It really just depends on how much of a computational surplus you have. Some tasks have become so incredibly easy relative to today's computational horsepower, that we can afford waste 90% of it if it means we can be 10% more productive.

But this isn't true everywhere. Imagine if Google's servers cost 100x more to run, if they didn't spend time to make their code efficient. Imagine if your video games ran at a frame rate 100x slower than they do now. Imagine if your phone sucked 100x more battery power, and lagged 100x longer after each tap.

Sounds like I'm making extreme hypothetical examples? Not really, when languages like Python and Ruby can be over 100x slower than other high level languages (e.g. Java, not to mention C/C++).

And of course, the counterpoint is usually "But most of the time is spent in the database/[some highly optimized library], not the high-level logic." To that I reply: You're absolutely right. Guess what those subsystems were written in? C/C++/Java, most likely.

If you're fortunate enough to have all your performance-critical components already highly optimized and written for you by experts at bare-to-the-metal efficiency, you probably don't have to think about this. But if you're working on a technology truly new and unique, chances are you're going to have to "get your hands dirty" at some point if you want to avoid paying 100x more than is necessary in server fees.