EVERY DX survey that comes out (surveying over 20k developers) says the exact same thing.
Staff engineers get the most time savings out of AI tools, and their weekly time savings is 4.4 hours for heavy AI users. That's a little more than 10% productivity, so not anywhere close to 10x.
What's more telling about the survey results is they are also consistent in their findings between heavy and light users of AI. Staff engineers who are heavy users of AI save 4.4 hours a week while staff engineers who are light users of AI save 3.3 hours a week. To put another way, the DX survey is pretty clear that the time savings between heavy and light AI users is minimal.
Yes surveys are all flawed in different ways but an N of 20k is nothing to sneeze at. Any study with data points shows that code generation is not a significant time savings and zero studies show significant time savings. All the productivity gains DX reports come from debugging and investigation/code base spelunking help.
In my experience the productivity measured in created merge requests increased massively.
More merge requests because now the same senior developers are creating more bugs, 4x comparing to 2025. Same developers, same codebase but now with Cursor!
Past survey results are hidden in some presentations I've seen, and the latest survey I have full access due to my company paying for it. So I'm not sure it's legal for me to reproduce
I think there is going to be 2-3 year lag in understanding how llms actually impact developer productivity. There are way too many balls in the air, and anyone claiming specific numbers on productivity increase is likely very very wrong.
For example citing staff engineers as an example will have a bias: they have years of traditional training and are obviously not representative of software engineers in general.
FWIW I only mentioned staff engineers because the survey found staff+ engineers reported the highest time savings. The survey itself had time savings averages for junior (3.9), Mid level (4.3), Senior (4.1) and Staff (4.4).
Staff engineers get the most time savings out of AI tools, and their weekly time savings is 4.4 hours for heavy AI users. That's a little more than 10% productivity, so not anywhere close to 10x.
What's more telling about the survey results is they are also consistent in their findings between heavy and light users of AI. Staff engineers who are heavy users of AI save 4.4 hours a week while staff engineers who are light users of AI save 3.3 hours a week. To put another way, the DX survey is pretty clear that the time savings between heavy and light AI users is minimal.
Yes surveys are all flawed in different ways but an N of 20k is nothing to sneeze at. Any study with data points shows that code generation is not a significant time savings and zero studies show significant time savings. All the productivity gains DX reports come from debugging and investigation/code base spelunking help.