Remember when NFTs were going to revolutionise art, gaming, real estate, and identity? When the metaverse was the inevitable next phase of human interaction? When every company needed a blockchain strategy?

If you bought in at the peak of any of those hype cycles, you probably regret it. The challenge isn’t identifying new technology — it’s figuring out which new technology actually matters. Here’s a framework I’ve developed for sorting signal from noise.

The Five Questions Test

When a new tech trend starts dominating headlines, I run it through five questions before deciding whether to pay attention.

1. What Problem Does It Solve?

This is the most important question, and it’s the one hype cycles consistently dodge. NFTs were a solution looking for a problem. The metaverse was an answer to a question nobody was asking. But cloud computing solved real storage and infrastructure problems. Smartphones solved real communication and access problems.

If you can’t articulate the specific problem a technology solves in one sentence, without using buzzwords, be sceptical.

2. Who’s Actually Using It (Not Who’s Investing)?

Investment money follows hype. Usage follows value. These are different things.

In 2021, billions of dollars poured into metaverse projects. But actual user numbers were embarrassingly low. Decentraland had about 30 daily active users at one point despite enormous investment.

Compare that to AI tools in 2024-2025. ChatGPT hit 100 million users within months of launch. Businesses started integrating AI almost immediately. The usage was real and growing. That’s a signal.

When evaluating a trend, look at adoption rates among regular people and real businesses, not just venture capital announcements.

3. Does It Work Without the Hype?

Strip away the conferences, the thought leadership, the breathless blog posts. Does the technology still hold up?

Cryptocurrency, for all its drama, does enable borderless transfers and programmable money. Those are real capabilities. Whether they justify the speculation is debatable, but the core technology has genuine applications.

Contrast that with Web3 social media platforms that were supposed to replace Twitter and Facebook. Without the hype, they were just worse social networks. The “decentralised” angle didn’t solve any user problem — it just made everything slower and more confusing.

4. Are the Advocates Specific or Vague?

Pay close attention to how people talk about a technology. Real innovations generate specific use cases. “We reduced customer response time by 40% using AI chatbots.” “Cloud migration saved us $200K per year in infrastructure costs.”

Hype generates vague aspirational language. “This will transform how we interact.” “It’s going to disrupt every industry.” “The possibilities are endless.” When the best anyone can offer is abstract potential, the technology probably isn’t ready.

I was chatting with AI consultants in Sydney recently who made a great point: the most promising technologies are the ones where people talk about boring, specific improvements rather than sweeping revolutions. When a trend sounds boring, it’s often because it actually works.

5. Who Benefits From You Believing the Hype?

This one requires cynicism, but healthy cynicism. When a venture capitalist says the metaverse is the future, remember they’ve invested hundreds of millions in metaverse companies. When a crypto exchange says everyone needs Bitcoin, remember they profit from transactions.

Follow the incentives. The loudest voices in any hype cycle usually have the most to gain from your participation.

Historical Patterns

Looking at past tech trends, some patterns emerge:

Real trends that survived: cloud computing, smartphones, social media, streaming video, AI/ML. These all had clear use cases, genuine user demand, and solved identifiable problems.

Hyped trends that fizzled: Google Glass, 3D printing (for consumers), NFTs (as mainstream), the metaverse, blockchain-for-everything. These generated enormous buzz but failed to find broad, sustained adoption.

Trends still in the “wait and see” category: autonomous vehicles (useful but perpetually “almost ready”), AR glasses, quantum computing (real but narrow applications so far), Web3 (some valid ideas buried under speculation).

The Gartner Hype Cycle Is Real

The Gartner Hype Cycle — that curve showing a technology peaking in hype, crashing into disillusionment, then slowly climbing toward productivity — isn’t just a chart. It’s a remarkably accurate description of how most technologies evolve.

The best time to adopt a technology is usually during the “slope of enlightenment” phase, after the hype has died down and practical applications have emerged. That’s when pricing normalises, tools mature, and best practices develop.

Being early is expensive and risky. Being late is safe but potentially costly. The sweet spot is being timely — adopting when the technology has proven itself but before it becomes the baseline expectation.

Practical Takeaways

• Don’t adopt technology because it’s trending. Adopt it because it solves a problem you actually have.
• Be suspicious of any trend that can’t demonstrate real-world results from real users.
• The more someone profits from you adopting a technology, the less you should trust their recommendation.
• Most genuinely useful technologies are boring on the surface. They just work.
• It’s okay to wait. Early adopters pay the highest price for the worst experience.

The next big tech trend is already being hyped somewhere. Run it through these questions before you open your wallet.