Both (1) "AI can, and does, make some people less effective" and (2) "the average productivity boost (~20%) is significant" (per Stanford's analysis) can be true.
The article at the link is about how to use AI effectively in complex codebases. It emphasizes that the techniques described are "not magic", and makes very reasonable claims.
the techniques described sound like just as much work, if not more, than just writing the code. the claimed output isn't even that great, it's comparable to the speed you would expect a skilled engineer to move at in a startup environment
> the techniques described sound like just as much work, if not more, than just writing the code.
That's very fair, and I believe that's true for you and for many experienced software developers who are more productive than the average developer. For me, AI-assisted coding is a significant net win.
Yet a lot of people never bother to learn vim, and are still outstanding and productive engineers. We're surely not seeing any memos "Reflexive vim usage is now a baseline expectation at [our company]" (context: https://x.com/tobi/status/1909251946235437514)
The as-of-yet unanswered question is: Is this the same? Or will non-LLM-using engineers be left behind?
Perhaps if we get the proper thought influencers on board we can look forward to C-suite VI mandates where performance reviews become descriptions of how we’ve boosted our productivity 10x with effective use of VI keyboard agents, the magic of g-prefixed VI technology, VI-power chording, and V-selection powered column intelligence.
The article at the link is about how to use AI effectively in complex codebases. It emphasizes that the techniques described are "not magic", and makes very reasonable claims.