Rippling Software Engineer Interview Experience — Explaining an Expense Rules Engine Before Using AI

The author reports passing Rippling’s first AI-assisted interview, which used an expense-policy evaluation exercise. Their approach began with discussing requirements and edge cases, then outlining classes and basic functions while explaining design decisions. This initial work took more than 20 minutes. Only afterward did the author ask AI to complete implementation details within that structure, followed by tests whose intended coverage was discussed first.

The exercise included checks on individual expenses, aggregate spending limits for trips, and a discussion of combining conditions. The author’s main lesson was that clear independent reasoning still mattered: AI helped fill in code, while the applicant remained responsible for the design and testing approach. This is the author’s interpretation of a successful first round, not a stated company-wide evaluation policy. No final hiring outcome is reported.