Sana

At Sana, partner is the word we use for our customers. We mean it literally. They shape the product as much as they use it, and the relationship doesn't end at go-live. That's where it starts. Here's what that looks like, from the teams using Sana Learn every day. Read more partner stories: https://sanalabs.com/products/sana-learn/customer-stories Book an intro of Sana Learn: https://sanalabs.com/products/sana-learn/book-intro

Economist and writer Tyler Cowen joins Sana founder Joel Hellermark for a wide-ranging conversation on how AI’s impact may arrive more slowly in the macro data than its capabilities suggest, and why that does not mean the transformation will be small. Tyler argues that the actual bottleneck is adoption: organizations redesigning work, workers learning new roles, institutions overcoming inertia, and societies finding ways to turn new knowledge into real-world progress. Coding is already changing, bioscience may be AI’s next great frontier, and the most important measure of AI may not be GDP growth but what life feels like 30 years from now. Topics covered: Why AI productivity gains are still hard to see in the macro data The human and institutional bottlenecks slowing AI adoption Why the AI revolution may unfold sector by sector India, startups, and the advantage of starting from scratch What becomes valuable when intelligence becomes abundant The future of jobs, initiative, charisma, and human trust Why AI could transform bioscience before it transforms GDP Tyler’s decision to reallocate his own career around AI How Tyler uses frontier models to learn, travel, and think Why a positive vision for AI matters How to identify talent before everyone else does The Beatles, creative friction, and what makes great groups work AI, architecture, beauty, and the case for new aesthetics Timestamps (00:00) Living in the pre-AI and post-AI worlds (00:25) Why AI has not shown up in productivity data (01:40) The human bottleneck and institutional inertia (04:06) Call centers, agents, and slow sector-by-sector adoption (05:12) Why India may become an AI implementation leader (06:50) What becomes valuable when intelligence gets cheap (09:17) Electricity, growth statistics, and measuring AI’s real impact (12:11) Initiative, charisma, and the future of human work (14:33) Diminishing returns to intelligence and the bottleneck of experiments (17:12) How companies will actually adopt AI (18:53) Coding, bioscience, and curing disease (20:17) Why Tyler is changing his own career (24:01) How Tyler uses AI models in daily life (26:20) Training AI with a positive vision (29:15) How Tyler spots exceptional talent (32:21) Great groups, the Beatles, and creative friction (37:00) New aesthetics and the crisis of ugly buildings (43:41) Rapid-fire questions on books, economics, and the future About Strange Loop Strange Loop is a podcast about how artificial intelligence is reshaping the systems we live and work in. Each episode features deep, unscripted conversations with thinkers and builders reimagining intelligence leadership, and the architectures of progress. The goal is not just to follow AI’s trajectory, but to question the assumptions guiding it. Subscribe for more conversations at the edge of AI and human knowledge.