Week 16: From Model to AI System

A trained model is only one component in an AI system.

Real systems have inputs, validation, preprocessing, serving code, decision rules, logs, monitoring, fallbacks, and people with authority to intervene. A model can behave exactly as tested while the surrounding system still fails.

This week follows one prediction from raw input to action. You will examine data contracts, serving and monitoring, then inject failures in the AI System Pipeline Simulator.

The main idea is simple: a score does not become a responsible action by itself. The system around the model determines what happens next.