| I love how these articles drop, and all of a sudden HN is filled with people who think engineering productivity is simple to measure. Yes, productivity implies revenue (or cost reduction), and revenue is measurable. However: 1. You spend money today to build features that drive revenue in the future, so when expenses go up rapidly today, you don’t yet have the revenue to measure. 2. It’s inherently a counterfactual consideration: you have these features completed today, using AI. You’re profitable/unprofitable. So AI is productive/unproductive, right? No. You have to estimate what you would’ve gotten done without AI, and how much revenue you would’ve had then. 3. Business is often a Red Queen’s race. If you don’t make improvements, it’s often the case that you’ll lose revenue, as competitors take advantage. 4. Most likely, AI use is a mixture of working on things that matter and people throwing shit against the wall “because it’s easy now.” Actually measuring the potential productivity improvements means figuring out how to keep the first category and avoid the second. This isn’t me arguing for or against AI. It’s just me telling you not to be lazy and say “if it were productive you’d be able to measure it.” |
I think the prevailing (correct) consensus is that developer productivity is actually very hard to measure, and every time it is attempted the measure is immediately made a target making the whole thing pointless even if it had been a solid measurement- which it wasn't.
IDK where you're getting the idea here that measuring productivity of anyone who isn't a factory worker is easy.