The age of hype cycles
If you had told me ~5 years ago that it would be possible to earn money without riding the Web 3.0 drive train, I would have genuinely doubted you.
Web 3. Blockchain. Decentralization. Crypto.
The above were the bomb, the shit, the beginning and the end of gathering wealth.
And yet here we are a few years down the road. The interest has died down and true to the word - hype cycle, the hype has died.
The grifters and the hype merchants have moved on to the next big thing. The conferences are smaller. The Twitter bios have changed. The laser eyes are mostly gone.
What’s mostly left are the people who were actually building things.
That is the thing about hype cycles. They create the illusion that a technology is either going to change everything tomorrow or disappear entirely. Reality is usually somewhere in the middle.
The internet survived the dot-com crash.
Cloud computing survived years of skepticism.
Cryptocurrency survived multiple market crashes.
And artificial intelligence will likely survive whatever comes after today’s excitement.
The pattern is remarkably consistent.
- A new technology appears
- Early adopters see potential
- Investors smell opportunity
- The media discovers a story
- Expectations become detached from reality
- Capital floods in
- Every startup suddenly adds the buzzword to its pitch deck.
Then reality arrives.
The technology turns out to be harder to implement than expected. Adoption is slower. Costs are higher. The promised revolution takes years instead of months.
People become disappointed.
Articles are written declaring the technology dead.
Investors lose interest.
Founders pivot.
The hype collapses.
And then something interesting happens.
The builders who never cared much about the hype keep building.
While everyone else is arguing online about whether a technology is over or underhyped, engineers are solving boring problems. They are improving infrastructure, fixing edge cases, reducing costs, and making products usable.
Today AI is going through the same process.
Every company is suddenly an AI company. Every presentation includes AI. Every startup founder has discovered the secret to replacing human labor with a prompt.
Maybe some of those claims will be true.
Most won’t.
That does not mean AI is a bubble. It means expectations are running ahead of reality, which is exactly what happens during every hype cycle.
The mistake people make is confusing a technology with the story being told about that technology.
The story changes every few years.
The technology usually remains.
As engineers and builders, our job is not to predict which hype cycle comes next. It is to identify the useful pieces hiding underneath the noise.
Because when the hype dies, that’s when the real work begins.
References
- Gartner Hype Cycle: https://en.wikipedia.org/wiki/Gartner_hype_cycle