The Harness of Harnesses • built for RSI: a trusted, persistent, self-evolving multi-agent ecosystem for all-domain collaboration.

Formal verification for AI: a Lean 4 + Dafny proof checker that catches fake AI proofs (reward hacking), and verified recursive self-improvement (RSI) for coding agents. AI for math, physics and software engineering.

NeoHorse-1: Towards Recursive Self-Improvement via Agentic Post-Training with Routing Harness.

The all-in-one AI agent. Build mobile apps, frontend, backend, manages files, deep research, schedule tasks and events. Self-improving, self-healing, fully autonomous. TUI, CLI and Daemon. Connect to your favorite channels. Zero Telemetry.

RSI-Anything: Unlocking Recursive Self-Improvement with World Models

A curated research map of Recursive Self-Improvement (RSI): models, agents, harnesses, embodied systems, automated AI R&D, benchmarks, and safety.

The official repository of "Position: Agentic Evolution is the Path to Evolving LLMs".

A curated list for Self-Improvement in Foundation Model Based Agentic Systems.

Harness self-evolution: update targets, theory, evaluation, and reported evidence. Bilingual reading list and project website.

ScienceBuddy: Recursive-in-Recursive Self-Improvement for Interactive Scientific Agents

Scikit-learn for Recursive Self-improvement (RSI). A modular framework for recursive harness evolution.

A lightweight Python SDK and CLI for evaluating recursive self-improvement (RSI) methods across agent benchmarks.

RSI-Exam: Measuring Recursive Self-Improvement on Long-Horizon, Executable Research Tasks · Discord https://discord.gg/FBzhepyE

Updated weekly — until humanity achieves AI4AI. A survey-grounded catalog of 432 papers on long-horizon agents, benchmarks, harness design, and recursive self-improvement.

Research artifacts from Hyra (/ˈhaɪ.rɑː/)

A plugin runtime for software that iterates on itself — the substrate where agents write, swap and hot-reload their own plugins in Rust, TypeScript, Python and Go, across processes and machines.

DiscoveryRSI: Recursively Learning to Discover Valuable Hypotheses

Fewer Tokens, Better Action: GPT-6 Astra Robot Agents with 14% Higher Success but 65% Fewer Tokens

Typed-decision models (noul / choice / score) trained by a self-improving loop of AI agents — checkpoints, the code that produced them, and every version that failed.

Self-evolution for any agent harness. Plug in. Evolve. Measure.