How time can ruin your most precious machine learning model

Once, potential time dependent effects have been identified you should check if these effects are present in the data and if your data actually covers the necessary time spans to detect it. If the data depends on time there are three basic options to handle it. What experience regarding time have you made in your machine learning projects? Would you like to read a story about the various modelling & feature engineering techniques and validation schemes to include these time effects?