Editor's Synopsis
Addy Osmani observes a recurring pattern in software development: every time we make it easier to write software, we end up writing exponentially more of it. He draws a historical parallel to when high-level programming languages replaced assembly — programmers didn't write less code, they wrote orders of magnitude more, tackling problems that would have been economically impractical before.
The implicit argument connects this historical trend to the current era of AI-assisted coding, suggesting that AI tools won't reduce the total amount of software being written but will instead unlock entirely new categories of problems worth solving. This reflects a broader economic principle known as the Jevons paradox, where increased efficiency in resource use leads to greater total consumption rather than less.