I often advocate for a straightforward yet effective rule: the shortest solution that delivers the desired result is usually the best. This approach, favoring concise algorithms, not only ensures efficiency but also reduces maintenance cost and bug susceptibility. Intriguingly, this practical principle finds its theoretical counterpart in data compression algorithm, data analysis and machine learning through the Minimum Description Length (MDL) and the Kolmogorov Complexity.