Laws of PM Teams Gartner Hype Cycle

Gartner Hype Cycle

Peak, Trough, Plateau

New technologies peak in expectation, crash into disappointment, then plateau into quiet everyday use.

Why PMs should care

The Hype Cycle isn't a physical law. It's a recurring pattern dressed up as analyst research, and the specific curve shape rarely matches any individual technology cleanly.

It's still useful, because it names two moments that working PMs need vocabulary for.

The trough of disillusionment is the most dangerous moment to kill a bet you just made. The hype is gone, the early wins didn't appear, the team is tired, and pulling the plug feels like cutting your losses. But the real learning is usually about to happen.

The slope of enlightenment is where the quiet money gets made. The tourists have left, and the remaining teams are building with realistic expectations.

Your job isn't to predict the exact timing of the curve — nobody can — but to have the right conversation at each phase, instead of having the same 'is this over-hyped?' conversation at every stage.

Example in product work

Consider the rough trajectories, with dates that will feel right to anyone who lived through them:

  • Crypto: peak around 2018, trough 2019, slope of partial enlightenment through 2020–21, second peak 2021, second trough 2022 onward.
  • Metaverse: peak 2022, trough by 2023, currently climbing back quietly as specific use cases (training, industrial digital twins) find product-market fit without the branding.
  • Generative AI: peak around late 2024, currently navigating the trough — the 'AI features' that shipped in 2024 with no user research are being quietly rolled back, while the teams that invested in evaluation infrastructure are starting to see real results.

A PM's job is to time entry and exit thoughtfully — not to be first into each peak or loudest during each trough.

What to do when you see it

Sources & further reading

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