Bad Data Breaks Automations: How to Handle Missing or Changed Fields

Most automation failures are not dramatic; they happen because a field is blank, a value changes format, or an input arrives differently than expected. This episode shows how data problems cascade through workflows and why validation matters before actions run. You’ll learn: How missing fields and bad formatting cause failures What schema drift looks like in real workflows Simple validation checks that prevent broken runs How to design safer fallbacks for incomplete data