Josh Han retweeted
🚀One of the biggest questions for AI agents is whether they can continue expanding their capabilities after deployment.
Deployment brings the experience needed to keep improving. As @ilyasut has argued, future intelligent systems should learn from deployment.
But this requires more than a new learning algorithm. It requires turning the serving stack itself into a learning layer: collecting live experience, turning it into updates, and safely bringing those updates back into serving.
That’s why we built Reef.
Reef is open-source infrastructure for continuously evolving agents at live deployment. To our knowledge, it is the first open-source infrastructure designed to evolve both model weights and the agent harness from deployment experience.
Not just weights, but also prompts, memory, skills, tools, and orchestration.
Reef already supports:
🧠Model evolution: SAO, TTT-Discover, OpenClaw-RL, with more recipes coming.
🛠️Harness evolution: SkillClaw, Meta-Harness, and a general harness-evolution engine built on Cordis, with native support for pi @pidotdev , OpenCode @opencode , and more harnesses coming.
With Reef, inference is no longer the end of the pipeline. It becomes part of a continual loop:
serve → learn → evolve → serve again.
Reef is fully open source. We would love you to try it, build on it, and tell us what is missing!
⭐ GitHub: github.com/Human-Agent-Socie….
💬 Discord: discord.com/invite/5y8e5f937….
#AgenticAI #llms
