I think there are a number of elements:
- What you are working on. AI is better at solving already solved problems with lots of examples.
- How fast/skilled you were before. If you were slow before then you got a bigger speed up. If AI can solve problems you can’t you unlock new abilities
- How much quality is prioritized. You can write quality, bug free code with AI but it takes longer and you get less of a boost.
- How much time you spend coding. If a lot of your job is design/architecture/planning/research then speeding up code generation matters less
- How much you like coding. If you like coding then using AI is less fun. If you didn’t like coding then you get to skip a chore
- How much you care about deeply understanding systems
- How much you care about externalities: power usage, data theft, job loss, etc.
- How much boilerplate you were writing before
I’m sure that’s not a complete list but they are a few things I’ve seen as dividers
A few more:
- How much do you prioritize speed?
- Do you have a big backlog of dev tasks ready to go?
- What are the risks if your software doesn’t work?
- Are you working on a green field or legacy project? Prototypes or MVPs?