AI for planning, AI for RFC, AI for writing code, AI for creating PRs. Sure we can have harnesses and tests to ensure nothing breaks. But how do we enforce engineers to have a deep understanding of the code that they are shipping?
Our team has the usual suggestions: write a plan first, write test cases first, etc. But in this age, how do you verify that the engineer did not simply delegate these tasks to an LLM first?
Also genuinely worried about junior engineers' growth if this is the future.
> But how do we enforce engineers to have a deep understanding of the code that they are shipping?
By not pushing AI-first mindset. When you start tracking token usage metrics, people will optimize for that metric.
If you don't push them, and tell to use AI as a tool, they will optimize for understanding the code
When you writes code yourself, you only use concepts you have come across previously. But if you generate an AI solution, it may well use concepts one has not previously come across.
What do we expect a junior engineer to do then, if they do not have time to learn the concepts used ? Do we really think they will reject the AI code and implement their own, more familiar, solution ?