The article discusses how researchers are using a linear regression model in Economics with many covariates to control for confounders. They found that the usual standard error estimators for linear models are inconsistent in this scenario. To address this, they developed a new formula that can handle both heteroskedasticity and many covariates. This new formula is automatic and robust, meaning it can work well even when the data is messy or has a lot of variables. They tested their findings in three different situations and found that their new method works effectively in all of them.