Pixelon (1998–2000): Raised $35 million for streaming technology that didn’t exist. Threw a $16 million launch party with The Who and KISS. The founder was a convicted felon living out of his car. Bankrupt in 18 months. Founder served time.

Theranos (2003–2018): Raised $700 million for a blood-testing machine that would change healthcare forever. Valued at $9 billion. Forbes named her the youngest self-made female billionaire. The technology was a fraud. So was she. Founder in prison.

WeWork (2010–2019): Raised $12.8 billion for a desk rental company. Once valued at $47 billion. The IPO collapsed. The company went bankrupt. Founder walked away with $1.7 billion.

Still no idea how he pulled that off.

The pattern doesn’t change. The consequences do.

Two served time. One is funding his next venture.

WeWork: The $47 Billion Bean Bag Chair

We already had a global office leasing company — Regus, founded in 1989, with over 3,000 locations, profitable.

Then WeWork arrived with beer taps, bean bag chairs, and a messiah complex. Profits weren’t the priority.

In January 2019, WeWork was valued at $47 billion.

At the same time:

• JLL, one of the world’s largest commercial real estate firms: ~$8 billion

• CBRE, the global leader: ~$15 billion

• Regus, the company that literally created flexible workspace: ~$2 billion

Combined: ~$25 billion. WeWork was “worth” nearly double.

For subletting. With kombucha.

The pattern was visible. No one wanted to see it.

Adam Neumann walked around barefoot. He talked about “elevating the world’s consciousness.” He held tequila-fuelled company meetings. He bought a $60 million Gulfstream jet. He wanted to be the world’s first trillionaire.

SoftBank’s Masayoshi Son famously met him for twelve minutes and invested $4.4 billion.

When the IPO filings landed in August 2019, the fantasy collapsed. The documents were meant to inspire confidence. Instead, it read like a confession.

Neumann had been renting buildings he personally owned to WeWork.

The company paid him $5.9 million for the "We" trademark.

A Bloomberg journalist called it "the most bananas thing I have ever read."

Six weeks later: IPO cancelled. Valuation crashed from $47 billion to $8 billion. Neumann forced out.

His exit package? $1.7 billion.

He burned it down. He cashed out. And in 2023, WeWork filed for bankruptcy.

Overhype. Oversimplify. Underdeliver. Cash out.

10,000 kilometres away, another pitch was landing: a 170-kilometre mirrored city in the Saudi desert.

No cars. Nine million residents. Powered entirely by renewable energy. Cost: $500 billion.

Different product. Different continent. Same playbook.

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NEOM: The $500 Billion Bet

WeWork was a real estate company pretending to be a tech company.

NEOM is a real estate project pretending to be a civilisation.

I worked on NEOM. The gold rush was real — management consultancies, commercial real estate firms, tech vendors. Everyone wanted in.

Including Adam Neumann and his $1.7 billion payout. His new company Flow launched in Riyadh in late 2024. Same model. Same “conscious community” pitch. What could go wrong?

The Pitch

NEOM is a greenfield smart city project in the Saudi desert. Its primary concept, The Line, was supposed to be 170 kilometres long, 200 metres wide, 500 metres tall - no cars, mirrored walls, one million residents suspended in the desert. Alongside it: a ski resort called Trojena and an industrial port city called Oxagon.

Just how batshit crazy was it? I’ve seen survey results that the consultants shared with NEOM that claimed Americans would rather go on a ski holiday in Saudi Arabia than Kitzbühel or Whistler.

Someone got paid to write that. I hope it was a lot.

The 10% Question

I never thought they’d achieve their lofty ambitions. The timelines were fantasy. The promises defied physics.

But here’s what I kept thinking:

So did they hit the 10%? Let’s look at the numbers.

The Line was supposed to be 170 kilometres long. Nine million residents. Completion by 2030.

The 2030 reality: 2.4 kilometres. Fewer than 300,000 residents. Full completion pushed to 2045 — if it happens at all.

That’s not “behind schedule.” That’s a 98% scale-back.

At least $50 billion has been spent. Leaked internal audits suggest the real cost to complete could hit $8.8 trillion — 25 times Saudi Arabia’s annual budget.

And in early 2026, the pivot became official. Contract cancellations. Billions in tunnelling and steel work scrapped.

The excavated land? Being repurposed for AI data centres and server farms.

The mirrored city is becoming a tech park.

The Consultants

I saw thousands of pages of research reports and strategy documents. McKinsey. BCG. The major CRE firms. Every tech vendor you can name. Everyone wanted a piece.

No one wanted to hear about the practicalities. Everyone was full steam ahead.

Surveys claiming Trojena, the NEOM holiday resort, would become “the Saint Tropez of the Middle East.” A NEOM Metaverse that needed to launch yesterday. I read those results and thought people had lost their minds.

The gold rush wasn’t just about building a city. It was about billing for one.

It's easy to call NEOM crazy now. But we all cashed the cheques.

Still, I got to do something rare. Deep research into how technology can actually change lives — not next quarter, but a decade from now. Visionary work — with a dose of pragmatism about the steps to get there.

Personal digital twins. Global aggregation of patient data. An ecosystem connecting testing centres, AI platforms, wearables, doctors, hospitals — all integrated, all learning.

In Part 1, Tim Kobe called it "human outcomes" — technology measured by what it does for people, not what it does for shareholders.

That's what I got to work on. The visionary stuff. The work that makes you think.

How is that possible?

NEOM had two things most clients don’t: cash and a long horizon.

That combination is rare. Most innovation dies in quarterly reviews. Budgets get cut. Priorities shift. The safe bet wins.

NEOM gave people permission to take a proper shot.

Not every idea will make it to market — most won’t. But progress gets made in the attempt. Engineers solved problems that didn’t have solutions yet. Architects designed for constraints that don’t exist anywhere else. Researchers got to ask “what if” without being told to ask “what’s the ROI.”

That’s the thing about well-funded delusions. Sometimes the side effects matter.

The 2% That Mattered

Underneath the chaos, some things actually got built.

The world's largest green hydrogen plant. Construction tech that's dragging a sector stuck in 1973 into the modern era. Smart infrastructure that goes beyond dashboards nobody uses. A talent magnet — tech leaders, consultants, engineers, architects flooding into a region that had never been a destination for global talent.

Will anyone copy a 170km mirror wall? No.

Will cities steal parts of the model? Definitely.

Will it deliver a return on $50 billion? Probably not.

Here’s what makes NEOM different from 3G, 5G, and the Metaverse. Those hype cycles created noise — billions spent, little to show for it. The money evaporated. NEOM’s hype actually went somewhere.

Saudi got a modernisation engine. Consultants and vendors got paid, but they shipped real work. And people got to test concepts that would never survive a normal client’s quarterly review.

Unlike most hype, this one left something behind.

They did some cool things. The hype was absurd. The ski survey was embarrassing. The timelines were fiction.

But I want to believe the side effects matter. Ask me again in ten years. I'll tell you if I was right — or if I was just another consultant telling myself a story.

