What is RLVR (reinforcement learning with verifiable rewards), and why does it work for reasoning models?
Swap a learned reward model for a checker that returns right-or-wrong, and reward hacking largely vanishes. The signal is why verifiable rewards beat learned ones for math and code, and where they break.
Updated Sep 2026 · Grounded in real GenAI, LLM, and AI/ML engineering interview loops and written to a senior-engineer editorial bar.
Swap a learned reward model for a checker that returns right-or-wrong, and reward hacking largely vanishes. The signal is why verifiable rewards beat learned ones for math and code, and where they break.
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.
