Why My AI Tutor Improved With Hindsight

Our AI tutor used to treat every submission like the first one—until Hindsight let it connect attempts, and suddenly it stopped explaining errors and started predicting them. What I Built (and Why It Wasn’t Working) I’ve been working on a coding practice platform that behaves less like a judge and more like a tutor. You write code, run it, get feedback—but instead of a binary pass/fail, the system tries to explain what went wrong and nudge you forward. At a high level, the system is pretty straightforward: A frontend where users write and submit code A Python backend that handles submissions and orchestration An execution layer (sandboxed) that runs code safely An AI layer that analyzes output and generates feedback A memory layer where things got interesting The first four parts worked fine. Code executed, errors were captured, feedback was generated. But something felt off. The tutor wasn’t actually teaching. It was just reacting. The Problem: Stateless Feedback Is Useless Every time