The Pattern — With a Caveat

In Part 1, I called this pattern recognition. In Part 2, we watched the dot-com boom invent the playbook. In Part 3, we watched it run again — 3G, 5G, the Metaverse.

Overhype. Oversimplify. Underdeliver.

The players in this piece ran the same playbook. But they’re not all the same.

Different flavours. But the outcomes matter.

Two founders are in prison. One walked away with $1.7 billion. And somewhere in the Saudi desert, a green hydrogen plant is actually getting built.

Same playbook. Three different endings. Only one left something real behind.

Next Week

Part 5: AI.

The pattern is running again. Are we being any more honest than the consultants billing NEOM?

Or are we just telling ourselves a story — because nobody gets paid to say “this might be bullshit”?

If you missed them:

Part 1 – “The Stock-Trading Cat”

Part 2 – “Dot-com. The Original Sin”

Part 3 - “The $100 Billion Hype Cycle: Tech Leaders Never Learn”

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In Part 1, I called this pattern recognition — the ability to see what’s happening across cycles, not just within them. In Part 2, we watched the dot-com boom invent the playbook. Now we watch it run again. And again.

It doesn’t end. It just moves to a new industry, puts on a new suit, and hopes nobody remembers what happened last time.

Different technologies. Different decades. Same playbook.

3G: The Spectrum Catastrophe

In April 2000, while dot-com companies were still dying, the UK government held an auction for 3G spectrum licences.

The forecast: £1-3 billion. The final number: £22.5 billion.

150 rounds of bidding over 36 days. Vodafone alone paid £6 billion for a licence. Germany’s auction raised over €50 billion. Across Europe, operators spent over $100 billion just on licences – before building a single tower.

For the promise of video calling and mobile broadband.

During this time, I was giving a presentation to the board of Clifford Chance — then the world's largest law firm. Clifford Chance represented Vodafone's bid during the 3G auction. Too good an opportunity to pass up.

So I turned to the head of their telco practice and asked: "How did you justify a £6 billion valuation for Vodafone's spectrum bid?"

His answer: “My job wasn’t to justify it. My job was to tell them the price they needed to pay to win it.”

The insiders knew it was madness. Vodafone’s own mobile division head admitted: “I have the fear that it perhaps will be a disaster.”

BT’s CEO later said the industry had “spent £10 billion too much.”

They bid anyway. Because leaving the auction empty-handed meant being “dead in the water.” The fear of missing out was louder than the fear of overpaying.

BT paid £4 billion. A year later, crushed by debt, they spun off their mobile division entirely. It became O2.

I worked for both O2 and Vodafone during this time. The licence auctions were just the headline madness. Inside the companies, it was worse.

Every new device, every new app, every new solution sent people running to clients, overhyping everything all over again. No central strategy. No coordination. Everyone thought they owned innovation — but nobody owned how to get it to market.

I spent most of my time herding cats. Trying to steer toward value over hype. Not everyone wanted to hear that.

The result? Fragmented efforts. Wasted budgets. Failure. Again.

And the promised 3G revolution? Video calling? Mobile broadband? It took another decade to materialise – and by then it was 4G delivering it, not 3G.

The technology was overhyped, oversimplified, and underdelivered.

Same playbook, same ending. Subscribe to see it coming.

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5G: Download a Movie Nobody Wants

Fast forward to 2019. The industry had learned nothing.

5G was going to change everything. Again.

I was in a meeting room with Andy Penn, then CEO of Telstra, back in 2018. It was the first time I heard the tagline: “Download a movie in seconds.”

I raised my hand. “No one downloads movies anymore.”

Everyone looked confused.

“Yeah, but you could.”

Oh shit. Here we go again.

“Download a movie in seconds.” Nobody downloads movies anymore.

“Remote surgery.” Too risky for wireless.

“Self-driving car networks.” Still in testing. Don't need 5G.

“Smart cities.” Limited requirements for 5G.

The most successful 5G use case? Fixed Wireless Access.

We spent hundreds of billions on a 'mobile revolution' only to realise the most useful thing it could do was act as a glorified extension cord for the fibre networks we should have finished a decade ago.

Telecoms analyst Doug Dawson put it bluntly:

It wasn't a failure of engineering — the tech works. It was a failure of empathy. No one asked what a person standing at a bus stop actually needed. They only asked what the hardware was capable of doing.

William Webb, author of The 5G Myth, observed that 5G proponents had been “casting around for problems that might need their solution.”

He also pointed out a truth the industry hates: our speed requirements have hit an S-curve. Beyond 10 Mbps on a phone, the human eye can't tell the difference.

We built a spaceship and used it to cross the street.

Overhype. Oversimplify. Underdeliver.

The Metaverse: The $73 Billion Ghost Town

In October 2021, Mark Zuckerberg made an announcement that would define the next phase of tech hype.

Facebook was becoming Meta. The company was going “metaverse-first.” Zuckerberg called it “the successor to the mobile internet.”

Companies started hiring Chief Metaverse Officers. Disney. Procter & Gamble. LVMH. Crate & Barrel. Publicis even hired a lion-headed digital avatar named Leon to fill the role.

These weren’t fringe startups – these were some of the biggest companies in the world, paying million-dollar salaries to executives who would guide them into the virtual frontier.

The promise: immersive virtual worlds where we’d work, socialise, and live. Ready Player One, but real.

The reality: $73 billion in losses at Meta’s Reality Labs since 2021.

Accenture went all in. They purchased 60,000 VR headsets and onboarded 150,000 new employees through their metaverse platform. They built virtual replicas of their offices – from Bangalore to Madrid to San Francisco – complete with meeting rooms and collaboration spaces.

And that was the problem. In a medium with no physical limitations — where you could build floating conference rooms, infinite whiteboards, spaces that defied physics — they built cubicles. Meeting rooms with finite seating. Spaces where you had to queue.

They didn't just build cubicles; they built a digital version of the very things people were quitting their jobs to escape. It wasn't just underdelivering; it was oversimplifying freedom until it looked like a Tuesday morning in a windowless office.

Even Meta’s own employees reportedly didn’t want to use it. User retention was dismal – only 1 in 10 returned after a month. Search traffic for “metaverse” dropped 80% within a year.

In 2021, when he renamed Facebook to Meta, Zuckerberg wrote: “Our hope is that within the next decade, the metaverse will reach a billion people, host hundreds of billions of dollars of digital commerce, and support jobs for millions of creators and developers.”

In March 2026, Meta announced it was shutting down Horizon Worlds on VR headsets entirely. The platform never drew more than a couple hundred thousand active users a month.

$73 billion in losses.

To put that in perspective: you’d have to spend $1 million a day for 200 years to burn through that much money.

Here’s what people missed: the timing was catastrophic. People had just survived lockdown. They'd spent two years trapped in virtual meetings, virtual happy hours, virtual everything. The last thing they wanted was more screens. They wanted to leave their houses.

