Literally the only thing I tend to worry about up front is deployment automation. I've worked in so many environments that don't have it, or have some byzantine manual deployment strategy that just gets irksome and difficult. I'm a big fan of containers, even for single-system deployments. If only because it always bites you when you are under the greatest time pressure otherwise.

Beyond that, my focus is on a solution to the problem/need at hand, and less about optimizations. You can avoid silly stuff, and keep things very simple from the start. Make stuff that's easy to replace, and you often won't ever need to do so.

Most software isn't about science, and isn't engineering... it's about solving real world problems, or creating digital/virtual solutions to what would otherwise be manual and labor-costly processes. You can shape a classic rdbms into many uses, it's less than ideal, but easy enough to understand. Very few jobs are concentrated on maximizing performance, or minimizing memory or compute overhead. Most development is line of business dev that gets deployed to massively overpowered machines or VMs.

But that's just the point, for most problems most people have, you don't have to be scientific. If your invariants vary and it breaks 5% of the time that's fine and nothing bad happens.

There's so much waste in the world, that it is unbelievable.

However counterintuitively, I have stopped caring about waste, and have been more focused on the value. Waste you can always optimize later if you want to, value creation is the difficult part.