Your assistant now writes most of the code. How do you validate AI-generated output at scale so quality doesn't crater?
When the model writes the code, your job shifts to specifying and checking it. The strong answer is a multi-layer validation pipeline that tests behaviors and contracts, not strings, plus the uncomfortable reframe that testing is now the bottleneck skill, not typing.
Updated Aug 2026 · Grounded in real Forward Deployed Engineer interview loops and written to a senior-engineer editorial bar.
When the model writes the code, your job shifts to specifying and checking it. The strong answer is a multi-layer validation pipeline that tests behaviors and contracts, not strings, plus the uncomfortable reframe that testing is now the bottleneck skill, not typing.
Lead with where the obvious approach breaks, because that is the judgment they are screening for — most candidates jump straight to the happy path and lose the room.
Then walk the failure back through the pipeline in order, naming the one metric the customer's exec sponsor actually cares about before you propose the fix.