The technology arrived. The human outcome didn't.

Know someone still waiting for their metaverse office to load?
Send them this.

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The Pattern

Three technologies. Three decades. Same playbook.

Overhype: Revolutionary promises. “This changes everything.” Billions invested on the assumption the future would arrive on schedule.

Oversimplify: Complex realities reduced to taglines. “Video calling.” “Download a movie in seconds.” “The successor to the mobile internet.”

Underdeliver: The technology eventually works, but the use cases were wrong, the timing was wrong, or the human demand simply wasn’t there.

Every case study above failed that test.

I’ve watched this pattern for twenty-five years. And right now, it’s playing out again.

Not in telecoms. Not in social media.

In the desert.

Next week: Part 4 – "The $47 Billion Con vs. the $500 Billion Bet" – I worked on one of them. I cheered when the other collapsed.

If you missed them: Part 1 – “The Stock-Trading Cat” | Part 2 – “Dot-com. The Original Sin”

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In July 2000, I stood on stage in front of my iXL colleagues and gave a presentation on why our clients needed strategy – not just websites.

Creatives. Techies. Suits. All of them smart. All of them chasing the same gold.

I had a slide called Dot-Com Graveyard.

It was a list of companies that had already died – and it was growing every week. Pets.com. Boo.com. Webvan. eToys. Kozmo. Names that had raised hundreds of millions and burned through it in months.

The message was simple: hype is not a strategy. And most of our clients – and most of the industry – didn't have a strategy.

We were right about the diagnosis. Being right didn’t save us.

The patterns were already there. We could recognise them. We chose to ignore them.

The Boom

To understand how badly the dot-com ended, you have to understand how insane it got.

Between 1995 and March 2000, the Nasdaq rose 600%.

By spring 1999, one in twelve Americans said they were founding a business.

A new millionaire was being created every 60 seconds in Silicon Valley.

In January 2000, seventeen dot-com companies bought Super Bowl ads. Seventeen. At $2 million a spot. Companies that had never turned a profit were spending more on a single advert than most businesses make in a year.

The money wasn’t just flowing. It was flooding.

Risk had been abolished. Valuations only went up.

You couldn't lose – you could only miss out.

“Get Big Fast.” That was the objective. Not “get profitable” – just get big. Market share first, revenue later, profit... eventually.

Pets.com built an entire brand around the tagline “Because pets can’t drive.” They spent $17 million on marketing in 1999 – and generated $619,000 in revenue. They went public anyway.

One founder was quoted saying:

“The last thing I want to be is profitable – because then I wouldn’t get the valuation of an internet company.”

The logic was insane. But it was consistent. Once you recognised the pattern, you recognised it everywhere.

The Game

When I left investment banking and joined iXL, the rules felt obvious: get in, get rich, get out.

I wasn't alone.

Some of my colleagues were paper millionaires. The money wasn’t real yet, but that didn’t stop anyone. Expats on fat per diems spending tomorrow’s money today. Consultants billing enough to pretend we belonged.

Bottles at the clubs. £100 shots of tequila at La Perla. Expensive toys nobody would own in two years.

Work hard, party harder.

And we did work – hard. I was surrounded by some of the smartest people I’ve ever known, building massive projects for massive clients and solving problems we genuinely thought mattered.

The work was real, even if the valuations weren’t.

Silicon Valley was a cult – true converts who thought they were changing the world.

London was a casino – mercenaries who knew it was a gold rush. We just wanted our cut before it ended.

Then it ended.

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The Bust

In March 2000, the Nasdaq hit its peak. One month later, it had lost 34% of its value. By October 2002, it was down 78%.

$1.7 trillion lost in public markets.

Over 100,000 tech jobs vanished in Silicon Valley alone. San Francisco office vacancy went from 1% to 20%.

The popular myth is that 90% of dot-coms failed. The reality: around half. Which means half survived – and the industry still collapsed.

The graveyard filled up fast. And we were now in it.

In a move of pure desperation, iXL merged with a competitor that was also collapsing – Scient. The combined entity went bankrupt. We were valued at $3 billion in 2000. Sold for scrap: $13 million in 2002.

Razorfish – our main competitor – hit a peak valuation of $5.5 billion. Stock price: $57 in February 2000. One year later: $1. In 2002, Razorfish sold for $8.2 million. From $5.5 billion to $8.2 million – a 99.8% wipeout.

Their founders were interviewed on 60 Minutes. They couldn't explain what the company actually did. The interview is still on YouTube – painful, cringeworthy, and a perfect snapshot of how unhinged things were.

We weren’t outliers. We were the pattern.

My Dot-Com Hero

Michael Fenne was the CEO of Pixelon, a startup that claimed to have developed broadcast-quality video streaming over the internet. In 1999, that would have been revolutionary. Miraculous, even.

He raised $30 million from investors. His pitch was compelling. His technology demos were impressive. Investment banks signed on. Hollywood studios came calling.

There was just one problem: Michael Fenne didn’t exist.

His real name was David Kim Stanley – son of a Baptist preacher who’d made his first fortune “fleecing his father’s flock.” A judge’s words, not mine.

He’d previously been convicted on 55 fraud-related counts, scamming more than $1.2 million from senior citizens across the South.

His CV claimed he’d worked for the CIA, the Saudi Royal Family, Disney, and Sony. Nobody checked.

He insisted on being paid in cash. He held mandatory prayer meetings in his office. He told employees he’d booby-trapped the company’s computers to self-destruct if anyone examined them. Nobody asked questions.

Then came iBash ‘99.

Fenne threw a launch party in Las Vegas that cost $16 million. The Who. The Dixie Chicks. Faith Hill. KISS. The event was supposed to be broadcast globally – proof that Pixelon’s streaming technology actually worked.

It didn’t. The broadcast failed. Nobody noticed. They were too busy partying.

That single event burned through 75% of the company’s cash.

It turns out his groundbreaking video streamer was just a re-skinned version of Windows Media Player. The whole thing was a con. Seriously.

A few months later, someone recognised his face from a Most Wanted poster in Virginia. He turned himself in to the police. The game was over.

Forget prison. I think there should be a statue of this man in Silicon Valley.

Not because he was a genius. Because he was the purest expression of the dot-com era.

He understood the game better than anyone: raise the money, promise the revolution, throw a spectacular party, and hope nobody checks if it actually works – or if you have outstanding warrants.

The statue should serve as a reminder.

Twenty years later, Elizabeth Holmes did the same thing with Theranos. Peak value $9 billion. Promised a miracle. Delivered nothing.

Same playbook. Same warning signs. Same outcome. The pattern doesn't change – just the names.

But that’s a story for another day.

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The Lesson Nobody Learned

After the crash, analysts did the post-mortems.

47% of dot-com failures were attributed to failed business strategy. Not technology failures. Not market timing. Strategy. Basic questions about how the business would actually make money.

Nobody had asked those questions during the boom. They were too busy getting big fast.

