Earlier quoted context omitted.
> But not having to spend hours here and there getting up to speed on some mundane but unfamiliar aspect of the implementation Red flag. In other words you don’t understand the implementation well enough to know if the AI has done a good job. So the work you have committed may work or it may have subtle artefacts/bugs that you’re not aware of, because doing the job properly isn’t of interest to you. This is ‘phoning…
It sounds like you've never worked a job where you aren't just supporting 1 product that you built yourslef. Fix the bug and move on. I do not have the time or resources to understand it fully. It's a 20 year old app full of business logic and MS changed something in their API. I do not need to understand the full stack. I need to understand the bug and how to fix it. My boss wants it fixed yesterday. So I fix it and…
In my 40 years of writing code, I’ve worked on many different code bases and in many different organisations. And I never changed a line of code, deleted code, or added more code unless I could run it in my head and ‘know’ (to the extent that it’s possible) what it will do and how it will interact with the rest of the project. That’s the job.
I’m not against using AI. I use it myself, but if you don’t understand the scope fully, then you can’t possibly validate what the AI is spitting out, you can only hope that it has not fucked up.
Even using AI to write tests will fall short if you can’t tell if the tests are good enough.
For now we still need to be experts. The day we don’t need experts the LLMs should start writing in machine code, not human readable languages
> I do not need to understand the full stack.
Nobody said that. It’s important to understand the scope of the change. Knowing more may well improve decision making, but pragmatism is of course important.
Not understanding the thing you’re changing isn’t pragmatism.