The other 90% is understanding specifications of requirements (sometimes even helping customers write them), produce detailed functional specifications, cost analysis, prototyping, meeting with third party vendors over interface design specifications, determine the project's scope, testing, delivery, integration and commissioning, bug fixing, identifying and managing scope changes among other things.
AI may help you complete some of these tasks more effectively, but at the end of the day it will be just another tool in your kit.
That really depends on the type of "Software Engineering" you're doing. In my experience, in greenfield projects, boring CRUD-type programming can easily take up 50% of your time.
It'd be great if AI could automate this boring CRUD-type programming away, and let me focus on the architecture and interesting algorithms.
The other 90% is understanding specifications of requirements (sometimes even helping customers write them), produce detailed functional specifications, cost analysis, prototyping, meeting with third party vendors over interface design specifications, determine the project's scope, testing, delivery, integration and commissioning, bug fixing, identifying and managing scope changes among other things.
AI may help you complete some of these tasks more effectively, but at the end of the day it will be just another tool in your kit.