AI-assisted development tools have dramatically accelerated how quickly teams can ship software. As output increases, a quieter leadership question is emerging. How do we ensure engineers still truly understand the systems they are responsible for?
As a Senior Engineering Manager working with AI-enabled teams, I have seen productivity gains firsthand. I have also seen moments, especially during production incidents or late-stage debugging, where speed suddenly gives way to uncertainty. Not because the code was wrong, but because no one fully understood how it worked.
That tension is worth paying attention to.
