Werner Vogels Hands Out Newspapers at His Likely Final Re:Invent. The Man Who Built the Cloud Isn't Done Teaching.

Sixty thousand people wait in the Venetian Expo. Werner Vogels walks out holding something nobody expected: a newspaper. Actual newsprint. Ink that smudges.

His black T-shirt reads "Open mind for a different view / And nothing else matters", Metallica lyrics for those keeping track. The CTO of Amazon has worn cryptic slogans on stage for years. This one fits the moment.

"The Kernel," reads the newspaper's masthead. One copy on every seat.

This is probably his last re:Invent keynote. He hinted as much to The New Stack's Frederic Lardinois recently. Vogels moved to Dubai a while back. Seattle and its gray winters are behind him. The conference grind—airports, hotels, stages, repeat—wears differently at 67 than it did at 47.

So he prints a newspaper. In 2025. The guy who helped make paper irrelevant in computing hands out something you can fold, stain with coffee, leave on an airplane seat. Open mind for a different view. Call it a parting gesture. Call it professorial. Either works.

From X-Rays to Everything Store

Vogels took a strange path to tech royalty. Dutch navy service. Medical radiology. Computer science came later, almost sideways. He earned his Ph.D. from Vrije Universiteit Amsterdam in 2003. His advisor was Andy Tanenbaum, whose operating systems textbook trained half the engineers in Silicon Valley. Vogels specialized in distributed computing, making scattered machines behave as one.

That expertise turned out to matter. Amazon in 2004 was buckling. The company had built itself selling books and DVDs, and its software architecture showed it. Holiday traffic crushed the servers. Something had to change.

Vogels arrived as Director of Systems Research. Months later: CTO. The speed of that promotion tells you what Amazon saw in him.

What followed reshaped how software gets built. Vogels and his team broke Amazon's monolithic codebase into hundreds of small services. Each team owned its piece completely. Wrote the code, ran the servers, answered the pager at 3 a.m. when something broke.

"You build it, you run it." Five words. They demolished the wall separating developers from operations in traditional IT shops. That wall had stood for decades. Vogels tore it down. The DevOps movement traces back to what Amazon figured out in those years.

Then the insight that birthed an industry. Amazon had built infrastructure capable of handling Black Friday traffic spikes. Most of the year, that capacity sat idle. Why not rent it?

AWS launched in 2006. Two services: S3 for storage, EC2 for computing power. Vogels called S3 "the ninth world wonder in a digital sense." Critics called AWS a distraction from retail. A side project. Nice revenue, maybe, but not the main event.

Around 2010, Vogels predicted AWS would eventually exceed Amazon's retail business. People thought he'd lost perspective. A cloud computing division bigger than the everything store?

He was right. AWS now holds roughly 30% of the global cloud infrastructure market. Microsoft trails at 22%, Google at 12%. AWS generates the bulk of Amazon's operating profits. Every major tech company scrambled to build competing cloud platforms after watching Amazon's runaway success.

Vogels saw it coming when nobody else did.

"I Drift Off"

In a side room at re:Invent, Vogels sits down with implicator.ai. The conversation careens. Healthcare. Loneliness. Japanese eldercare. Kenyan teenagers. Cultural homogenization in AI. His hands move constantly. One thought crashes into the next before the first one finishes.

"I have a tendency to drift off," he says at one point, catching himself mid-tangent. No apology in his voice. The drifting is how he thinks.

The tangent that prompted the admission: stroke detection. A neurosurgeon in Dublin told him something that lodged in his brain. Every minute a major stroke goes undetected costs a million brain cells. Die. Gone. The math haunted Vogels.

So he starts calculating. CT scans could run through language models to catch strokes faster. But which model? The big Claude model runs $15 per million tokens. Facebook's smallest Llama? Fifteen cents.

Through Amazon Bedrock, his team can route the same workload through different models and watch the cost shift in real time.

"Is the answer you get from that big model so much better?" Vogels asks. For stroke detection, maybe not. "If the only thing you want to do is word completion, you don't want to pay $15 per word."

Here is where it gets concrete. At $30 per scan, hospital administrators hesitate. They run cost-benefit analyses. They form committees. Meanwhile, brain cells die. Drop the cost to 20 cents. Scan everyone who walks in with a headache. The economics determine the medicine.

Vogels talks about AI this way, not as magic, but as infrastructure with price tags. What happens when costs drop. What breaks when they do not.

The Loneliness Problem

His predictions for the coming years veer toward the unexpected. Not new cloud services. Human problems.

Loneliness fixates him. He calls it an epidemic nobody recognizes as one.

