They probably still need to be able to read and distinguish good vs bad code, evaluate agent decisions, data structures, feasibility, architectural plans, etc, all of which require specific software engineering expertise, even if they don't end up touching the code directly.
But that doesn't make sense. They claim that AI is writing 100% of the code, yet if they need to be able to read and distinguish good vs bad code, evaluate agent decisions, data structures, feasibility, architectural plans, etc, that implies they are writing at least some of the code? Or else why would they ever need to do those things?
This is not the fantastic argument you think it is. 100% is only achievable if you have software engineers at the helm so there's no contradiction here.
If the AI is doing 100% of the work why would you need software engineers at the helm?
100% of the code, not 100% of the work.
what doesn't make sense? "writing" the code is implementation
you still need good swes to distinguish if the generated code is good or bad and adjust the agent and plan the system
ime opus is smart enough to oneshot medium to small features by learning the existing codebase provided you give it the business context