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Productivity isn't writing more code: measuring good engineering in the age of AI Velocity is up. Pull requests are up. Lines of code are way up. AI has changed how software gets built, so it's tempting to conclude that the old way of measuring engineering has broken, because productivity means something different now. There's a growing chorus that argues exactly that, calling for new, AI-native metrics built for a world where agents write much of the code. Yes, AI has changed how software gets built, and it has changed where the risks sit. But what it hasn't changed is what good software

Productivity isn't writing more code: measuring good engineering in the age of AI Velocity is up. Pull requests are up. Lines of code are way up. AI has changed how software gets built, so it's tempting to conclude that the old way of measuring engineering has broken, because productivity means something different now. There's a growing chorus that argues exactly that, calling for new, AI-native metrics built for a world where agents write much of the code. Yes, AI has changed how software gets built, and it has changed where the risks sit. But what it hasn't changed is what good

Productivity isn't writing more code: measuring good engineering in the age of AI Velocity is up. Pull requests are up. Lines of code are way up. AI has changed how software gets built, so it's tempting to conclude that the old way of measuring engineering has broken, because productivity means something different now. There's a growing chorus that argues exactly that, calling for new, AI-native metrics built for a world where agents write much of the code. Yes, AI has changed how software gets built, and it has changed where the risks sit. But what it hasn't changed is what good