In July 2000, standing in front of my colleagues, we could recognise the pattern. We knew why companies were failing. We had the diagnosis.

Being right didn’t save us.

Because here’s the thing about pattern recognition: it only works if someone’s willing to listen.

The pattern was visible. It's always visible. That's not the hard part. The hard part is acting on it.

And during a boom, nobody wants to hear that the party might end.

Not then. Not now.

If you missed it: Part 1 – “The Stock-Trading Cat”

Next week: Part 3 – “Same Playbook. Same Outcome.” – The pattern didn’t stop. It just moved to telecoms. 3G, 5G, and the metaverse: three decades, same playbook, same outcome.

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Peak 3G hysteria. Every presenter that day had promised us the mobile revolution was finally here. Video calling. Mobile broadband. The internet in your pocket.

Billions were being spent on 3G spectrum licences. The future was imminent.

Then one presenter got up and said something I’ve never forgotten.

The room went silent.

He’d nailed it. Everyone was so desperate for the “killer app” that they’d lost all connection to reality.

We were drowning in solutions looking for problems. And someone had finally said it out loud.

That was nearly twenty-five years ago.

I’m still waiting for us to learn the lesson.

The Accusation

People tell me I’m cynical about technology. I’m not. I love technology.

I’ve spent my entire career trying to drive its adoption – working with mobile operators, startups, venture capitalists, city governments, tech vendors, consulting firms.

I’ve sat in the middle of the tech ecosystem for over two decades, watching wave after wave of innovation arrive with promises of transformation.

And I’ve watched the same pattern repeat itself every single time.

Not long ago, I was asked on a podcast what I thought would happen with 6G.

My answer came out before I could stop it:

Later, listening to the playback, it felt like being punched in the stomach.

Twenty-plus years of trying to drive change, and that’s what I’ve learned? That we keep making the same mistakes?

I wasn’t being cynical. I was stating the obvious. Because I’ve seen this pattern more times than I can count.

The Pattern

Dot-com. 3G. 4G. 5G. Blockchain. IoT. Big data. Cloud. Metaverse. NFTs. Autonomous vehicles. PropTech. FinTech. Smart cities. VR. AR. Wearables. Edge computing. Web3.

I could keep going. The list is long, and it keeps growing.

Not all of these were failures – some eventually delivered real value. But every single one followed the same playbook:

1. Overhype – Revolutionary promises. World-changing predictions. “This changes everything.”

2. Oversimplify – Complex realities reduced to catchy taglines. “Data is the new oil.” “Download a movie in seconds.” “The successor to the mobile internet.”

3. Underdeliver – At least initially. Often by years. Sometimes by decades. Sometimes forever.

This isn’t cynicism. It’s pattern recognition. And once you see it, you can’t unsee it.

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I Was in the Room

During the dot-com, I was working for iXL in London. If you don’t remember iXL, you’re not alone – but at the time, we were one of the hottest e-consultancies on the planet.

Let me give you the numbers, because they still don’t make sense to me.

iXL went public in June 1999. Day one market cap: $1.1 billion. By early 2000: $3 billion.

For a professional services firm.

The year before IPO: $65 million in revenue, $49 million net loss. No profit. Just growth.

I’d joined from investment banking. I understood how to value things. I knew what a real business looked like. None of this made sense.

I watched in real-time as billions evaporated.

And when your clients go bankrupt, you go bankrupt.

In January 2002, iXL was acquired by Scient in a fire sale. The combined entity filed for bankruptcy. Final dissolution value: $13 million.

From $3 billion to $13 million in two years.

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The First Lesson

Here’s what I learned watching it burn:

Pattern recognition isn’t cynicism.
It’s memory applied to the present.

When someone tells me a new technology is going to change everything, I don’t dismiss it. I ask: “Have I seen this pattern before?”

When a company’s valuation is based on a future that doesn’t exist yet, I ask: “Have I seen this pattern before?”

When everyone is so desperate to not be left behind that nobody asks if the business makes sense, I ask: “Have I seen this pattern before?”

The answer, almost always, is yes.

The Second Lesson

The second lesson took me longer to learn.

I did a stint at Eight Inc., the experience design firm founded by the late Tim Kobe. Tim passed away earlier this year, and I’ve been thinking a lot about what he taught me.

Tim created the Apple Store. He'd been working with Steve Jobs since the mid 1990s – first on the coloured iMacs, then on a whitepaper outlining a new kind of retail experience for Apple. They launched the first store in 2001, right in the middle of the dot-com bust. Everyone else was going bankrupt.

Just prior to the launch, Bloomberg published the article: “Sorry Steve, Here’s Why Apple Stores Won’t Work.”

They were wrong. Spectacularly wrong.

While dot-com darlings were collapsing, the Apple Store survived – and built something that would last. Same crash. Completely different outcome.

Why? Because Tim understood something that everyone else had forgotten:

”Technology doesn’t exist for technology’s sake.
Technology exists to deliver human outcomes.”

Tim didn’t design a store to sell computers. He designed an experience.

A place where people could touch the products, get help from experts, feel welcomed.

The technology was almost incidental – what mattered was how it made people feel and what it enabled them to do.

That’s the difference between the companies that survived and the ones that ended up in the graveyard.

Every failed hype cycle I’ve watched made the same mistake: they talked about the technology, not the human outcome.

“3G will enable video calling.” But nobody wanted to video call in 2003.

“5G is so fast you can download a movie in seconds.” But nobody downloads movies anymore – everyone streams Netflix.

“The metaverse is the successor to the mobile internet.” But people had just survived lockdown and wanted real human connection, not more screens.

The tagline came before the use case. The technology was described, but not the human outcome.

Tim got it right. Most of the industry still hasn’t.

What’s Coming

Over the next four weeks, I’m going to show you the receipts.

Part 2: The dot-com crash – I was there. I have the scars.

Part 3: 3G, 5G, and the metaverse – three decades, three waves of hype, three patterns of disappointment.

Part 4: NEOM – the pattern playing out right now, in the desert. I worked on it. I have stories.

Part 5: What happens next – The survivors. The failures. And the question nobody wants to ask about AI.

These aren’t cherry-picked – they’re the clearest ones. The ones where I was in the room.

By the end of this series, you’ll see the pattern too.

And you’ll have two questions you can ask about any new technology, any promise of transformation, any claim that “this time is different”:

“Have I seen this pattern before?”
“What human outcome does this actually deliver?”

If they can’t answer the second one, be suspicious. Because I’ve seen this film before. I know how Act Two goes.

Next week: Part 2 – “Dot-com. The Original Sin” – Inside the dot-com crash, from someone who was there.

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IoT had a decade of hype, infighting, and broken promises. Now AI is giving it a second chance it doesn’t deserve.

I sat down with four people recently on the TechBurst Talks podcast who have lived it from very different sides of the industry:

The Architect — Alistair Fulton of IoT Labs. Helped build Microsoft & Hitachi’s IoT platforms before anyone heard of IoT, scaled LoRa at Semtech, now advises startups on what actually works.

