This post discusses the complexities of forecasting models used by Airbnb during and after COVID-19. It highlights the importance of making informed decisions when adapting models, differentiating between refitting, respecifying, and holding. Redefining structures and understanding biases that persist after shocks are key themes, as well as lessons learned from mistakes made during the pandemic.