May 20, 2026

Inference, not prediction — Prof. Michael I. Jordan on what modern AI is still missing

Michael I. Jordan, a leading figure in machine learning and statistics, argues for reframing AI from a race for disembodied superintelligence to the design of collective economic systems. He critiques the AGI hype, advocates for integrating economic principles and robust uncertainty quantification into ML, and proposes a new intellectual framework for building technology that augments, rather than replaces, human systems.

Apr 29, 2026

Why AI Infrastructure Is Everyone's Problem Now (with Linda Haviv)

Linda Haviv discusses the evolving AI landscape, arguing that systems thinking is becoming more critical than coding. She highlights how non-linear career paths and domain-specific expertise provide a competitive edge, and explores how the democratization of technology is fueling a new wave of entrepreneurship and content creation for tech professionals.

Apr 28, 2026

AI Infrastructure, Ray, and Why Nonlinear Careers Win — with Linda Haviv

Linda Haviv discusses the modern AI landscape, emphasizing that non-linear career paths and systems thinking are now more valuable than pure coding skills. She explores how open-source technology, like the Ray framework, is democratizing AI development and closing the gap with proprietary models, and why building a personal brand through content creation is essential for career growth and community building in a rapidly evolving industry.

Apr 07, 2026

Extreme Harness Engineering for the 1B token/day Dark Factory — Ryan Lopopolo, OpenAI Frontier

Ryan Lopopolo of OpenAI's Frontier team discusses "Harness Engineering," a new paradigm where AI agents manage the entire software development lifecycle. He details an experiment building a 1M LOC product with zero human-written code, shifting the engineer's role from coding to designing systems and context for agents. The conversation covers the Symphony orchestration framework, the concept of "agent-legible" software, and the future of AI-driven development.

Mar 13, 2026

Architecture for Flow • Susanne Kaiser & James Lewis

In an interview with James Lewis, Susanne Kaiser discusses her book "Architecture for Flow," which synthesizes Domain-Driven Design, Wardley Mapping, and Team Topologies. She explains how this holistic approach helps design adaptive socio-technical systems by starting with the problem space, visualizing the value chain, and aligning team structures to the software architecture, all guided by her practical "Architecture for Flow Canvas."

Mar 07, 2026

AI Won't Replace You—But Someone Using AI Will

In this episode, Ben Lorica and Evangelos Simoudis discuss how AI is fundamentally reshaping the modern workplace. They explore the necessary evolution of knowledge work, from a focus on routine execution to problem definition and spec-driven development, and outline the critical skills professionals must cultivate—including rapid experimentation, AI agent orchestration, and systems thinking—to remain valuable and navigate a more volatile labor market.