Felix

This is probably the first RL work on OpenClaw 🔥 MetaClaw: Just talk to your agent and let it evolve automatically. Github: github.com/aiming-lab/Met… Most AI agents are frozen the moment they ship. Every mistake they make, they'll make again tomorrow. MetaClaw fixes that. It's an online RL layer built on top of OpenClaw that lets agents learn from their own interactions — no GPU cluster, no offline dataset, no engineering team required. The loop is simple: every conversation is logged as a training trajectory. When the agent fails, it analyzes what went wrong and proposes a new reusable skill. LoRA updates train asynchronously in the background. The next time a similar situation comes up, the relevant skill gets retrieved into the prompt automatically. The agent doesn't just accumulate conversations. It accumulates capability. What makes this different from fine-tuning: there's no human labeling pipeline, no batch training runs, no deployment cycle. The improvement happens continuously, invisibly, in production. Interaction → learning → improvement, on a loop. No offline dataset. No coding required. No GPU cluster. The part worth paying attention to: this turns every user interaction into a training signal. The agent you deploy on day one is not the agent you have on day thirty. It's been shaped by everything it got wrong and fixed. Great work by @HuaxiuYaoML !

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from his funding wallet, the wallet with the highest volume of transfer activity was: 6wRep8xopKBL8XXZBjm3NPeatkTrLi5PEghawbWx7YmD safe to assume this wallet also belongs to Nick Fuentes #transfers" target="_blank" rel="nofollow noopener">solscan.io/account/FDUPzq…