How is this different from 'just controlling for covariates' in a regression?

A common confusion: people think a regression with controls = causal estimate. The potential-outcomes view makes explicit that you need the right covariates (those that block confounding) and that controlling for a collider or mediator can create bias. The framework's value is making those distinctions unavoidable.