AI

Is AI Making Us Give Up Too Soon? What a 1,222-Person Study Revealed In short: A new randomized study (N = 1,222) shows that AI assistance can improve performance in the moment, while reducing independent performance once AI is removed and increasing how often people give up. The strongest negative effect appears in users who ask AI for direct answers. The fix is not to stop using AI, but to change when you bring it in. Ten minutes with an AI assistant. That is all it took, in a new randomized study of 1,222 people, for participants to perform worse on the next problem without AI — and to give up on that problem more often. Not because they were lazy. Because they had stopped expecting hard things to feel hard. This is the second time in a year that careful research has pointed at the same shape of risk. The familiar version of the question is whether AI is making us lazy. Every new tool brings a version of this worry. Calculators made people do less mental arithmetic. Search engines made people remember less. Navigation apps made people worse at finding their way around. ...

Apps may fade into the background. Software won’t. Wall Street has a new consensus: AI is about to kill the software industry. Software stocks are down nearly 30% since the start of the year; pundits call it the SaaSpocalypse. But the story is wrong. AI is rewriting who builds software and how we pay for it—not eliminating it. This piece looks at why the real moats (data, workflows, habits) are getting deeper, how “Software as a Service” is turning into “Service as Software,” and what that means for builders and buyers. Two 19-year-old high schoolers built an AI calorie-tracking app called Cal AI that brought in over $30 million a year; it was recently acquired by MyFitnessPal. The deal size was not disclosed, but the two clearly came out on top. On another front, Cursor, the fastest-growing AI coding company in history and less than five years old, was reported in February to have passed $2 billion in annualized revenue. Whether we talk about AI companies that build apps or the AI-powered apps already in the world, the outlook seems bright. ...

Over the past two decades, something subtle but profound has been happening in the history of war. Wars are ending less often with grand campaigns or sweeping territorial conquest. Increasingly, they conclude with the physical removal of a single critical individual. At the same time, two different models of conflict have been unfolding in parallel. One resembles traditional industrial-age warfare — armored divisions, territorial lines, attrition. The other looks entirely different: precise, intelligence-driven, node-focused. I do not study warfare professionally. My work focuses on how AI reshapes organizations. But it is impossible to ignore how similar structural shifts are now transforming conflict. When organizational forms change, warfare changes with them. And once the efficiency gap becomes clear, the shift is irreversible. From a purely operational standpoint, the performance difference between these two paradigms is staggering. What follows is not a moral argument about right or wrong. It is an attempt to describe a transformation in the structure of power. From “Destroying Systems” to “Deleting Nodes” Modern military operations increasingly follow a pattern: Persistent surveillance → continuous modeling → anomaly detection → instantaneous strike. ...

A Critical Analysis of Citrini Research’s Viral 2028 Crisis Scenario The financial world is currently grappling with a thought experiment that feels uncomfortably close to reality. In a viral research piece titled “THE 2028 GLOBAL INTELLIGENCE CRISIS” published by Citrini Research (co-authored with Alap Shah), the authors paint a chilling picture: unemployment at 10.2%, the S&P 500 down 38% from its October 2026 peak, and an economy where AI’s productivity gains have paradoxically triggered the deepest structural crisis since the Great Depression. Written as if from June 2028, this speculative scenario has exploded across investment communities, racking up millions of reads within days of publication. What makes it particularly unsettling is not its dystopian framing, but its logical coherence. This isn’t science fiction—it’s financial analysis written in the language of cause and effect. Source: Citrini Research - THE 2028 GLOBAL INTELLIGENCE CRISIS The Core Mechanism: A Self-Reinforcing Doom Loop At the heart of Citrini’s crisis scenario lies a deceptively simple feedback loop: AI capability improves → Companies lay off workers → Consumer spending falls → Corporate profits compress → Companies buy more AI to cut costs → AI capability improves ...