RSI-Env lets an agent rewrite both model and harness, then hands the next round to the accepted version, with gains even without benchmark feedback
RSI-Env places model training and harness modification in one persistent sandbox, with an independent Host Controller handling services, validity checks, versioning and capability evaluation, and in Self mode each accepted model–harness version takes over the next improvement round. Starting from Qwen3.8-27B with a minimal harness, Open-General Self, which receives no benchmark feedback, raises GPQA Diamond accuracy from 65.2% to 73.2% and AIME 2026 from 53.3% to 56.7%; Knowledge Self lifts SimpleQA from 82.0% to 85.0% and then 88.0%, while the same runs fall back on other benchmarks.