What are multi-armed bandits, and when do you use them instead of A/B testing?

A bandit learns and optimizes at the same time, moving traffic toward the winning arm during the experiment rather than holding the split fixed like an A/B test. Interviewers look for the explore-exploit tradeoff, the three core algorithms, and a clear sense of when a bandit wins over a clean A/B test.

Updated Sep 2026 · Grounded in real GenAI, LLM, and AI/ML engineering interview loops and written to a senior-engineer editorial bar.