From T-1s to Models: Thirty Years of Building, Booms, and Lessons

I came up in technology when bandwidth hissed through copper lines and “the network” still felt like a miracle. A T-1 circuit lighting up a building was cause for celebration — a symbol that we were part of something bigger. Over the next thirty years, I watched every wave of that something: the Internet boom, the crash, the cloud rush, the mobile revolution, and now the fever dream of artificial intelligence. Each one promised transformation. Each one delivered, but never quite how we expected.

1995–2001: The Age of Connection

The late nineties were pure momentum. We weren’t chasing valuations — we were chasing connectivity. We wired schools and small offices, stretched networks across counties, and made the web usable for people who had never seen it before. Funding was fragile, but optimism was cheap.

Then came the gold rush. Every company was suddenly an Internet company. “Eyeballs” replaced revenue in the language of business, and money poured into ideas that were more concept than capability. It was exhilarating, until it wasn’t.

When the dot-com bubble burst, reality crashed into ambition. Thousands of startups disappeared, but something tangible remained: the infrastructure. The servers, the data centers, the fiber that we’d overbuilt during the mania — those became the foundation for everything that followed.

2002–2010: Rebuilding and Virtualizing

The early 2000s were quieter. We focused on stability. The survivors learned discipline: uptime mattered more than hype. We built clustered systems, learned to fail over cleanly, and treated the web as critical infrastructure instead of experiment.

Then came a new idea — cloud computing. At first it sounded like marketing fluff, but the logic was irresistible. Instead of racks and CapEx, you could rent compute on demand. It turned technology from a purchase into a service. Suddenly, small teams could build globally without waiting for hardware or budgets.

That shift changed everything — not just how we built, but how we thought about cost, agility, and ownership. The cloud didn’t just replace servers; it rewired incentives.

2010–2018: The Cloud and Platform Decade

By the 2010s, cloud had become the new normal. Startups no longer asked if they’d move to AWS or Azure — they asked how soon. Capital flowed differently: instead of building hardware, companies spent on subscriptions and scale.

Meanwhile, mobile devices and social platforms rewrote consumer behavior. Billions of people were suddenly online, all the time. Data became the new currency, and entire economies formed around attention.

This was the era when technology stopped being an industry and became the atmosphere — invisible, everywhere, assumed. The internet was no longer a destination; it was the default.

2018–2025: The Intelligence Surge

Now we stand in another acceleration — the AI boom. The energy feels familiar: the promise that this new thing will change everything, everywhere, all at once. Investment is pouring in faster than measurable results. Companies race to prove they’re “AI-enabled,” even when the ROI isn’t clear.

It’s easy to see the echoes of 1999. The same FOMO, the same faith that exponential growth will outrun physics. But there’s also a difference: this time, the infrastructure is real. We have the cloud, the compute, and the connectivity to make the ideas plausible.

What’s missing, often, is the human layer. The early Internet was about inclusion — connecting classrooms, small businesses, and communities. Today, AI is often framed in terms of efficiency — doing more with fewer people. Somewhere along the way, the story shifted from connecting people to replacing them.

Patterns That Never Die

Every tech wave follows a rhythm:

Hype → Overspend → Collapse → Integration → Maturity.

The dot-com bust paved the way for real e-commerce. The cloud boom taught enterprises how to buy flexibility instead of hardware. Mobile and social normalized digital dependency. And AI — whatever form it ultimately takes — will leave behind systems and habits that endure long after the hype cools.

But one pattern worries me. Each wave moves the center of gravity higher — from personal computers to shared servers, to global platforms, to a handful of AI models run by even fewer companies. Power keeps consolidating upward. The innovation that once felt communal now feels centralized.

Where This All Leads

Technology’s story has always been one of acceleration, but acceleration isn’t the same as progress. We’ve made it easier to deploy code than to justify its purpose, easier to automate than to explain, easier to scale than to sustain.

Still, I’m not cynical. The same energy that built dial-up networks under failed budgets is still out there — builders who care about doing things right, not just fast. The infrastructure endures because the people behind it do.

If there’s a lesson from three decades of wiring, scaling, and modernizing, it’s this: hype fades, but fundamentals persist. The next revolution — whatever follows AI — will still depend on the same quiet work that always mattered: keeping systems running, data flowing, and people connected.

Because in the end, progress isn’t about the models.

It’s about the humans behind them.

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We’ve lived through one bubble before — let’s make sure we build what lasts this time.