[snovv_crash]

In academia you get to choose your problem. This means that if something isn't working you can restrict the inputs or only operate on some subspace of the problem.

In contrast, industry doesn't let you choose the problem: you need to solve whatever the problem is that the client has. This means generalising a lot further and having a less optimal solution that is more robust to input error or poorly calibrated measurements. Even if it does fail you should be able to identify why and explain to the user what they did wrong.

In academia this feedback process is generally to the person who wrote the software, so a cryptic error message including some algorithmic details might be sufficient to debug the inputs sufficiently.