Explain the basics of reinforcement learning (and how it differs from supervised learning).
RL sits under RLHF, robotics, and recommendation, and interviewers want the core framing. What matters is the agent-environment-reward loop and the three things that make it harder than supervised learning. Here is the answer.
Updated Sep 2026 · Grounded in real GenAI, LLM, and AI/ML engineering interview loops and written to a senior-engineer editorial bar.
RL sits under RLHF, robotics, and recommendation, and interviewers want the core framing. What matters is the agent-environment-reward loop and the three things that make it harder than supervised learning. Here is the answer.
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.
