suppose that I want to use linear regression on a data where independent variables x1,x2,...xn are all more or less normally distributed, while the dependent variable y is almost exponentially distributed, what should I do to y (or the whole dataset) so that it is okay to use linear regression model?

if not limit to the ordinary linear regression model, what model can I use to have a better fit?

suppose that I want to use linear regression on a data where independent variables x1,x2,...xn are all more or less normally distributed, while the dependent variable y is almost exponentially distributed, what should I do to y (or the whole dataset) so that it is okay to use linear regression model? I applied log transformation to y and then used ols, which seems fine to me, until a friend argued strongly against using log transform under such condition, but he did not provide any solution. So I am here to ask for help.

if not limit to the ordinary linear regression model, what model can I use to have a better fit?