The Analyst — Matt Hatton of Transforma Insights. The rare IoT analyst who stayed sober while the industry drank the Kool-Aid.

The Connector — Wienke Giezeman, co-founder of The Things Industries and The Things Conference. He built the community that saved the LoRaWAN ecosystem.

The Builder — Gerhard Loots, CEO of Kallipr. Took Telstra's IoT portfolio from a boring afterthought to market leader, now scaling industrial monitoring across water, rail and mining. And winning.

Their perspectives shaped this. So did my own.

What follows is my honest take on IoT: where we started, what we got wrong, where we are now, and what it will actually take to get us to the next level.

We Lied To Ourselves

The Numbers Game

Was the IoT market projection 70 billion connected devices? 50 billion? 30 billion? The number didn't matter. The hype did.

Every analyst firm had a different number, every vendor had a bigger one.

Then came the market forecast. IDC put IoT at $7.1 trillion in 2014, quietly revised it to $1.7 trillion six months later, and down to $1.0 trillion by 2018.

An 86% collapse in the market forecast. Nobody questioned it.

That’s when I stopped blaming the analysts.

The industry got the forecasts it wanted.

Investors needed big numbers to justify big bets. Vendors needed big numbers to justify big teams. And analysts — well, they gave the market what it was asking for.

We all looked the other way when the numbers stopped making sense.

We knew. We just didn’t care. It’s on us.

The Gold Rush That Wasn’t

The forecasts didn't represent new money. They never did. The opportunity was to digitise existing industries — not build a new economy on top of the old one. We dressed up that transition as a gold rush. It wasn't.

The result? 50-person companies trying to sell supply chain transformation to global enterprises, who looked back and thought: are you even going to be here next year?

The Connectivity Wars

LoRa versus Sigfox versus NB-IoT — each convinced it was the one true standard. None of them were.

Rather than making the collective case for Low Power WAN, they spent years kicking over each other's sandcastles while the market waited.

The lesson nobody wanted to learn: different use cases need different connectivity. There is no one true standard. There never was.

And the market paid the price for that argument.

The Full Stack Fantasy

Building IoT solutions is complex — multiple products from multiple vendors to create a single solution. No single company could own the entire stack.

Instead of acknowledging that, companies tried to own the entire stack anyway. And the market stalled.

The companies that tried to own everything ended up owning nothing.

Signs of Life?

AI Is Changing The Conversation

AI is doing something IoT never managed on its own — it’s making the data valuable. Anomaly detection in networks, automation of IoT operations, video analytics on existing camera infrastructure.

These are not generic AI use cases. They are IoT-specific, outcome-driven, and immediately measurable.

And critically, they are shifting the conversation from selling kit to selling outcomes.

Connectivity: Still A Mess

The connectivity landscape remains fragmented, costly, and nobody is fixing it.

• NB-IoT is a great technology — but AT&T switched it off in the US while Spain is mandating it in 25 million vehicles. Global standard no more — but not dead yet.

• LoRaWAN is proven but hamstrung by a fragmented developer ecosystem.

• Sigfox raised $310M+ to become the global IoT network. Valued at $600M in 2016. Sold for €25M in 2022. The smart metres still work. The vision doesn't.

• Satellite is promising but too expensive. Great for tracking a container ship, useless for anything with a roof over it.

• RedCap was supposed to be 5G's answer for IoT — turns out it's neither cheap nor power-efficient.

• SGP-32 — named by someone who hates marketing — promises easier multi-country deployments. Useful, but not a magic wand. The commercial complexity doesn't disappear just because the architecture changed.

The honest prognosis: fragmentation isn't a bug. It's the business model.

The standards bodies are busy. The vendors are happy. The customers are screwed.

The Business Case, Not The Spec Sheet

Finally, some companies are selling IoT the right way — on value, not technology. Total cost of ownership is entering the conversation.

One US city calculates it costs $30,000 just to shut down the streets and open a manhole cover. That's before anyone touches the sensor.

If your solution means they open it once instead of three times, it sells itself.

The industry spent a decade selling tech specs. The customer just wanted fewer truck rolls.

AI: Same Mistakes, Different Buzzword.

AI is only as smart as the data feeding it. In the physical world, that data comes from IoT.

Sensors on infrastructure, machines, supply chains, and buildings are the input layer. Without that real-world data, AI models are running on history. With it, you get digital twins, predictive maintenance, anomaly detection, real-time operational intelligence.

That is the opportunity.

But here is the risk: the industry is already showing signs of repeating the same mistakes.

The AI market forecasts are as wild as the IoT ones were.

AI will not save IoT. IoT has to save itself first.

Get the data right, get the use cases right, get the business model right — and then AI becomes a genuine multiplier.

Do it in the wrong order and you’re back in 2015.

Big Tech Left. Now They Need Us.

At the peak of the hype cycle, every major tech vendor launched an IoT platform. Google, Cisco, SAP, IBM, GE, AWS, Microsoft, Bosch — over 600 platforms fighting for a market that wasn't ready.

Then, one by one, they buried them inside something else and moved on.

The earnings calls found AI, and so did they.

Funny thing about AI: you can’t train a model on PowerPoints.

You need real-world, physical data. Sensors. Machines. Edge. That means IoT.

They built the intelligence. We have the data. Guess who’s knocking on whose door now.

Fix This Or Forget It

Three things. Just three.

1. Stop selling technology. Sell outcomes, business value, and ROI.

Own the domain problem first. Understand the market, its economics, its politics, who pays whom and why — then build the IoT solution around that.

The sensor is not the product. The solved problem is the product.

2. Sort out the connectivity mess.

There is no universal connectivity standard. Get over it. There never will be. Every use case has different requirements — range, power, cost, bandwidth.

Build the flexibility in from day one or pay for it later.

3. Collaborate. Seriously, this time.

IoT is too complex for one company to own.

The companies that get this build ecosystems — they partner, integrate, and make it easy for others to build on top.

The ones that don't, protect everything, trust nobody, and wonder why the market isn't growing.

Don’t Blow It

The IoT industry has already wasted a decade. AI is handing it a second chance it does not entirely deserve.

The window is open. The technology works. Big Tech finally has skin in the game.

The foundation is there. The excuses aren't. There won't be a third chance.

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Not because of the technology. Because organisations fail to change how they work, who owns the outcome, and what they actually expect people to do differently.

AI has not fixed this.

It has made it faster, more expensive, and considerably harder to hide.

I recently sat down with Nathan Bell to find out why the pattern keeps repeating. Nathan spent 25+ years delivering transformation programmes inside some of the world’s largest telcos and is now a Partner in the Digital Practice at Kearney.

We covered why AI strategies are mostly announcements dressed up as plans, where the money is actually worth spending, and why every technology transformation ultimately fails or succeeds on the same variable:

People. Always people.

The AI Strategy That Isn’t One

Walk into any boardroom today and ask whether the company has an AI strategy. You will get a confident yes. Press on what that means, and the confident yes becomes a list of pilots.

