Most quiz systems check whether you typed the right string. I wanted to build one that evaluates whether you understood the concept. That's a harder problem. "A contract between services" and "an agreed-upon interface" are the same answer to anyone who understands APIs. To a string matcher, they're completely different. Closing that gap is what led me down the path of deploying a custom ML model on AWS Lambda — and eventually to cutting PyTorch entirely from the container. Here's how it went. The problem with string matching Know-It-All Tutor is a serverless learning system where users define knowledge domains, add terms and definitions, and get quizzed on them. The core evaluation problem: when a user submits an answer, how do you decide if they got it right? The naive approach — exact string match or even fuzzy string match — fails immediately. Learners paraphrase. They use synonyms. They express the same concept in ten different ways.…