PenguinHarness is an open-source framework for agent self-evolution (recursive self-improvement, RSI). The model stays fixed; the harness evolves: prompts, Skills, tools and hooks. It runs on your computer or server as a desktop app, a Web App, a CLI and an SDK.
The Harness of Harnesses • built for RSI: a trusted, persistent, self-evolving multi-agent ecosystem for all-domain collaboration.
Recursive Self-Improvement (RSI) refers to processes in which AI systems improve their own capabilities and can also improve the mechanisms that generate subsequent improvements.
NeoHorse is TokenRhythm's family of open-weight models for agent workflows. NeoHorse-1 provides 4B and 9B language models for tool use, coding, and instruction following. NeoHorse-Jev builds on NeoHorse-1-4B to make structured decisions through prefill-only inference.
The open-source design agent and harness, better than Claude Design on academic communication artifacts production. ) and any agentic model you want.
Recuris is a recursive self-improvement framework that improves a long-horizon agent by evolving its memory instead of its weights or its prompt. A frozen agent is paired with a Skill Memory M = (E, W, ρ, C).
> This repository accompanies The Last AI Built by Humans: Toward Genuine Recursive Self-Improvement (Yi Duan et al., 2026; arXiv:2609.11873).
Plug in any agent harness × any model, let it rewrite its own harness over many context-fresh episodes, and measure how the harness changes — under a goal, many goals, or no goal at all.