Hanfei Yu

Postdoc @ UC Berkeley | Ph.D. @ Stevens Institute of Technology | AI Infra

[Hanfei Yu @yhfchitanda]

@Xuan04263449 Indeed! Reef will release more features and optimizations. Stay tuned!

[Hanfei Yu @yhfchitanda]

Check how Reef serves your self-improving agents uninterruptedly while learning! https://t.co/7fpVuevR34

[Hanfei Yu @yhfchitanda]

@BobbyZhouZijian Thank you Zijian! Let’s make Reef accelerate RSI!

[Hanfei Yu @yhfchitanda]

@hanzheng_7 Thank you Han! Go Reef!

[Han Zheng @hanzheng_7]

Reef is taking off! 🔥 Within 2 days since we open sourced it, Reef got ~300 GitHub ⭐️!

Reef is the first open-source infrastructure designed to evolve both model weights and the agent harness from live experience.

Reef already supports:
🧠Model evolution: SAO, TTT-Discover, OpenClaw-RL, with more recipes coming.
🛠️Harness evolution: SkillClaw, Meta-Harness, GEPA, with native integration for pi, OpenCode, Hermes Agent, and more harnesses coming.

Come and build Reef with us at https://t.co/IsAcJZFNQq !

[Han Zheng @hanzheng_7]

🚀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: https://t.co/IsAcJZFNQq.
💬 Discord: https://t.co/UcMW6CTbww.

#AgenticAI #llms

[Ao Qu @ao_qu18465]

https://t.co/1T2jy03kth

[Bo Liu (Benjamin Liu) @Benjamin_eecs]

Continuous self-improvement needs an ever-expanding supply of training environments (goals).

SPADE: one model self-plays the Environment Designer and the Reasoning Agent, writing executable, agentic environments that get harder as it improves. Environment scaling on its own. ♠️