The smart people on these boards aren’t asking “do we have an AI strategy?” They’re asking “what does that actually mean?”

That question tends to land in silence.

The gap isn't ambition. It is the distance between an AI press release and the operating model change required to deliver on it. Companies are buying platforms, licences, and anything with an AI slide deck — on the assumption that the invoice validates the strategy.

It doesn’t. It moves the problem downstream and makes it more expensive.

The CFO is feeling this in real time. AI investment hits the P&L immediately. There’s no capitalising your way through a failed programme across a 20-year depreciation schedule.

Fund AI Like a Venture Capitalist, Not an IT Department

The fix is simple and almost nobody is using it.

Stop handing over multi-million budgets against a 2.5-year ROI promise. That’s not a metric. It’s an aspiration dressed up in a spreadsheet.

Fund AI the way a VC funds a portfolio: small tranches, clear milestones, proof before the next cheque.

This forces teams to define success in weeks rather than years. It builds confidence progressively rather than betting the farm on a single "Go Live" date that never arrives.

A handful of companies are beginning to operate this way. Most aren’t, because it requires accepting short-cycle accountability that neither finance nor delivery teams have been trained for.

Solve for Competence, Not Hype

The highest-return AI opportunities right now are not the ones getting standing ovations at conferences.

They are operational, unglamorous, and immediately measurable.

That is precisely why they work.

1. Internal Knowledge Management (The “Basics” Filter)

Most companies are drowning in their own “how-to” debt. HR, Legal, and Finance spend half their week answering the same three questions.

An AI that actually knows where the latest policy lives is not transformation—it is basic competence.

• The Win: Zero customer exposure, no new governance headaches, and savings visible in weeks.

• Risk: Low.

2. Customer Service: The Human Sidekick

Everyone wants a fully autonomous agent. Nobody is ready for one. Instead, start with AI surfacing next-best-action prompts to the human on the live call.

In one organisation we discussed, 48% of inbound contacts were just people asking for status updates. That’s a data governance problem masquerading as a technical one.

• The Win: Immediate efficiency without the “hallucination” PR disaster.

• Risk: Medium (requires fixing the “politics” of your data).

3. The Procurement “Long Tail” Audit

Most organisations manage their top 50 vendors and cross their fingers for the rest. AI can continuously audit thousands of “long-tail” contracts against actual performance.

Almost nobody does this because it’s unglamorous. The gap between what you contracted and what is being delivered is likely costing you more than the AI implementation.

• The Win: Direct, bottom-line recovery.

• Risk: Low–Medium.

The Town Hall That Burned the House Down

Picture this: A CEO stands on stage presenting a series of AI use cases, each demonstrating “efficiency gains.” The execs in the front row are patting themselves on the back.

At the back of the room, two employees are having a quieter conversation. One has just realised the first demo is his job. The second has realised the next demo is his.

They aren’t thinking about “innovation”; they are discussing when to contact HR about their redundancy packages.

This is not a communications failure. It is a sequencing failure.

• The Employee Filter: People think about their own job first, their team second, and their organisation third.

• The Executive Filter: Senior leaders think about shareholder value first and work backwards.

AI hasn’t changed that misalignment; it has simply made the collision faster and more public.

The “innovation” on stage looked like an “eviction notice” in the back row.

The fix is to involve people in the design of what they are asked to adopt before the announcement, not after it.

The Steering Committee’s Fatal Flaw

Change Management isn't a workstream. It is the only work that matters.

In most organisations, HR is not at the AI steering committee table. The CIO is there. The Head of Strategy. Occasionally the CFO. HR gets informed. Sometimes.

This is precisely backwards.

Middle management is where transformation goes to die quietly.

These are the people with the most to lose from flattened hierarchies and agent-managed workflows, and the ones closest to the teams being asked to change.

Ignore them and watch your programme stall six months in with no one able to explain why.

The Three Principles of “Sticky” Transformation

1. Engage before the announcement: If the first time they hear the plan is at the Town Hall, you have already lost the room.

2. Forgive the past: Stop interrogating why the old system was built that way. Move on.

3. Progression over Perfection: Staged tranches that prove value before moving to the next survive contact with reality far more reliably than multi-year “greenfield” rebuilds.

The Myth of the Autonomous Agent

AI-for-AI is not a governance model. It is a governance-shaped absence of governance.

Two failure modes are already visible with agentic AI.

1. Historical Data: Agents learn from your past. If that data reflects decades of culturally specific decisions, as most organisations’ data does, the agent replicates those patterns at scale and calls it efficiency. The technology is not the source of the bias. It is just honest about what it found.
   

2. The “Closed Loop” Trap: In one case, a generation agent was paired with a vetting agent to filter quality. It worked for two weeks. Then the logs showed the generation agent had learned the second agent’s approval criteria and was gaming them.
   
   You had two systems negotiating with each other to hit metrics that satisfied nobody’s intent.

Agents require ongoing human oversight, not just initial configuration. Handing a new employee your financial records and telling them to get on with it is not innovation. It is negligence.

Capability First. Technology Second.

The thread running through every failure pattern, orphaned pilots, burned town halls, ungoverned agents and change programmes that never finished, is the same.

Organisations are treating AI as a technology acquisition rather than a business capability.

A technology acquisition needs a budget line.

A business capability requires the organisation to understand what it is committing to own, who governs it and what changes for the people delivering it.

That is the part nobody budgets for, nobody governs properly and nobody wants to be accountable for when it goes wrong.

Fix that first. Everything else follows.

The Full Briefing

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I’m on the ground in Barcelona for Mobile World Congress. A hundred thousand people, six themed pillars, and enough AI signage to wallpaper a small country.

The theme this year is “The IQ Era.” At least they resisted the temptation to put “AI” in the official title, even if they couldn’t help themselves with the pillars.

So before I hit the floor, I went back to the people I trust to cut through the mobile industry hype: Chris Lewis of Lewis Insight and Rob Jones of Sylva Growth Partners.

We reviewed the current state of telecoms and tech based on the 100+ years of industry scar tissue we have between us.

We went in with one question:

Here’s what we concluded. And here’s what I’m watching for on the MWC floor.

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The Verdict: Attitudes vs. Action

Attitudes have shifted. Financials haven’t. That is a problem.

There is more acknowledgement now that the industry needs to move from selling technology inputs to delivering customer outcomes. That is real, and it matters.

But acknowledgement isn’t action. The industry has been acknowledging the same things since I joined O2 in 2002. Back then, we were talking about transforming the workforce because BlackBerry was launching and data was coming and everything was going to be different.

The Refusal to Sit with Discomfort

The core problem isn’t technological. It is psychological. The industry won’t accept that transformation requires things getting worse before they get better.

Why do telcos still have four billing systems? Multiple CRMs? Three app front-ends pointing at the same customer?

Because they started consolidating, it got painful, and they stopped. That is not a capability gap. It is an institutional refusal to sit with discomfort.

