A strange mismatch has taken shape around artificial intelligence. At conferences and in interviews, the people building AI repeat the same urgent concerns: power is tight, compute is stretched, and expansion is hitting physical limits. Yet, everyday use tells a completely different story. When people open AI tools today, they
Some arrangements, once they are put into operation, no longer treat exit as a reversible move. Not because departure is forbidden, but because returning after a position is lost becomes prohibitively expensive. Power purchase agreements extend across decades. Transformer orders sit in queues measured in years. Grid connection permits, once
Not all AI scales by code. Some of it scales by permits, steel, and time. Sequence Cannot Be Skipped AI is often discussed as software, but parts of its development now resemble heavy industry. Not in appearance, but in constraint. Progress is no longer gated by models alone, but by
Markets continue to rely on familiar signals such as growth, margins, execution, and competitive position. What has become less stable is the context in which these signals are interpreted. Increasingly, they are assessed alongside constraints that sit outside the firm’s control, and policy-driven uncertainty is one of them. The
The Supreme Court case over Trump’s emergency trade powers is not only about tariffs. It is about whether temporary legal tools can be converted into standing economic policy. At stake is the interpretation of the International Emergency Economic Powers Act, or IEEPA, a statute passed in 1977 to give
Most discussions about AI still begin with capability. Accuracy improves. Reasoning lengthens. Benchmarks move. In deployment, capability is rarely the binding constraint. Systems using models of similar maturity often grant AI very different roles. Some allow continuous autonomous decisions. Others restrict AI to advisory functions, even when performance appears sufficient.
Most public conversations about AI still begin with capability. Model size, benchmark scores, reasoning depth, and the pace at which new thresholds are crossed form the dominant vocabulary. Progress is framed as something that can be measured, compared, and ranked. When Ren Zhengfei spoke with ICPC contestants at Huawei’s
Alpha Arena, at first glance, resembled a familiar experiment. Six large language models were each given $10,000 and two weeks to trade crypto perpetual futures. Some ended with gains, others with significant losses. Qwen and DeepSeek finished near the top, while GPT-5 and Gemini ended deep in the red.
Florida, 2025. A driver rear-ends another vehicle while Autopilot, part of Tesla’s Full Self-Driving (FSD) system, is engaged.His hands are on the wheel. The system does not issue a takeover alert. The court assigns Tesla 33 percent of the liability. The ruling is not about whether the system
Forecasts for AI’s contribution to global GDP cluster between fifteen and twenty trillion dollars by 2030. The number shifts from report to report. The assumption beneath it does not. Each projection treats AI as if it will scale the way software has always scaled. Elon Musk often talks about
You hold Bitcoin. So does Elon Musk. His companies sit on more than 20,000 of them. But the same coin is not the same thing in your hands and his. Not because you disagree on where it's headed, but because you're using it for different
When Gemini’s big update landed, the reactions surfaced in a familiar pattern. People didn’t just celebrate; they moved. Confidence shifted, curiosity spiked, timelines filled with screenshots and first impressions. Some even announced they were switching models. Whether they stay or drift back isn’t the point. The behavior
Protocol Hegemony
A field note on liquidity, standards, and the new meaning of stability 2024 was supposed to be the year contradictions caught up with America. Inflation remained stubborn despite aggressive rate hikes. The federal deficit ballooned past $1.8 trillion. Political dysfunction reached levels that would trigger capital flight in any
AI Economy
AI Economy
The Infrastructure of Dependency Novelty fades faster than infrastructure. What felt revolutionary in 2023 had become routine by 2025. Three out of four knowledge workers used AI tools daily, and nearly half had adopted them within months [1]. The excitement of early experimentation settled into expectation. Automation ceased to feel
AI Economy
The Psychological Infrastructure of Acceleration A day begins with a question entered into a chatbot. The response arrives within seconds, formatted and confident. A designer uses AI to generate three variations of a layout in the time it once took to sketch one. A programmer watches code appear line by
AI Economy
How Technology Forces Society to Rebuild By the mid-1840s, Britain had caught railway fever. Parliament approved more than two hundred new companies in a single year, sketching lines that together would stretch nearly 10,000 miles [1]. With only a tenth of the price required up front, clerks and schoolteachers
Global Liquidity
The Mirage of Global Liquidity and What It Reveals About Our Time In recent years, a kind of brightness has spread through economies and cities alike. Prices climb across markets, new fortunes appear overnight, and the tone of daily life carries an ease once rare. The movement feels constant, though