Or there are valid business reasons to keep chipping away, in particular on performance-per-dollar problems at scale. If you're spending $1M/month on hardware to run something, each 10% win is worth enough to employ a couple senior engineers.
1M * 12 * 10% = 1.2M
500k * 12 * 2 * taxes >= 1.2M
How many 10% wins do they have to achieve in what timeframe to have a good ROI on micro-optimization, considering that these seniors could be producing stuff that allows for multiple times their salary in revenue?
Suppose you have two engineers that total to $1M of personnel cost. If they deliver a cost savings of 1% per month (compounding) the savings-per-month will have surpassed their pay per month; you will see your infra costs at 85% of what they were after 16 months, and on month 17 you will have made a net profit on those engineers, where the savings they got you has totalled more than what you've paid them.
If your business is growing, you could project your infra costs to grow beyond $1M per month, and the numbers become even more favorable.
Anyway, a profitable software company will be looking at getting a big multiple of 10x the salary of their engineers
All hard. But there's also a lot of easy cases out there - even good engineers might code like monkeys if they're under time pressure and trying to grow the business.
I've done a lot of performance work, and while of course no one individual could achieve a 1% savings per month on the entirety of FAANG compute loads, there is lots of code out there that nobody thought would run at scale or be on the critical path of something important, but now it is and it has gotten expensive.
Though cost opt generally involves way more than optimizing code. It's normally about auditing things, creating budget tooling, right sizing, broader architecture redesigns, etc.
1M * 12 * 10% = 1.2M
500k * 2 * taxes >= 1M