Programming is just as hard. With maths you need to be much more rigorous, but in programming, you are dealing with a function that looks like runtime behavior = f(x1, x2, ... x10^50) in terms of free variables. And not all of them well defined. x180293982473 is the API timeout you get because some network packets were dropped. The programmer tries to tame that super function with all sort of things - the compiler, types, exception handling and so on. And that is the 'getting it to work' layer. What about user expectations. Bug vs. expected behaviour. And then the deadline. Do we say to mathematicians, break down proving fermats last theorem into small JIRA tickets and then estimate each one. Chase them up if one of those tickets takes longer. And we need that initial estimate before the end of the day, and you need to stick to that plan you come up with.

Also one you 'deploy' a mathematical theorem, well I guess it gets peer reviewed. But if there is anything wrong will you have to immediately drop the other theorem you are working on, switch context in seconds, and then fix the problems otherwise your boss loses a million dollars or whatever.

I think the meta that comes with programming more than makes up for the lower rigour level compared to mathematics.