After automation: unmeasurable work stops being a luxury
every · x · 2026-10-01
Calum Forsyth, founder of Tanis Labs, argues AI will reshape what knowledge work gets done. His core observation: knowledge work pools wherever measurement is easy—work tied to a metric (sign-ups, load time, retention) instantly answers "how will we know it worked?" and wins resources, while big problems with names but no numbers starve.
Journalism already went through this: once pageviews made one kind of value countable, uncountable value—beats and sources cultivated over years—starved, done only by the tenured and the stubborn.
AI thrives on the measured layer. Once the machine does the measured work for everyone, there's little left to compete on there. For any firm selling expert time, once the machine does the billable work, salaries pay for work with no number attached—most firms will cut it and call it efficiency. The ones that keep paying do so for the least sentimental reason: it's where advantage can still live. Journalists, researchers, and designers who've spent years making progress without legible metrics already know how to make that case.
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