Overview
Software Lifecycle Env is a public Python benchmark environment that tests whether AI agents can inspect realistic engineering context, apply safe fixes, run validation, and avoid visible-case-only patches.
What I built
I built a benchmark environment where agents inspect an in-memory repository, patch files, run deterministic validation, and submit final answers against visible and hidden checks.
Technical focus
The technical focus is safe evaluation design: typed actions, deterministic scoring, hidden regression checks, anti-gaming controls, FastAPI wrapping, and reproducible benchmark-quality scripts.
Why it matters
This project demonstrates applied AI engineering beyond demos: designing evaluation systems that test realistic software lifecycle behavior.