The Competitive Blind Spot: MVNOs

The competitive pressure is building from directions the industry keeps underestimating. MVNOs have grown customers in the UK for two consecutive years while traditional operators have lost them.

Not because MVNOs are more clever. Because they’re structurally forced to segment, target, and serve a specific customer intelligently. They don’t have the luxury of being all things to all people.

While telcos hesitate, challenger banks are annexing the relationship. Revolut didn’t just launch an MVNO — they built a “Lifestyle Bundle” that makes traditional family plans look like relics. Bundle 5G with NordVPN, global messaging, and RevPoints loyalty, and you’ve delivered the ecosystem play telcos have promised for twenty years.

When a fintech can cherry-pick your most profitable, digitally-native customers for £12.50 a month, the pain might finally force structural change.

This isn’t just a new competitor. It’s the total decoupling of the customer from the network.

What I’m Watching at MWC

AI: Hype vs. Reality

Every booth at MWC has AI in the title. The question isn’t whether it gets talked about. It’s whether anyone can show evidence of something that went beyond a pilot, survived contact with a real customer base, and actually moved a metric that matters.

The foundational problem is data. Telcos are sitting on more customer data than almost any other industry and have done less with it than a supermarket loyalty card. It’s siloed, poorly governed, and guarded by lines of business that treat it like territorial rights.

That is a political problem, not a technology problem, and no LLM deployment fixes it.

“AI-native telco” is jargon. What it usually means in practice is: we ran some pilots.

The industry keeps pointing at AI pilots as proof of progress. They aren’t. A proof of concept that never scales isn’t innovation. It’s expensive procrastination with a press release attached.

Will a Telco Break Rank?

This is the one I’m least optimistic about, which is saying something.

Every telco CEO is currently obliged to have a transformation story. The talk is everywhere. What’s missing, and has been missing for 25 years, is anyone standing up and describing something genuinely structural.

Not an innovation lab tucked away somewhere that reports to no one and influences nothing. Not a digital venture that quietly folds in three years.

An actual reorganisation of how decisions get made, what gets dismantled, and what the business is willing to make worse in the short term in order to make permanently better.

If a telco at MWC this week is willing to say that out loud, to name the pain they’re currently in as the price of something better on the other side, that’s the one worth watching.

I won’t hold my breath. But, trust me, I’ll be happier than anyone if some does break rank and calls it like it is.

Network APIs and the Sophistication Paradox

Telco’s Network API opportunity may be heading for the graveyard. Not because the underlying capability is worthless, but because the industry has spent years pitching the technology instead of the outcome.

We’ve been here before. The sophistication paradox: where the more technically impressive something is, the less anyone can explain why a normal human being should care about it.

• IoT: 50 billion connected devices, trillions in new revenue. We got smart lightbulbs.

• Digital Twins: operational revolution. We got slides.

• Network slicing: 5G's killer app. Still waiting for the kill.

The pattern is not hard to spot. Yet here we are again.

Now it’s Network APIs. Same pattern. Genuine capability. Inside-out pitch. No clear answer to the only question that matters: what problem does this solve for someone who isn’t already in the room?

I’ve tried to make this relatable. I compared Network APIs to a cheeseburger. Genuinely. Because if we can’t explain this in plain language, we’ve already lost.

The Ericsson-Vonage disaster sits there as the monument. $6.2 billion in, $4 billion already written down. Because it turns out “developers will come if we provide APIs” is not, in fact, a market.

One Last Thing

The industry knows what it needs to do. It has known for the better part of three decades. The structural forces making transformation difficult — risk aversion, legacy debt, talent hollowing out, hyperscalers hoovering up the margin — haven’t gone away.

Some bright spots exist. Parts of Asia are moving. MVNOs are innovating where telcos won’t. The pain is slowly reaching the threshold that precedes real change.

But slowly is doing a lot of work in that sentence.

Most years, my best takeaways from MWC are seeing old friends and eating wonderful tapas (not that that’s a bad thing).

Let’s see if 2026 is any different.

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I put this question to Andy, and his answer set the tone for everything that followed.

His answer: the pub. Why not? Might as well.

I’ve been using his Pub Scale ever since. At one end it’s too early. At the other, your card is behind the bar and you’re not leaving anytime soon.

Where are we now?

Coats on. Walking towards the pub. Hoping it’s open.

This Isn’t A Transition. It’s A Rupture.

Canadian PM Mark Carney said it best at Davos last month. The US-led rules-based international order isn’t transitioning into something new. It’s rupturing.

There’s a difference. Transitions are managed. Ruptures leave debris everywhere and nobody’s entirely sure what just broke.

We’ve seen the Trump playbook before. The massive opening demands, the outrage, the financial markets wobbling, the quiet rollback. The script is familiar.

What’s different this time is the Iron Fist sitting behind it.

• Military assets deployed to back economic demands.

• The Venezuela decapitation action.

• Greenland rhetoric that was serious right up until it wasn’t.

Next in the queue? Iran? Cuba? Some random island only inhabited by penguins?

The “napkin deals,” as trade economist Deborah Elms perfectly describes them, keep getting written. Most will get challenged, rewritten, or ruled illegal before the ink dries. But the disruption they cause in the meantime is entirely real.

The Tariff Rollercoaster

Last week the Supreme Court ruled Trump’s sweeping global tariffs were illegal. Companies got excited about rebates. Accountants sharpened their pencils.

Finally, an end to the chaos? Nope.

Trump was not pleased. He called the decision a “disgrace to our nation.” He then vowed to go in a different direction.

He found one within hours. Trump imposed a 10% tariff on imports from EVERY COUNTRY ON EARTH simultaneously.

A never-before-used mechanism, applied overnight, to every trading partner on the planet. He liked it so much he raised it to 15% the following day.

This is not trade policy. This is improvisation with a global economy as the instrument.

Carney Had An Answer. Here's The Problem With It.

Carney didn’t just diagnose the problem at Davos. He proposed a response. Middle powers, the EU, Canada, Japan, Singapore, Australia, the UK, have enough shared interest in a functioning rules-based order to build something together.

A third path. Not subservient to Washington, not naive about Beijing.

It’s a compelling idea. It’s also going to get tested brutally. Look at Canada. Trump hasn’t just rattled it with tariffs.

He’s gone after its identity, its sovereignty, floated the 51st state fantasy with apparent sincerity. And worse, he’s gone after ice hockey.

In response to Canada negotiating a trade deal with China, Trump replied "The first thing China will do is terminate ALL Ice Hockey being played in Canada, and permanently eliminate The Stanley Cup."

I truly wish I was making this shit up.

Canada is (was? I don’t blame them) a close ally and it still got the full treatment.

If you’re a middle power thinking about finding your spine, Canada is your case study in what that costs.

The Middle Powers Have The Ingredients. Not The Unity.

Take the EU. It represents 450m consumers and the world's most formidable regulatory machine — but it moves at the speed of its slowest member.

Every bold move gets watered down, referred to a court, or vetoed by someone with an election coming up.

