WSJ: “Everyone’s talking about an AI bubble. For the bulls, that is proof that there is no such thing. If, the argument goes, people really believed prices were wildly overinflated, they would sell and it would pop. How can there be a bubble if everyone knows it? As a natural contrarian, I like the idea. It bothers me when I’m part of the crowd. But it is simply wrong to think a bubble can’t continue to inflate amid widespread warnings. History proves that—and psychology and financial theory explain why…The only absolute proof of a bubble comes when it bursts.”
NYTimes: “India has a teeming population of able-bodied workers, tens of millions more than its employers can accommodate. Many other countries have the opposite problem: more jobs than workers. Today, across the Indian government and business sector, a movement is gaining steam to begin exporting more workers. The idea, which economists call labor mobility, is to connect young Indians to companies in places with shrinking populations where labor shortages are holding back growth. The challenge for India and its partners overseas is a growing opposition to immigration in many countries. Officials are trying to craft policies to make it easier to move Indian workers abroad swiftly, while ensuring they have viable paths home.”
FT: “To build an AI-powered phone outside of Apple’s walls requires Google’s infrastructure. Android is the only commercially available, open source mobile operating system available. Ive’s background at Apple and OpenAI’s rivalry with Google may make this difficult to swallow but it would be the fastest, best way for Ive to make a return on OpenAI’s investment. Producing an AI phone is the tallest order in tech since 2007. But in order for AI hardware to succeed and deliver on the promise of inserting the technology in everyday life for billions of people, it must fit into life as we know it. In other words, instead of taking months to build something that fails to complement or compete with the smartphone, OpenAI needs to engineer its next iteration.”
SaaStr: “We’re sitting on a really big problem in SaaS nobody wants to talk about much. The exits … are no more. For years, we had a predictable exit playbook: build a solid SaaS company to $20M-$50M in ARR, maintain decent growth, and … the buyers would come. Private Equity would write checks. Strategic acquirers would see you as a tuck-in. VCs knew where to skate the puck. The ecosystem worked. That playbook has broken down in the Age of AI. Revenue appears less durable when AI puts every deal into play, and growth can’t be counted for decades any longer. So the exits are … in many cases … gone.”
