompts like:
“Show me the declension of personal pronouns and how to use them.”
I kept coming back to each chat like a chapter in a textbook.
Then I created a separate chat just for exercises.
The exact type I would find in the exam.
Except GPT can generate infinite exercises, tailored to the exam format.
Try doing that with a traditional learning app.
Or even with a human teacher.
Or… with a human girlfriend with limited patience 😅.
This experience made something very clear to me:
AI isn’t just a tool.
It’s a 24/7 personal assistant and tutor.
Use it as such.
Hey Sam, AI data centers in space are not crazy after all.
At first glance, the economics look brutal.
According to calculations reported by The Economist, building a typical data center on Earth costs around $16B per gigawatt over five years.
In space, that number jumps to ~$51B.
No contest.
But that comparison only holds if launch costs stay high and satellite stay heavy.
That is what startups like Starcloud are trying to change.
They created state-of-the-art satellites that are smaller, lighter, and cheaper than systems like Starlink.
Now add SpaceX Starship to the equation. 🚀
If launch costs fall far enough, the price per gigawatt could drop dramatically, potentially to below $10B.
And that changes everything.
Like always, Elon Musk is playing several moves ahead.
He knows that the space race is the next big arena for AI.
If the value of AI still isn’t obvious...
Sure, just because I can build something with AI doesn’t mean I should.
Out of 10 scripts I build, 9 will probably be work-slop.
But…
That 1 script out of 10 will change the game. 🚀
And anyway it's a huge improvement compared to zero of one year ago!
When you think of AI, think:
“Could I have done this a year ago?”
If the answer is no, you’re probably on the right path!
