The plant immune system relies on germline-encoded pattern recognition receptors (PRRs) that sense foreign and plant-derived molecular patterns, and signal health threats. Genomic and pangenomic data sets provide valuable insights into the evolution of PRRs and their molecular triggers, which is furthering our understanding of plant-pathogen co-evolution and convergent evolution. Moreover, in silico and in vivo methods of PRR identification have accelerated the characterization of receptor-ligand complexes, and advances in protein structure prediction algorithms are revealing novel PRR sensor functions. Harnessing these recent advances to engineer PRRs presents an opportunity to enhance plant disease resistance against a broad spectrum of pathogens, enabling more sustainable agricultural practices. This Review summarizes both established and innovative approaches to leverage genomic data and translate resulting evolutionary insights into engineering PRR recognition specificities.