Most systems optimize for getting an answer. Some have to optimize for never getting the wrong one. Here's how building for asymmetric error costs changes everything about your architecture.
A note before we start: this is an architecture essay, not a product teardown. There's no proprietary anything in here — just a design philosophy I've had to live inside for the last couple of years, and that I think more engineers should be deliberate about.
Two kinds of "wrong"
Most of the systems we build are quietly optimized around a comfortable assumption: that a missed answer and a wrong answer cost about the same. A search result you didn't surface and a search result that's slightly off are both just "not great." You tune for accuracy, you ship, you move on.
Then occasionally you build something where that assumption is not just wrong — it's dangerous.
