Oct 14, 2025

Why AI Will Create Abundance and Transform Customer Experience: Cresta CEO Ping Wu

Ping Wu, CEO of Cresta, and Sequoia’s Doug Leone discuss the transformation of contact centers with AI. They explore a dual approach, blending AI-powered human agent assistance with full automation, to meet enterprises where they are. Wu details the immense technical challenges of deploying AI at scale, from orchestrating over 20 models in real-time with sub-800ms latency to solving for legacy on-premise systems. Leone provides a framework for building AI companies at speed, arguing that value will accrue in the application layer and that we are at the beginning of an "Industrial Revolution 2.0".

Oct 13, 2025

How to build agents that take ACTION

Alex Salazar, CEO of Arcade, argues that the true value of AI is not in chatbots but in agents that can take real-world actions. He details the primary reasons agents fail to reach production—security, cost, latency, and accuracy—and introduces an "Agent Hierarchy of Needs" as a framework for building robust, production-ready agents. The talk emphasizes a critical shift from exposing raw APIs to building intention-based tools and solving the complex challenge of agent authorization through a delegated model.

Oct 09, 2025

Why Your Cloud Isn't Ready for Production AI

Zhen Lu, CEO of Runpod, discusses the shift from Web 2.0 architectures to an "AI-first" cloud. The conversation covers the unique hardware and software requirements for production AI, key use cases like generative media and enterprise agents, and the critical challenges of reliability and operationalization in the new AI stack.

Sep 30, 2025

Building an AI Physicist: ChatGPT Co-Creator’s Next Venture

Former researchers from OpenAI and Google DeepMind, Liam Fedus and Ekin Dogus Cubuk, discuss their new venture, Periodic Labs. They aim to create an 'AI physicist' by integrating large language models with real-world, iterative experiments, moving beyond simulation to solve fundamental challenges in physics and chemistry, starting with high-temperature superconductivity.

Sep 26, 2025

Richard Sutton – Father of RL thinks LLMs are a dead end

Richard Sutton, a foundational figure in reinforcement learning, argues that Large Language Models (LLMs) are a flawed paradigm for achieving true intelligence. He posits that LLMs are mimics of human-generated text, lacking genuine goals, world models, and the ability to learn continually from experience. Sutton advocates for a return to the principles of reinforcement learning, where an agent learns from the consequences of its actions in the real world, a method he believes is truly scalable and fundamental to all animal and human intelligence.

Sep 25, 2025

Juicebox: AI Agents for the Hiring Process

Co-founders David Paffenholz and Ishan Gupta share their journey building Juicebox, an AI recruiting platform. They discuss their pivot from a music app to leveraging LLMs for talent search, how they achieved product-market fit, and their vision for AI agents that automate top-of-funnel recruiting.