This very well summarizes my current thinking on the subject as well

> I think many software engineers forget they exist to get real things done (in many cases at least) and they are a cost center for most businesses. If your end product is not selling software, very few people actually Doing the Thing(tm) will give a single solitary care about code quality or maintainability when they can just spend 30 minutes and $15 worth of tokens to fix it. I am suprised to hear people so naive they expect their token usage to stay flat if code quality and maintainability starts falling exponentially? What if to fix 2 bugs your LLM starts adding 50 new ones? Will you tell your customers in supports channel "sorry software is finished, if we try fixing anything, everything else might break, not worth it". Or "we can probably fix it, but our AI usage will raise so much we need to up the subscription 3 fold, you choose". The speed at which LLM codes is only comparable t…

> Does AI make incredibly inefficient code most of the time? Yup. But it does it at lightspeed with minimal effort. This hits the nail in the head. Detractors often hang on to examples of coding assistants making mistakes or output subpar code, but they somehow miss the fact that coding assistants can also be prompted again and refactor whole swaths of code just as fast as they introduce oppsies. This means that the worst case scenario implies fast convergence to an acceptable outcome, and from there also fast iteration to improve upon that.

I think many software engineers forget they exist to get real things done One billion percent. I think the vast majority of the anti-AI sentiments I hear from software engineers comes down to them caring more about playing with their tools than actually solving the problem.