What comes next
The future, argued seriously. Where today's signals lead, without the hype.
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Retention algorithms already flag employees likely to leave months before they know it themselves — and some managers act on the prediction first. This episode follows the logic of predictive HR to its uncomfortable endpoint, where a forecast becomes the cause of the thing it forecast.
Cheap, clean, near-limitless energy would transform civilization — so trace what actually changes and how quickly, and unpack why practical fusion has stayed 'thirty years away' for so long.
An exploration of the urban reorganization triggered by the decline of private car ownership, focusing on housing, commerce, and the reclamation of public space.
As AI-generated text floods the web and future models train on it, examine the risk of a feedback loop that degrades quality — and what it takes to keep genuine human knowledge findable.
A deep dive into the era of 'water bankruptcy,' exploring how the depletion of aquifers and the weaponization of rivers are reshaping global power, food security, and human migration.
Trace the knock-on effects if cultured meat becomes cheap and good: the fate of livestock farming, the freeing of enormous amounts of land, and the cultural fight over what we eat.
As convincing fakes of voices, faces, and video become trivial, what happens to evidence, journalism, courts, and democracy when we can no longer assume what we see is real.
Antibiotic resistance is rising while the pipeline of new drugs runs thin. A serious look at how routine surgery, childbirth, and infection care change if our most basic drugs fail.
The future, argued seriously. Episodes trace what actually changes if fusion works, what cities become when driving is optional, medicine after antibiotics, economies built on growth meeting falling birth rates, and what happens to human knowledge when machines write most of the internet. Where today's signals lead — without the hype, and without the doom.
Fylom episodes are researched, written, and voiced by AI. Automated checks help catch inaccuracies, but episodes aren't reviewed by a human and AI can still get things wrong. Treat them as a starting point, not a source of record — more in our accuracy disclaimer.