Antigen recognition by T cells through their highly diverse T cell receptors (TCRs) is central to adaptive immunity, and recent high‑throughput methods and databases have greatly expanded the availability of TCR–antigen specificity data. However, much of this information is noisy or weakly validated. We explore the field’s main bottlenecks, which are data quality rather than quantity, motivating rigorous experimental validation, statistical filtering and multimodal AI approaches to derive high-confidence TCR specificity records.