These Founders Invested $42M To Build On Hyperliquid An interview with @IamGyomei, co-founder of @Outcomexyz 🎙️ 0:33 Welcome: meet the founder of Outcome 1:19 Getting into crypto at university 3:18 From market maker to builder 5:19 Why prediction markets blew up 7:25 You can predict literally anything 8:22 Can anyone build on Outcome? 10:03 The first two weeks since launch 11:32 Hyperliquid traders vs the Polymarket crowd 13:54 The $42M stake explained 15:35 Why they skipped VC money 17:28 Team, hiring and using AI at work 19:17 When token? 21:40 Rewards, referrals and zero fees 24:26 What you can trade on Outcome 25:37 Why users can't create their own markets 27:32 The future of prediction markets 30:23 Bringing Wall Street markets on-chain 33:56 New York and educating TradFi 35:11 How to try Outcome 38:08 Catch Outcome at Token2049

Sherwood co-founder @imthatcarlos joins @ThisIsNewWave_ on the growth of AI agents. What started as experiments and slop looks very different two years later. Frontier models are more advanced now, opening a bigger opportunity for onchain agents and what Sherwood is building.

OUTCOME COFOUNDER REVEAL - FRIENDS PLEASE MEET @IAMGYOMEI

You can also watch here: 📹 YouTube(4K) - piped.video/rZ80zdIMXUc 🎧Spotify - open.spotify.com/episode/20a…

AI agents will need their own payment rails AI agents are starting to need a way to pay for resources online without relying on traditional payment methods That’s exactly where infrastructure like @sherwoodagent and X402 starts to become important

Meta’s ability to turn attention into money is insane

AI is starting to solve problems mathematicians couldn’t Now both OpenAI and Google DeepMind are showing how far AI can go in mathematical research

Would You Let AI Invest Your Money? An interview with @imthatcarlos , co-founder of @sherwoodagent 🎙️ 00:37 Welcome Carlos, and what Sherwood does 01:36 Carlos's background, and whether AI should be writing smart contracts 03:38 From the 2024 on-chain agent wave to now 05:01 How long agents can actually run, and what a multi-day task looks like 07:33 Power users, beginners, and where the edge is 09:56 Which AI model Carlos uses for agent work 11:19 Sherwood explained: the capital coordination layer for agentic finance 13:21 Agent operators, depositors and the fund leaderboard 16:24 Fund tokens and tokenized hedge funds 17:19 Who actually writes the strategies 20:41 The WOOD token, and how fees are split 23:49 What happens when a fund loses money 26:22 Guardians, staking and slashing 27:31 Voting windows versus the speed of crypto 29:49 Why Sherwood launched on Robinhood Chain 32:40 Tokenized stocks and access to the US economy 35:31 Where AI agents sit in finance in two years 36:34 Vibe trading 38:38 The agentic economy and X402 39:53 Revenue, fees and buyback plans 41:40 Launch timing, audits, and where to find Sherwood