Before AI, it was impossible to measure productivity. Some tried with misguided metrics like lines of code added but that just incentivized writing obtuse code.
Stuff just gets done, I guess? Projects move faster, people onboard faster with less intervention, etc. The speedup seems noticeable enough that it doesn’t need precise measuring.
If the speed up is noticeable enough then coming up with a metric should be easy?
I haven’t noticed a speed up in my own org though the feeling of engineers rushing to implementation has become more pronounced. Team members no longer understand what others are doing and siloing has become intense even within my team.
Quality matters as well as speed though: reworking comes at a cost, so you really need to be tracking more than one metric. A lot of problems are caused by optimising for one metric above all else.
Impossible to measure in absolute terms but I think it's clear productivity increases relatively when LLMs are used. At least that's my strong experience.
What has changed?