The Biggest AI Productivity Hack? Doing What We Should Have Done All Along

Everyone's optimising for AI right now. Writing clearer requirements. Documenting features properly. Structuring code cleanly. Maintaining READMEs. Breaking work into small, well-defined tasks. Keeping track of technical debt. It's all good stuff. It genuinely helps AI produce better output. But here's what's nagging at me: we already knew all of this was worthwhile. We knew it before AI showed up. We just never had enough reason to do it consistently. These are the practices that every engineering team has preached for years. Understand the requirements before you start coding. Do some upfront design. Write things down. Break the work into the smallest possible tasks. None of this is new. And human beings have always produced better results when these things are done well. The problem was never that the practices didn't work. It was that the feedback loop was too slow. A developer who receives well-written requirements delivers better code, but that plays out over weeks and across han