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Its a yes if you do not know the domain space, query patterns well enough and also if the cost of optimization or time for optimization may have detrimental impact to business. In this case it most likely means that the crowd in the room did not anticipate much on this in early phases and no one in the room pointed these things out. The irony is that these performance and disk numbers are heavily discussed as a part of system design interviews. > In fact optimization is by far the easiest part of the process because there are many system programming experts on this HN thread who consider these optimizations to be trivia This is a misconception when you including roll out as a part of the change too, changing data once its running in production is hard, changing the data structure is even harder and when you talk about making changes in cache which is at the hot path its probably the hardest. Looking at the graph at the end it looks like it took them 4+ months to roll out the changes after optimization.

I do not think Cloudflare was a less-than-peers optimized product when they launched. This is one of their blog posts which describes taking one aspect even further. I think Cloudflare became big only because they were so much more optimized than others that they offered some services for free that others were not offering. If running costs are high, you only burn (VC) cash and then you exit.

Or optimize a bit earlier and prevent having to scale out to a bazillion systems.

This assumes that you have plenty of cash to burn in the process, which is approximately correct for VC-backed ventures, and for offshoots of large corporations that play a lomg game.

Make it work, make it fast, refactor