Writing code is just one part of the overall list of things that an engineer does. Infact, barring the early versions of product/project more time is spent elsewhere in subsequent versions. With code it is more reading than writing new code. Other things on which time is spent are:
1. What needs to be built? What is feasible?
2. Investigations (bug reports, production issues, performance issues, etc)
3. Quality control (code reviews, writing tests)
I am only listing things which require considerable thinking and multi-domain skills. So LLMs (as of now) really only helps with one part of overall things to do.
Also, Rate of code generation with AI >> Rate of effective code review. So the bottlenecks will still be humans.
PS: About quality control: I think AI writing code and generating the test code is not desirable. If the underlying LLM has issues even the test code will have issues. Generating boilerplate is one thing but the key things about the tests (i.e. inputs/scenario & things to check) needs much better curation. This needs human intervention.
1. What needs to be built? What is feasible?
2. Investigations (bug reports, production issues, performance issues, etc)
3. Quality control (code reviews, writing tests)
I am only listing things which require considerable thinking and multi-domain skills. So LLMs (as of now) really only helps with one part of overall things to do.
Also, Rate of code generation with AI >> Rate of effective code review. So the bottlenecks will still be humans.
PS: About quality control: I think AI writing code and generating the test code is not desirable. If the underlying LLM has issues even the test code will have issues. Generating boilerplate is one thing but the key things about the tests (i.e. inputs/scenario & things to check) needs much better curation. This needs human intervention.