There has been a massive shift in teaching quantitative political research since the "Journal of Political Science Education" was launched in 2004. Smartphones were an anomaly, and it was uncommon to have laptops in the classroom. Statistical calculations were sometimes done by "statisticians", i.e., professional staff who did calculations for faculty members. Today, it is rare to see students without electronics. Through that transition we experienced ubiquitous Wi-Fi and smartphones, statistical computing on personal computers, the end of the academic staff statistician, an explosion in open-source statistical software and tutorials, and an unexpected mass transition to online learning during COVID. We experienced a similar revolution in teaching statistics. Increases in computational power and data availability make quantitative and qualitative research different than 20 years ago. Computation is rarely a limiting factor, and we find ourselves spending more time on statistical assumptions, correct methods, data integrity, and replicability. We are now entering an era of assistive technology and will need to transition to teaching students how to use artificial intelligence tools to assist them with quantitative work. In this article, we consider these changes and what they mean for teaching political science in the next 20 years.