Five ideas, papers, and products shaping our investment thinking, and what we think they mean. This series is powered by an AI assistant that helps synthesize recurring themes from our discussions, alongside our own reflections.
AI power is being underwritten like infrastructure. CleanSpark closed $2.276B of senior secured notes, following its 20-year, 175 MW lease with an unnamed investment-grade tenant worth $6.6B. TeraWulf signed a similar 20-year, 401 MW lease with Anthropic worth $19B. This matters because the credit belongs to the tenant while the scarce asset is the energized site, which is why former bitcoin miners now borrow like utilities. We think the opportunity sits between power and compute: project-level financing, and capacity for tenants below investment grade that still need megawatts.
Compute futures hit a regulatory speed bump. The CFTC extended its review of CME’s proposed H100 and B200 rental index futures to November 9, citing novel or complex issues. A separate request for comment asks about cash-market liquidity, manipulation and customer protection. This matters because compute can’t be hedged or financed at scale until there’s a price people trust. We think the opening is index integrity: neutral, transaction-based benchmarks and verifiable settlement underneath any forward curve, GPU-backed loan or onchain compute market.
OpenAI is building a chip-design model with Synopsys. GPT-Synopsys will operate Synopsys’s EDA tools directly under a multi-year revenue-sharing deal, without training on customer designs. The same day, Synopsys signed a $1B-plus IP deal with Amazon that also covers its AI tools. This matters because a frontier lab now sees chip design as worth its own model, and chose to enter through the incumbent. We think a model trained to drive one vendor’s tools learns the tools, not the judgment of the designers using them. That leaves room for an independent layer built on real design decisions that works across every vendor’s flow.
Robots can do the work, just not cheaply enough. Anthropic estimates robots could perform 74% of physical job tasks, but only 0.3% are cost-competitive with human labor today. Training is getting cheaper: Magic-W0, a new world-action model, learns from human video, real-robot and simulation data and adapts to real tasks with little fine-tuning. This matters because physical AI’s constraint has moved from capability to unit economics. We think the nearer-term winners are cost-curve bets: cheaper hardware, structured environments, and the financing and integration layers that make deployment pencil out.
Stablecoins are becoming B2B payment rails. Allium counts $401-527B in stablecoin payments through August, up 42-63% year over year, with business-to-business the largest lane at $137-153B. Supply grew only 6%. This matters because volume, not supply, is now the story: stablecoins are settling real corporate flows. We think the next opportunity is credit on top of the rails: short-duration working capital for payment companies and their suppliers, financed onchain, where repayment data already sits in the transaction history.
We’ll share another edition next week.