Issue 20: The Long Part of the Cycle
Productivity, patience, and where returns actually form
Lately I’ve noticed how quickly certainty turns into debate.
A year ago, AI felt like the answer to everything. Today, the conversation is quieter and more nuanced.
Not because the technology stopped mattering, but because expectations are starting to catch up with reality.
Who actually benefits? Where does productivity show up? And what happens when growth does not arrive all at once?
Before diving into the stories, a few ideas help frame what follows.
AI investment is no longer just about enthusiasm or fear of missing out. It is increasingly about productivity, execution, and whether spending translates into durable economic gains.
Europe’s technology gap reflects deeper structural issues, not just slower innovation. Differences in capital markets, labor mobility, and scale all shape how technology adoption plays out over time.
Tokenization continues to move from concept to infrastructure. As institutions participate, the focus shifts to compliance, structure, and real use cases rather than experimentation.
With that context, here is what stood out this week.
📈 BY THE NUMBERS
Is the AI Boom Overstated?
Carlyle examines whether the surge in AI investment reflects a true productivity shift or inflated expectations. While spending remains strong, the piece argues that returns will vary widely depending on where AI delivers real efficiency gains rather than speculative growth.
Takeaway for allocators:
AI exposure should be evaluated through productivity and cash-flow impact, not hype. Allocators may need to separate infrastructure, applications, and adoption risk, and prepare for uneven outcomes rather than broad winners.
📡 HEADLINE SIGNAL
Bridgewater Flags AI Spending Risk
Bridgewater warned that massive AI investment funded by external capital could create risk if returns fail to keep pace. With spending accelerating rapidly, concerns are rising that valuations may outstrip sustainable earnings.
Takeaway for founders:
Capital discipline is coming back into focus. Founders in AI-related sectors should be ready to defend unit economics, timelines, and durability as investors scrutinize growth assumptions more closely.
📈 BY THE NUMBERS
Does Europe’s Tech Gap Matter?
Paul Krugman explores whether Europe’s lag in big tech leadership meaningfully hurts its economy. He argues the impact is more nuanced, as living standards and employment outcomes depend on broader structural factors beyond headline innovation dominance.
Takeaway for allocators:
Regional tech leadership does not automatically translate into economic superiority. Allocators should weigh productivity, policy, and capital efficiency alongside innovation narratives when assessing geographic exposure.
📡 HEADLINE SIGNAL
JPM Launches Tokenized Money Fund
JPMorgan introduced a tokenized money-market fund on Ethereum, seeded with bank capital and designed to mirror traditional money-market behavior using blockchain settlement. The move reflects growing institutional comfort with tokenized financial products.
Takeaway for founders:
Tokenization is moving into production. Founders should focus on institutional requirements like compliance, reporting, and settlement rather than experimentation alone.
Back From Cape Town 🌍
I’m back in Honolulu after an incredible time in Cape Town, and the experience is still settling in. What stood out most was not just the work, but the way Greg Stephens and Paul Dando are approaching it. Thoughtful, grounded, and clearly built with the long term in mind.
Spending time with teams like Orobit is a reminder of how much care and intention goes into building real infrastructure. I’m grateful for the conversations, the hospitality, and the perspective, and genuinely impressed by what’s taking shape there.
That’s it for this week.
Thanks for reading the latest Dispatch. If you made it this far, you’re part of the shift. 🌊
See you next week, with more plays worth tracking.
— Thomas
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