Different species often arrive at similar solutions to recurring challenges through convergent evolution. Such events provide some of the strongest examples of adaptation, yet understanding the molecular mechanisms and constraints that result in such convergence has only recently become possible due to advances in computing and genomics. Among animals, traits such as flight have arisen independently numerous times (e.g., in lineages giving rise to birds, bats, and insects), defining the ecologies and enabling the success of the resulting species. Similarly, venoms have arisen independently more than 100 times in animals and play diverse roles in, for example, predation and defense. These recurring traits represent optimal systems for investigating the rules and limitations of how evolution can yield complex adaptations, a major open challenge in evolutionary biology. This project will use integrative approaches including AI in multiple venomous animals to understand how complex traits repeatedly arise and evolve. Such an approach will enable not only the identification of how complexity originates but also catalyze future biotechnological innovations in the bioeconomy by uncovering functional solutions to common problems across the Tree of Life. Convergent evolution is a hallmark of adaptation and provides a means for delineating the roles of genetic and functional constraints in determining evolutionary trajectories. Venoms are one of the most common and convergent functio