Multicellular tissues, and ultimately complex organisms, are composed of multiple distinct cell types that differ in functional attributes. Such diversity in cell composition (i.e. phenotypic diversity) arises during development and regeneration, where progenitor cells differentiate along multiple cell fate lineages to form a heterogeneous population. While the molecular signals (i.e. cell states) that specify individual cell fates are widely studied, less is known about how multiple cell types can simultaneously emerge from a seemingly homogeneous population and which molecular mechanisms coordinate this process on a tissue-wide scale. Increasing evidence suggests that stochastic events, as opposed to hard-wired deterministic processes, are critical for emergence of heterogeneity. However, the molecular mechanisms that drive stochasticity and diversity in a mammalian tissue remain unknown, mainly due to a scarcity of tools to measure stochastic events in large numbers of single cells and to perturb cell-to-cell heterogeneity on a tissue level. Here I propose to use quantitative single-cell imaging, transcriptomic approaches, and optogenetic control of tissue heterogeneity to identify the molecular mechanisms driving phenotypic diversity. I will apply these techniques to mouse intestinal organoids, a multicellular system that recapitulates the intestinal epithelium. I hypothesize that variability in cell state (at the single-cell level) drives cell phenotypic diversity (at the tissue level). Different combinations of dynamic molecular signals within single cells may thereby pattern populations within a tissue to adopt specific fate outcomes. Gaining insight into the mechanisms of phenotypic diversity will answer fundamental questions in developmental and synthetic biology on the origins of cell diversity in multicellular tissues, how stochastic processes can ensure developmental robustness, and the maintenance of phenotypic equilibrium in homeostasis and disease.