Digital markets and platforms have shaped the algorithmic landscape into a complex ecosystem of strategic, self-interested entities. This has motivated the study and development of mechanisms or algorithms that are robust to strategic behaviour, using tools from algorithms, game theory and economics. Standard assumptions in mechanism design are too strong to capture the informational challenges present in many real scenarios, from ad auctions where bidders' values depend on competitors' private market data, to resource allocation where there is uncertainty about future demands. In this talk, I will provide an overview of my recent work that tackles three important challenges—strategic behavior, interdependence, and online decision making—going beyond standard assumptions. In particular, I will focus on my work establishing the first constant-approximation algorithms for prophet and secretary problems with interdependent values.