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Strategic insights on blockchain, AI, security, leadership, and career in an age of disruption.
Quantum Computing's Hidden Climate Opportunity
Quantum computers could revolutionize climate modeling by computing probability distributions natively, enabling predictions worth trusting—yet boards only focus on encryption threats.
Recent Essays
Crypto Settlement: Why Banks Win, Intermediaries Lose
Blockchain disruption targets clearing and settlement, not banks themselves. Firms controlling regulatory trust and technical reliability will dominate the next five years.
Your Power Law: Where AI Actually Changes Time
Pareto's 80/20 rule reveals most productivity advice optimizes the wrong things. Discover how AI agents reclaim hours by automating maintenance tasks in your time's "head."
AI Ate Entry-Level Jobs—Now We Need Apprenticeships
AI automation is eliminating the grunt work that built professional judgment in junior employees. Leaders must rebuild structured apprenticeships to develop the next generation of decision-makers.
Why AI Agents Are Making Beautiful Decks Obsolete
As AI agents become primary document readers, polished presentations lose value. Structured, machine-legible formats like HTML and Markdown now outperform designed assets.
#ai regulation
4 posts
AI Cost Reality: When Subsidies End
Compute subsidies are temporary. Learn how to build sustainable AI products that survive price increases and compete beyond today's token economics.
AI Governance: Balance Adoption and Risk
Leaders face competing pressures on AI: boards demand adoption, risk committees demand controls. Learn how to govern AI as a critical dependency, not a strategic choice.
AI Language Models: Optimizing for the Wrong Thing
Explore why unaligned AI optimization—from newsfeeds to language models—creates unintended harm at scale, and what leaders must understand about AI risk.
AI Training Data Rights: The Legal Framework We're Missing
Authors suing AI companies will likely lose, but they're exposing a critical gap: no legal framework exists for compensating data creators whose work trains billion-dollar models.