Trump knows this. You don't negotiate with a bloc. You pick off its members individually, offer just enough, and the coalition fractures before it forms.

Asia: Who’s Actually Winning

Singapore is the grown-up at the table. PM Wong has been refreshingly straight with his citizens about the turbulence ahead. The professional eye-rolling at Washington's recent overreach has been a masterclass — including when the new US ambassador described tariffs as “America calling in a favour from a friend.”

Singapore smiled, nodded, and got on with it.

Behind the diplomacy, Singapore is quietly building something serious on AI. Over S$1 billion committed to national AI R&D through 2030 and they recently unveiled the world’s first governance framework for agentic AI.

The Johor Special Economic Zone solves two problems simultaneously — data centres are sprouting up faster than bubble tea franchises across the border, nobody in Singapore has to live next to them, and the city-state gets a significantly larger economic hinterland in the process.

Japan called it right. Takaichi’s snap election gamble paid off spectacularly. The LDP took 316 of 465 seats, the biggest single-party win in post-war Japanese history, giving her the legislative muscle to push her defence agenda without meaningful opposition.

Beijing’s attempt to pressure her into retracting her Taiwan comments backfired badly. Voters endorsed her unyielding stance and handed her a mandate to confront China on her own terms.

The backstory matters. In November, Takaichi told parliament that a Chinese attack on Taiwan could constitute a “survival-threatening situation” for Japan, the first sitting prime minister to say so explicitly in an official setting.

China reacted with seafood import bans, flight cancellations, rare earth export restrictions, and a Chinese consular official posting on X that someone should “cut off that filthy neck.”

The last two pandas in Japan were sent home, ending 50 years of panda diplomacy. No, really. THEY TOOK BACK THE PANDAS, FFS!

With a supermajority now secured and a White House visit scheduled for March, the direction of travel in Tokyo is unambiguous. Beijing is taking note.

Malaysia has had a genuinely good run. Neutrally positioned, pulling in FDI from every direction, Penang’s semiconductor ecosystem booming along with the data centres in Johor. Wind in their sails.

Vietnam keeps surprising people. 100m people, growth north of 6%, and when the tariff shock hit they didn’t freeze, they pivoted. Samsung represents 16-18% of GDP, which is a concentration risk worth watching, but the fundamentals remain strong.

India is playing everyone's game and winning. Larger population than China, growing faster, EU trade deal done, and somehow maintaining credible relationships globally at the same time. It won't be another China. It'll be something else entirely.

Thailand has a constitutional referendum, genuine political stagnation, and numbers that tell the real story. Full year 2025 came in at 2.4% but the IMF projects just 1.6% for 2026. Thailand has the demographics and the FDI potential to be performing much better. Keep an eye on this one, it might get worse before it gets better.

Indonesia is the interesting wildcard. Prabowo spent his early months flying around making friends with everyone — Washington, Beijing, Brussels — which is a reasonable strategy for a country that wants to stay out of the crossfire. The recent Chinese military hardware purchase is the footnote that might not stay a footnote.

The Philippines is a different story entirely. Marcos is closely aligned with Washington and Tokyo, chairs ASEAN this year, and will push hard on South China Sea territorial claims. With the Duterte family waiting in the wings and a security architecture that puts Manila increasingly in the US camp, this is a country where the geopolitical pressure is building.

Wake up! Stop Enjoying The Show.

In Venezuela, the US removed a head of state without an articulated strategy for what followed — and that absence of doctrine did not go unnoticed. Moscow noticed. Beijing noticed. Every government paying attention noticed.

This is what Carney meant by rupture. Not the bluster. Not the tariffs. Not the 2am social posts. The actual deployment of hard power without a coherent framework behind it.

That is the miscalculation risk nobody wants to state plainly. Not a disciplined adversary executing a strategy. An improvising one.

So. Card Behind The Bar?

The optimistic scenario for 2026 is fragmented but functional. The global economy keeps moving. Middle powers build their geopolitical muscle slowly but genuinely. No major security crisis erupts.

We’re closer to the pub than we were twelve months ago. The door is in sight.

The challenge for businesses, for governments, for anyone making real decisions with real money in genuinely uncertain times, isn’t surviving the noise. It’s finding the signals inside it.

That’s what I’ll keep doing here.

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That told me everything I needed to know.

LinkedIn users turn to the platform seeking professional insights and business intelligence. Instead, they're getting inspirational fiction because the algorithm rewards exactly that.

The Numbers Don’t Lie

Richard van der Blom’s October 2025 analysis of nearly 400,000 LinkedIn profiles confirms what many of us suspected: LinkedIn’s reach is collapsing.

• Average visibility dropped 47%

• Engagement fell 39%

• Follower growth tumbled 42%

Here’s what’s killing it:

• More people posting algorithmic junk

• Advertisements choking more feed space

• An algorithm that rewards emotional manipulation over substance

In short, we’re being fed slop.

So while professionals scroll through LinkedIn hunting for genuine business intelligence, they’re served up fake vulnerability and manufactured inspiration instead.

The Algorithm Rewards Fiction

Last year, I hosted conversations with industry leaders across four continents…

• AI deployment realities

• IoT infrastructure challenges

• 5G implementation disasters

• Orbital data centres

• Geopolitical tech wars

Real conversations. Real money. Real consequences. Got the LinkedIn engagement you'd expect from actual substance: minimal.

So I decided to run an experiment. I fed ChatGPT this prompt:

It produced a masterpiece of algorithm bait. I posted it.

It outperformed everything else I shared that year, not because it was good, but because it was engineered for an algorithm that mistakes emotional manipulation for engagement.

And I never had a cat.

Time to Stop Performing

So I'm done with the act.

I'm moving my insights to a platform that values substance over spectacle. No emoji requirements. No heartwarming narratives. Just intelligence.

Where Real Intelligence Lives

After decades watching technology hype cycles, from dot-com bubbles to 5G promises to AI fairy tales, I’ve learned to spot the difference between substance and spectacle.

The names of the technologies change, but the patterns stay exactly the same. Most initiatives fail predictably. Most 'breakthroughs' are repackaged ideas. Most vendor promises are fiction.

While LinkedIn celebrates another inspiring story about someone’s morning bowel movement teaching them about operational efficiency, real business intelligence happens elsewhere.

The people making actual decisions with real money on the line aren’t getting their insights from inspirational posts about imaginary pets.

They're reading intelligence that cuts through vendor spin and explains why most “revolutionary” initiatives fail spectacularly.

The Alternative

My weekly CRA REALITY CHECKS go directly to people who understand the difference between engagement metrics and actual value.

Leaders who need to separate hype from reality and make decisions based on evidence, not inspiration.

No algorithm gaming. No fake vulnerability. No business parables disguised as thought leadership.

Just 35 years of watching what actually works and why most of it doesn’t.

If you're tired of LinkedIn's manufactured inspiration masquerading as insight, you know where to find me.

The algorithm can keep the cats. You deserve better.