We Gave Our Coding Tutor a Thinking Style Detector — This Is What We Found

By Aman | Team Clarion | Code Mentor AI "Six of us. Same loop problem. Same wrong answer. And the platform LeetCode, Scrimba, take your pick gave us all the same hint. The issue wasn't just that these platforms forgot our mistakes. It was that they never tried to understand how we think. Code Mentor AI started as our attempt to fix that. My job was building the AI that actually models how a student approaches a problem not just what they got wrong." Beyond Mistake Logging: Understanding Thinking Patterns Most AI tutoring features focus on outputs wrong answers, failed tests, error messages. I worked on something earlier in the pipeline: the Thinking Pattern Report, which analyses how a student approaches a problem based on their behaviour in the editor. Using Monaco editor event listeners, we capture keydown/keyup events, detect pauses longer than 3 seconds, and track deletion-to-keystroke ratios. These raw events get batched and sent to a FastAPI endpoint every few seconds, then aggre