Mentor Me - an AI mentor that reviews code the way I actually would

This is a submission for the Hacktoberfest Weekend Challenge: Build for a Friend

What I Built

Mentor Me is an AI mentor for a junior developer I informally mentor. She gets code review and "why would you do it this way" answers from me whenever I have a free minute, which is inconsistent and usually late at night. Mentor Me reviews her code on her own schedule and writes up what actually matters so she's never stuck waiting on me, and the feedback still reads like mine, not a generic bot's.

Demo

https://mentor-me.ashwintemkar.com

Code

https://github.com/ashwintemkar/mentor-me

How I Built It

• Backboard routes the review request through a single API key to an open-weight model, so the mentor agent isn't locked to one provider.
• Tinker (Thinking Machines) fine-tunes a small open model with LoRA on a corpus of my own past review comments, so its feedback carries my actual tone and priorities instead of generic LLM notes. finetune/compare.py samples the base model and the fine-tuned checkpoint on the same prompt, side by side.
• Render hosts the app itself (via a render.yaml Blueprint), so my mentee just opens a link nothing runs on my machine for her to depend on.
• Sign-in (Google/GitHub) and sessions run on Supabase Auth.

Why Does Open Innovation Matter?

This only works because the model is open-weight. I can fine-tune it on my own private review history no closed, hosted model lets an individual mentor do that without becoming an enterprise customer. Backboard means I'm not locked to one model or vendor, so I can route to whichever open model is cheapest or sharpest that week. And because it costs next to nothing to run, my mentee can ask for a review as often as she wants without anyone metering her, or her mistakes sitting on a server neither of us controls beyond the inference call itself.

Prize Categories

• Best Use of Tinker (Thinking Machines)
• Best Use of Backboard
• Best Use of Render