Picture an engineer who graduated in 1929. He walks into work with books, formulas and methods he can rely on for almost his whole career. According to an estimate published in IEEE Spectrum in 1966, the half-life of an engineering degree from the late 1920s was about 35 years.1
Someone who earned the same degree in 1960 got, by the same estimate, about a decade. Same profession. Three and a half times less time.

It has a name
It's called the half-life of knowledge. The term is attributed to the economist Fritz Machlup, who wrote about it in 1962: the time it takes until half of what you learned is no longer true, or no longer useful.2
The term comes from physics. Radioactive material loses half of itself in a fixed period of time. Knowledge behaves in a similar way. It doesn't vanish in a day. It wears down slowly, and you only notice when something stops working.

In 2012, Samuel Arbesman gave it a whole book, The Half-Life of Facts. His point: even facts that look solid get updated, at a pace you can actually track.3
And the clock is speeding up
In software engineering, the researcher Philippe Kruchten estimated in 2008 that the half-life of ideas in the field is not much more than five years.4 That's one researcher's estimate, not a measurement. But the direction is clear.
The recent numbers aren't comforting either. The World Economic Forum estimates that 39% of workers' core skills will change by 2030. In 2023 the estimate was 44%, so the pace may be leveling off, but it stays high.5
59 out of 100
workers will need to learn something new by 2030 to keep doing their jobs.
- 41 won't need significant training
- 29 will be trained in their current role
- 19 will be trained and move to a new role
- 11 will need training that won't reach them
In other words, 59 out of 100 workers will need to learn something new to keep working. And for 11 of them, by this estimate, the training won't arrive. LinkedIn estimates that 70% of the skills used in most jobs will change by 2030.6
And what doesn't expire
Not all knowledge ages at the same speed. The fundamentals hold much longer: the laws of physics the 1929 engineer learned are still true, and his math still works.
What ages fast is the layer on top: the tools, the methods, what works this year and didn't five years ago. That's where most of the change is.
It's also worth remembering that the numbers here are estimates. Kruchten presents his five years as a hypothesis, and the World Economic Forum estimates rather than measures. The conclusion is calmer than the headline suggests: the fundamentals stay, and what needs constant updating is what's built on top of them.
What you learned isn't erased. It just needs someone working with it now.
Where knowledge stays fresh
If knowledge expires, the interesting question is where it stays fresh. The answer is almost embarrassingly simple: with the people who use it.
The chef who cooks every night knows what changed in this season's ingredients. The designer who works with clients knows which tools no longer hold up. The developer knows what broke in the latest release before anyone has written about it.

A curriculum is written once and updated slowly. People who work with the knowledge update it every day, sometimes without noticing they're doing it.
Our take
The question that matters now is who you learn from.
Institutions will keep teaching the fundamentals, and that has real value. What's happening in a field right now, the shortcuts, the mistakes, the changes of the past year, is known mostly by the people inside it.
What this says about you
If you work with your knowledge every day, you hold exactly what's going stale for everyone else. What feels obvious to you, because you've done it a hundred times, is exactly the fresh knowledge this article is about.
The engineer from 1929 had 35 years to rely on what he learned. You have something better: knowledge that updates every day, because you work with it.
Sources
- IEEE Spectrum, "Technical Obsolescence", 1966. Cited in Robert Charette, "An Engineering Career: Only a Young Person's Game?", IEEE Spectrum, 2013.
- Fritz Machlup, Knowledge Production and Distribution in the United States, Princeton University Press, 1962.
- Samuel Arbesman, The Half-Life of Facts, 2012.
- Philippe Kruchten, IEEE Software, 2008.
- World Economic Forum, The Future of Jobs Report 2025, chapter 3.
- LinkedIn, Work Change Report, January 2025.



