# harness

A Tsinghua Shenzhen team proposes Natural-Language Agent Harnesses: move agent control logic from code into structured language executed by an IHR runtime. Harnesses can reshape behavior, but more structure does not always mean better results.

ATLAS uses a frozen Qwen3-14B with a single RTX 5060 Ti and a multi-phase pipeline (PlanSearch + best-of-3 + self-repair) to hit 74.6% on LiveCodeBench — passing Sonnet 4.5's 71.4%. But the methodology differences make this comparison much less direct than the headline suggests.

Ethan Mollick's game-changing AI framework: Model, App, Harness. The same AI (e.g., Claude Opus 4.6) performs vastly differently across layers. Mollick used Claude Code to turn GPT-1's 117M weights into 80 books in ~1 hour, selling out immediately.