𝑱𝒐𝒆

OPTIONS TRADE ALERT🔥🚨 $NOW CALL 95 5/29 avg 3🚨

JP Morgan paid ~$700K/year to headhunt this Goldman Sachs trader, who turned $25M → $400M - Lehman Brothers also hired him and after he left the bank collapsed with $600B in debt 16-min and you’ll learn exactly what skills made every top fund on Wall Street chase the same trader

Major areas where the financial system still needs an update: 1. Tokenization of real-world assets - Real estate, stocks, bonds, funds, etc. onchain for instant settlement, fractional ownership & massive distribution. 2. 24/7 Global trading - Pooled global liquidity, every asset, every person, with great leverage and capital efficiency. 3. Next-gen payments - Near-instant, low-cost global transfers using stablecoins, including for Agentic payments. 4. AI-powered risk, credit, compliance, and advice - Better decisions, less fraud, and broader access to capital. Everyone gets access to a great financial advisor. 5. Innovation friendly regulation - Move from one-size-fits-all to risk-based rules that encourage innovation and competition instead of stifling it. 6. Expanded access - Open protocols that reduce middlemen and self-custodial wallets to expand access to everyone with a smartphone. 7. Capital formation - Low cost and turnkey for anyone to raise money for a good idea, increasing the number of startups. 8. Sound money - A refuge from inflation, when discipline is lost in fiat money. Jobs not done until we get these working for all. Will require lots of tech innovation and policy work to get there.

The continued conviction and doubling down on AI infrastructure, including names like $IREN and $SNDK, alongside strategic positioning in names such as $TE, $APLD, $WYFI, $BW, $CRWV, and former Bitcoin miners like $RIOT, $CLSK, $BTDR, and $HIVE, while still holding $BE, reinforces Leopold Aschenbrenner’s view that AGI could be achievable before the end of the decade. If that thesis holds, the primary demand for AI will remain concentrated in the infrastructure layer powering the entire revolution. This includes the energy required to support data centers where both training and inference take place, as well as sustained demand for memory and high-performance computing. The sector is positioned for trillions of dollars in electricity and infrastructure spending in the coming years as model scale continues to expand. From Aschenbrenner’s perspective, the greatest opportunity lies in the infrastructure buildout, which underpins the foundation of Situational Awareness LP.