"Baby boomers, and I'm sort of the last of that generation, now you can kind of guess how old I am, they're all healthy. Healthier than generations before. They have disposable incomes. The longer we can keep them at home, the lower the stress on healthcare systems."

He visited Japan recently. The traditional model there: kids care for aging parents, everyone lives together, grandparents help raise grandchildren. That model is cracking. Younger generations want careers. They do not want to become caretakers.

Technology might fill part of the gap. Vogels rattles off examples. Pressure sensors in beds, if grandma goes to the bathroom at night and does not come back in ten minutes, an alarm triggers. Sounds trivial. But without that sensor, she might need to move to a care facility just so someone can check on her. Robots that remind patients about medication. Amazon's Astro home robot, which users apparently treat less like an appliance and more like... something else.

He mentions Kate Darling, the MIT researcher who studies how humans relate to robots. The findings surprised him. People do not treat robots like machines. They treat them like pets. Give them names. Talk to them. Play with them.

"And not if they're six or seven or eight years old," Vogels says. "No. If they're 80, 90 years old. And if you make one that looks like a cat and meows like a cat, you'll sell a lot of them."

Does a robot cat solve loneliness? He does not pretend it does.

"Loneliness is mostly solved by human to human. Unfortunately."

That last word hangs there. Unfortunately. Because human connection cannot scale. Cannot be manufactured. Cannot be deployed across populations.

His own family scattered across the globe. One daughter in Florida. One in Washington State. Vogels in Dubai. "And by the way, I wouldn't want them to take care of me, but that's a whole different story." He laughs when he says it. The laugh does not erase the point.

Video calls connect people who used to share dinner tables. Better than nothing. Not the same thing.

"I Don't Want the World to Turn Into America"

The conversation shifts to language models. Vogels leans forward. His energy changes.

The biggest, most capable AI models come from two places: America and China. Translation handles the language barrier on the surface. Ask a question in Spanish, get an answer in Spanish. The words convert fine.

Culture does not convert.

Vogels uses an example. Ask an American-trained model to summarize an Isabel Allende novel. Compare that to what you would get from a model trained on South American literature with South American cultural context. The facts might match. The understanding will not.

"Culture is super important in communication," he insists. "It is not only how big the models are. How much reasoning can they do. But what is the core of their culture."

He points to Ricoh in Japan. They trained language models from scratch on Japanese documentation, specifically to interact with Japanese customers appropriately. An American model translated into Japanese gets the information right and the social register wrong. The politeness levels. The formality markers. The thousand small signals that Japanese speakers read automatically.

Then there is Jacaranda Health. They work with pregnant women in Kenya, mostly through SMS. Not smartphone apps, basic text messages on basic phones. The women they serve are young. Fourteen, fifteen, sixteen years old. Pregnant. Often scared.

Think about that for a second. A chatbot built for European users assumes a certain demographic. Late twenties, early thirties. Educated. Married, probably. The whole communication style follows from those assumptions.

Now try deploying that in rural Kenya. A teenager gets medical advice delivered in a tone meant for someone twice her age, from a different continent, with a different relationship to authority and healthcare and pregnancy itself. The information might be accurate. She will not act on it. The delivery kills the message.

Jacaranda built something different. Local languages. Local cultural knowledge baked in. Communication that actually reaches the people receiving it.

"I don't want the world to turn into America," Vogels says. No hedging. No diplomatic softening.

The sentence just sits there.

Humans in the Loop

For someone who built infrastructure enabling the AI boom, Vogels spends a lot of time emphasizing limits. One phrase recurs: "AI predicts, but we decide."

He illustrates with Amazon's fraud detection. Nine billion packages a day. Nine billion orders. Humans cannot review that volume manually. So Amazon trained models on billions of historical orders, which ones turned out fraudulent, which ones did not, and scores incoming transactions against those patterns.

But the system does not auto-reject flagged orders. Suspicious transactions go to human reviewers. The AI narrows the funnel. Humans make the call.

Counterfeits work similarly. Vogels mentions Amazon removed either 25 million or 250 million counterfeit products last year. He genuinely cannot remember which. "One of those two," he says, waving his hand. The uncertainty itself makes the point. At those volumes, an order of magnitude becomes a rounding error. Models flag the obvious knockoffs. The ambiguous stuff. People decide.

"If I use AI to create code and I work for a bank and for some reason that code isn't compliant with regulations, I can't tell the regulator 'oh, but the AI did that,'" Vogels says. "No. It is you. It is still your work."

Tomorrow's keynote introduces what he calls the "renaissance developer." The name comes from, well, the Renaissance. Vogels wants developers who know multiple disciplines, who can paint and engineer, so to speak. Technical depth combined with domain breadth. People who grasp what the AI produces, not just that it produces.

