This paper introduces AIFL, a deterministic LSTM-based model for global daily streamflow forecasting, utilizing a novel two-stage training strategy to bridge the performance gap between historical reanalysis data and operational forecast products. It demonstrates competitive predictive skill and exceptional reliability in extreme-event detection, serving as a robust baseline for the global hydrological community.