I’ve written about three ideas that explain AI’s impact on software engineering better than the Jevons’ Paradox framing that dominates the discourse.

Solow’s Paradox explains why returns are unevenly distributed: the technology works but organisational restructuring takes time, so some teams capture value quickly while others see nothing. Braess’s Paradox explains why faster code generation doesn’t mean faster delivery: local speedups create congestion elsewhere. And Bainbridge’s Ironies of Automation explain why engineers feel like they’re working harder: hand the routine work to agents and every remaining task is a difficult decision.

Three explanations at different scales, each revealing what the others miss. Together they point to a way through.

Read the full post on the JUXT blog.