"You have never been more valuable," he tells developers. Not despite AI. Because of it.

But he sees the tension clearly. Code gets generated faster than humans can review it. Traditional code review, senior and junior developers sitting together, critiquing each other's work, served as education. Junior developers learned from senior feedback. Senior developers got fresh perspectives.

"That natural learning process can't, doesn't, shouldn't go away," Vogels says. "Because otherwise we lose."

The Education Gap

What clearly irritates Vogels is how generative AI reached consumers. Normal technology rollouts work differently. You educate early adopters. Get feedback. Refine. Then educate broader audiences. By the time average users encounter the technology, they understand what it can and cannot do.

Generative AI skipped those steps entirely.

"Here are two companies that want to fight over search," Vogels says. The reference to Google and Microsoft lands without subtlety. "So they dump technology in the hands of consumers without actually telling them what it can do and what it cannot do."

The race to ship faster than competitors eliminated the education phase. Users got tools without context. Now people expect factual accuracy from systems optimized for generating plausible text. They treat pattern-matching engines like oracles.

"And if a chatbot helps your kid kill himself more efficiently, then we should ask ourselves whether that is actually really where we want technology to go."

The reference stings. Reports of AI chatbots contributing to user suicides have made headlines.

"We created that stuff," Vogels continues. "There is a bit of responsibility on our side to help it get used responsibly. One of the leadership principles at Amazon: with success and scale comes both responsibility."

Rwanda's Data Nerve Center

His optimism resurfaces when describing what is possible with clear-eyed implementation. Rwanda's Ministry of Health runs something that stopped him cold.

"In their control center, they have data about everything in the whole country. Real time. Monkeypox is happening over there in that particular district. And you know what. It is largely among sex workers. So those are the people you vaccinate. Not everyone else in the country."

Rwanda also decided, this was a policy choice, not an accident, that pregnant women should not have to travel more than half an hour to reach medical care. Thirty minutes maximum. Try implementing that. You need maps of where women actually live. Where clinics actually exist. The gaps between them. Then you build clinics where they are missing.

"The average age in Rwanda, and I've noticed this in Angola and Kenya too, is nineteen," Vogels notes. "In ten years, the whole young population of the world will be living under the equator."

The center of demographic gravity shifts south. The technologies that matter most may need to solve problems in Lagos and Kigali, not San Francisco.

The Newspaper on Your Seat

Back on stage, Vogels works through his keynote. "The Kernel" sits in every lap. The format forces different engagement than slides. You hold it. Turn pages. Read linearly instead of skimming bullet points.

The choice feels intentional. Vogels spent twenty years explaining cloud computing to audiences wanting quick takeaways. He gave them something richer. A philosophy of building systems that scale. Principles outlasting any individual product.

"You build it, you run it." "APIs are forever." "Eventually consistent." These phrases entered industry vocabulary because Vogels repeated them until they stuck.

Now newspapers. In a world drowning in ephemeral digital content, he prints something physical. Something you take home. Something requiring no login.

The Man From Amsterdam

One detail about Vogels. He did not get a driver's license until age 28. Growing up in Amsterdam, he did not need one. Bicycle. Tram. Train. That was transportation.

The detail illuminates his worldview. He comes from somewhere public infrastructure works, where cars are optional, where density enables efficiency. When he criticizes American assumptions baked into AI models, he speaks from outside the American frame.

"If Elon is right, tunnels are the answer," Vogels muses about urban transportation. "Others think flying taxis will work. Next month in Dubai, the first ones launch. 350 dirhams, about 90 euros, from the airport to Dubai Marina."

He runs the comparison. Driving that route: ninety minutes. Flying: a few minutes. Worth 400 dirhams?

But his instinct pulls elsewhere. "I'd solve it with better public transportation. Because I'm from Amsterdam."

The city shaped the engineer. The engineer shaped the cloud. The cloud shapes everything.

Still Building

At 67, living in Dubai and likely delivering his final re:Invent keynote, Werner Vogels shows no sign of winding down. His 2026 predictions address loneliness, quantum-safe cryptography, defense technology spillover, personalized education. He worries about cultural homogenization in AI. He celebrates stroke detection that costs pennies.

"Health is all we have," he tells the room. "Time is the only thing limited for humans. If we can spend that time as well as possible, the better."

Half the audience probably thinks he is rambling, he jokes. The crowd laughs. Vogels grins and keeps going.

The digressions connect things. Healthcare to loneliness to robots to culture to infrastructure.

Outside, Las Vegas glitters. Inside, everyone holds a newspaper from the man who helped make paper obsolete.

Now go build.

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