In venture capital, chasing 'access' to hot, consensus deals is usually a trap. The best founders and investors learn faster from direct, real-world feedback than from polished credentials.

For a century, companies extracted profits first and gave back through charity later. The most enduring businesses of the next 50 years will build models where unit economics improve only when customer and community outcomes improve.

We are wired to react to vivid, emotional threats while ignoring slow-moving statistical risks. In markets as in technology, abstract risks on a spreadsheet rarely feel real until the damage is already done.

As AI makes generating code and content nearly free, value shifts to what cannot be automated: trust. Durable moats will belong to businesses built on skin in the game, reputation, and clear accountability.

Instead of keeping interest income on reserves like Tether or Circle, Open USD shares reserve yield and network ownership with the platforms distributing it—a modern take on how Visa was originally built as a member-owned network.

When software can take a user from prompt to output in seconds, traditional onboarding funnels stop mattering. The real bottleneck shifts from building features to having clear product judgment.

Most investment mistakes come from boredom and action bias rather than a lack of IQ. Like carmakers reducing defects on an assembly line, long-term compounding comes from systematically eliminating unforced errors.

Notes from a 1955 archival interview with Benjamin Graham: why Wall Street consensus is no better than a coin flip, why mechanical strategies like dollar-cost averaging fail when human emotions take over, and why credit leverage—not high prices alone—causes market crashes.

Why chasing logo counts in AI software is misleading when inference costs pull gross margins down to ~50%, and how to separate temporary 'experimental' budgets from sticky annual contracts.

The split between 'Neobranches' (polished apps renting banking APIs with thin margins) and 'Hyperbanks' (firms that own their regulatory licenses and clear directly at the central-bank and depository level).

A clear breakdown of how reserving credit-on-UPI for RuPay pushed its share of new cards past 30%, and how the 0% MDR rule on transactions under ₹2,000 squeezes issuing bank margins.

Even if AI labs stopped training new models today, it would take years for companies to absorb what existing models can already do. The bottleneck is no longer raw model intelligence, but workflow design and human judgment.

Kris Abdelmessih breaks down position sizing under uncertainty—why even a great bet can ruin you if you size it too aggressively, and why survival always comes before maximizing returns.

How Nubank is entering the U.S. market through partner banking rails and using low-cost cross-border settlement to connect everyday retail banking with global transfers.

A sobering look at how generative AI wiped out a 40,000-person freelance writing economy in Nairobi almost overnight—and a reminder of how fragile purely transactional digital work has become.

Anthropic CEO Dario Amodei makes the case for tying frontier AI deployment speed to measurable safety benchmarks rather than racing blindly ahead.

Why public markets often price in a 15–25% discount when second-generation heirs take over from founders—and how hard it is to pass down founder-level urgency and cost discipline.

A clear look at why momentum persists across centuries of market data, and how simple index funds quietly act as long-term trend-following machines.