I came across the 2014 Oppezzo & Schwartz paper on Twitter this morning and went looking for the wider literature. What I found describes a pattern I had been running unconsciously for months: walking from the studio to the kitchen when stuck, a ten-minute loop to pick up my son, the dog out for a quick pee. A decade of replication, applied to AI-assisted work.
A Wharton paper gave a formal name to what I described three weeks ago: when AI thinks for you and you let it. The data is worse than I expected.
AI creates a demographic time bomb: it increases demand for senior talent while destroying the pipeline that produces it. What replaces corporate apprenticeship is something closer to Hollywood.
Keynes predicted 15-hour weeks by 2030. Gates says 2-day weeks within a decade. Meanwhile, Germany, Argentina, and Silicon Valley are legislating or normalizing 12-hour days. The paradox has a name, and it’s 161 years old.
Everyone says AI makes developers faster. My experience is the opposite: I arrive exhausted not because I wrote more code, but because I evaluated more decisions. The effort didn’t shrink. It transformed.
Three fractures in how we learn, hire, and distribute capability.
From the SPACE Era to the AI & DevEx Revolution: a necessary update.
How can you tell if a development team is working effectively and meeting its objectives on time? Some insights from scientific research.
Come si può sapere se un team di sviluppo sta lavorando in modo efficace e se sta raggiungendo i suoi obiettivi in modo tempestivo? Qualche spunto dalla ricerca scientifica.