January 2026

Peter Diamandis explores the gap between Elon Musk's vision of Universal High Income (UHI) — a world where AI and robots produce everything at near-zero cost — and the practical question of how to fund and distribute that abundance. Musk admitted on Diamandis's podcast that he doesn't know how to implement UHI and welcomed ideas. Diamandis presents Daniel Schreiber's MOSAIC Model as a compelling answer. The framework addresses the "Automation Paradox": AI unemployment differs fundamentally from traditional unemployment because AI doesn't just displace workers — it creates enormous productivity gains that can be captured and redistributed. Traditional unemployment means workers disappear with nothing replacing them; AI unemployment means productivity explodes while workers are displaced. The MOSAIC Model proposes mechanisms to capture a portion of AI-driven productivity gains and channel them into universal income without raising taxes on workers or businesses. Schreiber, CEO of Lemonade (the AI-insurance company that launched 50% off premiums for Tesla FSD drivers), brings practical business experience to the design. The piece argues that the economics of scarcity are flipping to the economics of abundance, and that the transition requires deliberate institutional design rather than hoping markets will self-correct.

Peter Diamandis shares insights from a conversation with Tony Robbins addressing the number one question entrepreneurs face: how to stay relevant when AI can do their jobs better. Robbins recounts warning a U.S. President a decade ago that 8 million truck drivers would be displaced — and being told it wouldn't happen that fast. Now it's happening in cities worldwide. The speed is the critical variable: the agricultural revolution took 7,000 years, the Industrial Revolution took 140 years, but the AI revolution will transform society within 3-10 years. Robbins identifies three essential skills for survival: Pattern Recognition (seeing what's happening before others do), Pattern Utilization (applying those insights to create value), and Pattern Creation (inventing new patterns that others will follow). He draws historical parallels to the Luddites, who rioted not because machines were bad but because 70% of jobs disappeared faster than humans could adapt. The government is too slow to respond, so individuals must take responsibility for their own retooling. The implication is that AI will become a tool for those who master pattern-thinking, rather than a replacement. The piece frames the AI revolution not as a threat to be feared but as a transformation to be navigated through deliberate skill development.

Peter Diamandis, drawing from his new book "We Are As Gods" co-authored with Steven Kotler, contends that Stewart Brand's 1968 proclamation has become measurable reality. By noon on any given day, the average person has performed feats that would have been considered biblical miracles: summoning knowledge from the ether, moving money with a gesture, speaking across continents, and parting clouds with weather apps. The core argument is that having godlike power is only half the battle — the real challenge is upgrading human consciousness and cognitive navigation systems to match accelerating technological capability. Diamandis outlines seven takeaways: (1) The failure of analogy — our brains evolved for local and linear environments, creating "cognitive vertigo" in an exponential world. (2) The importance of developing a mindset of abundance rather than scarcity. (3-7) Additional strategies for thriving amid overwhelming change. The piece serves as both a philosophical reflection and a practical guide, arguing that the gap between our technological power and our wisdom in wielding it is the central challenge of our era. The book draws on decades of research into exponential technologies and their societal implications, positioning itself as a survival guide for the Age of Abundance.

Peter Diamandis argues that to understand the future of the economy, you must stop looking at money and start looking at physics — specifically energy, which he calls the "Innermost Loop." For 4,000 years, human civilization ran on a biological engine: sunlight captured by photosynthesis, converted into food, and metabolized into muscle and cognitive output. This loop built the Pyramids and the Roman Empire but is constrained by biological limits. We are now in the midst of a phase shift to a silicon engine: sunlight or fusion generates electricity, which powers compute, which runs AI and robots, producing abundance. The key difference is efficiency — photovoltaics capture 23% of solar energy versus photosynthesis's 1%, and GPUs don't need sleep. Diamandis positions energy as the "governing prior of the Universe" — whoever controls energy controls civilization. He traces this through history: empires rose and fell on their energy access. The new loop means AI doesn't just augment human labor; it replaces biological intelligence with silicon intelligence at scale. The implication is that nations and companies that secure abundant, cheap energy will dominate the coming era, and that every industry must be rethought through the lens of energy-to-compute economics.