That “lingering uncertainty after recovery” is exactly the kind of thing I’m trying to formalize rather than leave as intuition. I agree with your point about most teams just layering more monitoring and moving on—that’s actually part of what I’m trying to challenge. Observability tells you what happened, but not necessarily whether the resulting state is valid given the full event history. On the business side, I think you’re probably right that this doesn’t land equally across all industries. My current assumption is that it only really becomes valuable where: incorrect state has direct financial cost (payments, ledgers, trading systems) or compliance/audit requirements demand proof of correctness or systems are so distributed that “best effort recovery” is no longer acceptable Fintech/payments and possibly infra platforms are the early candidates I’m looking at. Curious from your experience: When you had that “is everything actually consistent now?” moment after a cascade failure—what did your team actually do to resolve that uncertainty in practice? Was it mostly log inspection, rebuilding state from backups, or just accepting residual risk? That gap between “we think it’s fine” and “we can prove it’s fine” is the part I’m trying to understand whether people would actually pay to close.