While the basic principles were formally presented almost 30 years ago, satellite detection of fires is still a developing field which has seen rapid evolution in recent years both of the data available and our understanding of what is being observed and quantified. Development work of the Wildfire Automated Biomass Burning Algorithm (WF_ABBA) for the GOES-R Advanced Baseline Imager has allowed for a close examination of how instrument characteristics impact fire detection and characterization, as well as illustrating the advantages of the next generation satellites while simultaneously suggesting new directions for fire detection and characterization. The WF_ABBA has been implemented on geostationary satellites including the National Oceanic and Atmospheric Administration's GOES series through the planned GOES-R, EUMETSAT's Meteosat-8/-9, and the Japanese Meteorological Agency's (JMA) MTSAT-1R and will be implemented for other geostationary satellites such as India's INSAT-3D as they become available. Advances in affordable computing hardware have allowed relatively easy reprocessing of the entire data records of the supported satellite series, creating a 13 year (and growing) record from GOES over the Western Hemisphere and providing a large, internally-consistent dataset. The advantages and drawbacks of using one algorithm for global detection of fires will be discussed.