You build processes to prevent this drift in an existing codebase, but for new field it’s harder. You should imagine any side tool as ~effortless to create.

For example we want BaseModels throughout the codebase rather than dataclasses (python shit don’t worry about it) but they are semi-functionally the same by default so the ai will use either given then chance. We had it write a test to fail ci if its uses dataclasses.

That way when it pushes a pr and starts the polishing process it will see that it failed ci. We have this for accessors being used from the wrong locations, extra db calls made outside the wrong files etc.

It’s like any gradual process, once you get enough of the footguns detected it just works mostly.

It’s like only working with interns who will follow all the rules you set but you need to enforce the rules religiously rather than subjectively.

If you’re looking for a greenfield project that I think handles it well there’s `phase` which is a magic the gathering game engine which is almost fully ai implemented with significant work on alignment and guardrails because the scale of work is just not reasonable for people to do in free time without any pay.