Elezea

Mike Fisher applies the Jevons Paradox to AI: early fears of automation assume a fixed amount of work being redistributed, but work expands when constraints are removed. Radiologist numbers grew despite AI predictions—the same pattern is likely for software engineering.

Lorin Hochstein argues that AWS's "Correction of Error" framing is dangerously misleading—defects alone don't explain incidents. The same applies to product work: "fixing the bug" often misses the systemic context that made the failure surface in the first place.

A LinkedIn post about AI in interviews generated some pushback. Here's the fuller version of what I was trying to say.

Anton Zaides on shadow work in engineering—the invisible work that eats capacity and can burn out your engineers.

B2B product leaders rate themselves highly across core responsibilities, but their IC PMs disagree on every measure. The gap points to a mutual visibility problem, not just a performance one.

Daniel Parris traces how "classic rock" was invented by radio executives chasing advertising demographics, not by music fans debating what deserved the label.

A practical 30-minute guide to setting up OpenCode as a product management second brain with custom slash commands for PRD reviews, OKR checks, and idea stress-testing.

Scott H. Young examines what skills remain worth developing as AI reshapes work, finding that generalists and experienced workers may fare better than specialists and newcomers.