My first coding project took me a week to debug. I used to think programming was just typing lines of code. But then I ran into this weird error that made no sense. I spent hours looking for a missing semicolon. Turns out, even the tiny stuff can cause big trouble. So yeah, not so simple after all.

Last summer, I argued back, but now I just say 'thanks for the tip' and keep working.

Hold up, they actually tried to pass a cover off as their own song?

What if overfitting isn't the real problem here? Sometimes models learn too well because the data is just bad. Splitting sets might hide issues instead of fixing them. I've seen cases where clean data fixes overfitting better than any split. If your model falls apart with new data, maybe your features are wrong. Relying on splits can make you lazy about real data quality.

Seriously though, that slope is way steeper than people realize. I've seen friends notice their tolerance building in weeks, not months. Then you're just trading one deadline for a totally messed up sleep cycle.