The Metaverse Was the Future. Now 1,500 People Lost Their Jobs. (+5 Prompts to Cut Through AI Hype)
Why most predictions about "the future of AI" are wishful thinking and how to think more clearly about what's actually coming
Meta just laid off 1,500 people from its Metaverse division.
According to the Wall Street Journal, the team that was supposed to build the future of work the one with avatar meetings and virtual offices is now significantly smaller.
Remember when we were told this was inevitable? That within a few years, we'd all be strapping on headsets for our morning standups?
It didn't happen.
And it's worth asking: how many of today's confident AI predictions will age the same way?
The Problem With "The Future"
Every technology cycle produces the same pattern.
A new capability emerges. Early adopters get excited. Thought leaders declare it “the future.” Companies pour billions into building that future. And then… reality intervenes.
Sometimes the technology wins. Often it doesn’t at least not in the form we were promised.
The metaverse was supposed to replace Zoom. It didn’t.
Crypto was supposed to replace banks. It didn’t.
And now we’re hearing that AI will replace lawyers, doctors, writers, developers, and half the workforce within five years. Maybe. But probably not in the way the headlines suggest.
The Future Doesn't Exist Yet
Here’s what most AI predictions get wrong: they treat the future as a destination we’re travelling toward, rather than something we’re actively building.
The future of AI isn’t written. It’s being written right now by the choices we make.
Every policy decision. Every regulatory framework. Every company that adopts AI responsibly (or recklessly). Every individual who learns to use these tools thoughtfully (or blindly).
We’re not passengers. We’re participants.
How to Think About AI Predictions
When someone tells you what AI “will” do, ask yourself:
Who benefits from this prediction? Vendors selling AI tools have an incentive to overstate capabilities. Consultants have an incentive to create urgency. Media has an incentive to write dramatic headlines.
What has to be true for this to happen? Most AI predictions assume smooth adoption, no regulatory pushback, unlimited compute, and human behaviour changing on cue. Those assumptions rarely hold.
What’s the track record? The same people who promised us the metaverse are now promising us AGI by 2027. Their confidence hasn’t earned your trust.
What Actually Matters
Instead of predicting the future, focus on what you can control:
Learn to use current AI tools well. Not the imaginary tools of 2030 — the ones that exist today.
Build judgment, not just skills. The ability to evaluate AI outputs critically will outlast any specific tool.
Stay skeptical of timelines. “Within five years” is the tech industry’s way of saying “I don’t know, but it sounds impressive.”
Watch what companies do, not what they say. Meta talked about the metaverse for years. Then they quietly laid off 1,500 people.
The Real Opportunity
The metaverse hype created winners and losers. The winners were those who waited, watched, and only invested when the value was clear. The losers were those who bought the vision before the technology delivered.
AI will be the same.
The people who benefit most won’t be the earliest adopters or the loudest believers. They’ll be the clearest thinkers the ones who separate signal from noise, capability from promise, and reality from projection.
The future of AI isn’t something to predict. It’s something to build. And every choice you make including the choice to think critically shapes what it becomes.
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FAQs
No. AI tools available today are genuinely useful. The point is to focus on current capabilities rather than speculative futures. Use what works now, build real skills, and stay skeptical of grand predictions about what’s coming in five years.
Look for predictions that are specific, testable, and come from people with a track record of accurate forecasting. Be skeptical of vague timelines (“within 5-10 years”), predictions from people selling AI products, and claims that assume perfect adoption with no friction.
AI is genuinely more useful than the metaverse was. But the pattern of overpromising is the same. The technology is real; the timelines and scope of predictions are often exaggerated. AI will transform many things just probably not as quickly or completely as the headlines suggest.
Get hands-on with current tools. Learn to evaluate AI outputs critically. Develop skills that complement AI rather than compete with it judgment, creativity, context, and relationship-building. Focus on fundamentals rather than chasing every new announcement.
Because predicting technology adoption requires understanding not just the technology, but human behavior, economics, regulation, and culture. Smart people often overestimate technical progress and underestimate adoption friction. Add financial incentives to hype, and you get confidently wrong predictions from otherwise credible sources.