Long-form interviews and conversations with tech, AI, and finance leaders (30min+)
Mercado Libre is the only public company to deliver 30%+ revenue growth for 27 consecutive quarters, yet trades at its lowest valuation ever despite expanding operating profits 30-fold over five years while the stock rose only 30%, creating a potential opportunity as Latin American e-commerce penetration sits at just 14%.
Cancer is not merely a mechanical failure but an inevitable evolutionary phenomenon where individual cells defect from multicellular cooperation, operating on timescales orders of magnitude faster than species evolution and creating recursive layers of cooperation and defection within the body.
Amazon Principal Engineer Al Harris introduces Spec-Driven Development through Kiro, an agentic IDE that replaces unstructured 'vibe coding' with a formal workflow converting prompts into EARS-format requirements and property-based tests, enabling FAANG-scale reliability in AI-assisted development.
The host shares a cautiously optimistic update on his son's cancer treatment, which achieved remission with help from AI-suggested minimal residual disease testing, while offering practical advice for leveraging AI in high-stakes scenarios and tempering expectations about Claude Opus 4.5 constituting AGI.
Artificial Analysis co-founders George Cameron and Micah Hill-Smith detail their journey from a side project to becoming the presumptive independent standard for LLM evaluation, revealing how they maintain objectivity through 'mystery shopper' protocols while navigating the shift from an OpenAI-dominated market to a fragmented, globally competitive landscape.
Kevin Madura from AlixPartners demonstrates how DSPy shifts AI development from manual prompt engineering to declarative programming, enabling developers to build modular, optimizable Python systems that treat LLMs as first-class citizens while remaining robust to model changes.
Robert Brennan outlines the evolution from single AI coding agents to parallel agent orchestration, demonstrating how breaking massive refactoring tasks into coordinated sub-tasks can deliver 30x productivity improvements on tech debt remediation while maintaining essential human oversight.
Michael Bloomberg shares his journey from a laid-off Salomon Brothers partner to building a financial data empire, emphasizing that success comes from solving real problems, outworking competitors, and taking care of people—principles he applied equally to business, 12 years as NYC Mayor, and giving away over $20 billion in philanthropy.
SallyAnn DeLucia and Fuad Ali from Arize demonstrate how iterative "prompt learning"—combining automated evaluations with human explanatory feedback—can improve AI agent performance by 15% without fine-tuning, outperforming traditional optimization methods while reducing costs significantly.
Peter Wielander demonstrates how Vercel's open-source Workflow DevKit transforms local AI agents into production-grade systems by wrapping AI SDK code in durable, retryable workflows with minimal refactoring, enabling automatic observability and resumable streams without managing queues or databases.
![Claude Agent SDK [Full Workshop] — Thariq Shihipar, Anthropic](https://i.ytimg.com/vi/TqC1qOfiVcQ/hqdefault.jpg)
Anthropic's Thariq Shihipar introduces the Claude Agent SDK, which packages the Claude Code architecture to build autonomous agents using a 'bash is all you need' philosophy, leveraging Unix primitives and dynamic code generation instead of rigid predefined workflows.
Ryan Kidd of MATS discusses high uncertainty around AGI timelines (median 2033), the paradoxical state of AI safety where frontier models display both surprising ethical alignment and concerning deception capabilities, and why MATS employs a portfolio strategy to develop talent across diverse research agendas—including long-term bets that could be compressed by future AI labor.