Long-form interviews and conversations with tech, AI, and finance leaders (30min+)
Trust in American society has collapsed from roughly 50% to 33% since the 1970s, driven by the erosion of 'mangrove' institutions—such as shame, local media, and elite accountability—that once filtered toxins and buffered social conflict, compounded by social media's disintermediation and failures of governance to deliver competence and fairness.
Healthcare complexity stems from WWII-era employment insurance models and market failures, but leaders are simplifying the system through patient-centered operational design, AI-powered clinician efficiency tools, and nonprofit utility structures that dramatically reduce costs of essential medicines.
Panelists at the Stanford Leadership Forum debate AI's labor impact, with predictions ranging from gradual task automation over the next five years to majority workforce displacement within three decades, while current payroll data shows minimal displacement but significant anxiety among early-career workers.
A panel of media experts and policymakers argues that social media algorithms designed to maximize engagement through negative emotions have created the worst epistemic crisis in generations, fundamentally rewiring democratic discourse by privileging distraction and rage over truth and shared reality.
Academic and business leaders discuss navigating unprecedented policy uncertainty, noting that while financial markets remain calm, text-based uncertainty indicators have hit historic highs since 2025, requiring leaders to focus on structural trends rather than temporary government incentives and engage only on social issues core to their business purpose.
OpenAI's missed user and revenue targets have sparked IPO concerns and internal leadership tension, but recent product improvements with ChatGPT 5.5 may give them an edge over Anthropic's struggling Opus 4.7 in the critical coding market. The entire sector faces severe power and compute constraints that favor hyperscalers while driving the need for algorithmic innovations like model pruning to meet exploding demand.
Panelists debate whether Erika Kirk should remain CEO of Turning Point USA following her husband Charlie Kirk's assassination, as she faces conspiracy theories and intense scrutiny while defending herself at the White House Correspondents Dinner.
AI companies are growing three times faster than traditional SaaS but face unique pricing challenges due to unpredictable compute costs and razor-thin margins, requiring a shift from static subscription models to flexible hybrid pricing that prioritizes rapid iteration and customer-perceived value over technical metrics.
Peterson contrasts Freudian repression with Piagetian coordination to argue that psychological health emerges from organizing motivations into functional abstractions rather than fighting social constraints. He contends that controlling your mind requires navigating society as a complex dance rather than escaping a prison, while defining mental health as movement toward an ideal rather than mere normality.
Kyle Corbitt explains that unlike supervised fine-tuning (SFT), which destructively overwrites model weights and causes catastrophic forgetting, reinforcement learning (RL) optimizes performance by minimally adjusting logits within the model's existing reasoning pathways—delivering higher performance ceilings and lower inference costs for specific tasks, though frontier models may still dominate creative domains.
This workshop demonstrates how to bridge the gap between AI prototypes and production systems using Brain Trust's observability platform, featuring Trainline's experience deploying multi-agent AI applications serving 27 million users.
New York Times book critics Gilbert Cruz, Tina Jordan, and Dwight Garner reflect on two decades of literary evolution, tracing how memoir scandals, dystopian YA blockbusters, Scandinavian crime waves, and the autofiction revolution reshaped reading habits and publishing trends.