routing
FDE interview questions tagged routing, across every topic.
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Concepts behind "routing"
The curriculum that explains the ideas these questions test.
Core
Multi-Armed BanditsA bandit is online decision-making under uncertainty: you have several options (arms), each with an unknown payoff, and every choice both earns a reward and teaches you something. The tension is explore versus exploit: try uncertain arms to learn, or pull the current best to win. Epsilon-greedy, UCB, and Thompson sampling balance that tradeoff; contextual bandits pick per request using features. Unlike a fixed A/B test, a bandit shifts traffic toward winners as it learns, cutting the cost of running a loser.📊 Evaluation & ML FoundationsSign in
Advanced
Model Routing and CascadesModel routing sends each request to the cheapest model that can handle it, escalating only when needed. Most production traffic is easy, so paying frontier prices for every request is usually the largest avoidable line in an AI bill. The engineering is in deciding cheaply and in knowing what to do when the router is wrong.🧠 Foundations of LLMs & GenAI🔒 Premium
Advanced
System One Decision Models (Jev)A System One model such as TypeSafe's Jev returns typed decisions with calibrated probabilities instead of generated text: a yes/no probability, a choice from a closed set, or a score along rubric levels. It decides the architecture question that follows every LLM classifier in an enterprise pipeline: what belongs to the model, what stays in code, and where the confidence threshold goes.🧠 Foundations of LLMs & GenAI🔒 Premium