Sequence-based identification and detection technologies have revolutionized plant disease diagnostics in the last few decades, opening the door to highly selective and specific diagnostic assays. However, diagnostic assay development and validation remain hindered by many factors that would be ameliorated by research prioritization and coordination. Massive amounts of sequence data, in the forms of evolutionarily informative markers and now whole genomes, are available yet not easily accessible or properly organized to guide efficient assay development and deployment. For many key pathogen groups, particularly those that are not easily culturable, data are scant. Identification of pathogen-specific sequences in microbial genomes, the ultimate diagnostic markers, requires massive data processing and is slowed by a lack of quality data curation pipelines that efficiently translate data into problem solving. New technologies have the potential to enable detection at extremely low titers, but many of these have not yet found their way into diagnostic labs, much less the field. Here, we review the current status of diagnostics readiness in select groups of pathogens and pathosystems and define research priorities to fill knowledge and resource gaps to support scientists engaged in diagnostics. These priorities include improved coordination of data generation and curation and validation of new technologies, such as LAMP, MiFi, RPA, and CRISPR-Cas, to accelerate the implementation of more specific and sensitive assays. Finally, novel approaches, such as detection of volatile profiles and microbiome analyses, have the potential to complement pathogen diagnostics focusing on specific pathogens. The author(s) have dedicated the work to the public domain under the Creative Commons CC0 ?No Rights Reserved? license by waiving all of his or her rights to the work worldwide under copyright law, including all related and neighboring rights, to the extent allowed by law, 2023.