R kelly

Hi jev

Hash n beans to start the day with @SuperteamMY in Kuching, Sarawak.

Flew and safely landed sarawak yesterday for Startup Village Borneo. First time in borneo with great people, great place, great haze 😆 . Jokes aside, very excited for the week ahead @SuperteamMY @solana @socoe_s

is there such thing as onchain quant researcher 😆 . finding edge using volatility as a base over #ROBINHOOD memestock szn. meme rarely fascinates me. but the degens have outdid themselves with this one, pegging it against Equities. a-meme-coin:native base:0x85e90a5430af45776548adb82ee4cd9e33b08077

The perfect bridge to offchain + onchain finance

And an agent is only as good as the information it can reason over. That's why Canopy is partnering with @wintelsite . Wintel brings institutional-grade market intelligence across US markets and equities, combined with real-world event context. Because price tells you what happened. Context helps explain why. And for tokenized markets, that context becomes even more critical.

Our Thesis LLMs give agents reasoning. Multi-agent systems give them specialization. Risk systems give them constraints. RL gives them a way to learn from outcomes. And markets give them the environment. We're still early. But I think this is a much more realistic direction than building another chatbot that tells you what stock to buy.

And this is where I think things get really interesting. Every trading cycle can produce a trajectory: State → Action → Outcome. What did we know? What did we decide? How much did we size? When did we enter? When did we exit? What happened afterwards? Over enough cycles, that becomes a dataset for learning.