The hardest part about writing AI-generated code was having to explain it later.

AI made it possible for us to go from concept to prototype way quicker than ever before.

The issue arose weeks later after we began implementing changes to our existing code.

A simple change meant having to understand the reason behind multiple seemingly unrelated lines of code.

The code worked but the context didn't make sense.

In order to fix this, we've stopped documenting each line of code and have instead documented why we decided on some AI-generated solution.

It has already helped us with making future changes by keeping track of our decisions rather than the code itself.

How do your development teams ensure that the decision-making process behind AI-generated code is not lost?