Autoresearch — Autonomous Iterative Optimization

You define the goal and how to measure it. The agent does the rest: hypothesize, edit, measure, keep or revert — running autonomously until you stop it or the budget runs out.

Inspired by Karpathy's autoresearch, adapted for Python, SQL, pytest, ty, and ML workflows.

[!IMPORTANT] Every experiment is committed before running, and reverted on failure. The branch only ever advances on real improvements.

Phase 1 — Setup (interactive)

Work through these questions with the user before touching any code. Do not skip or assume answers.