Aug 27, 2026

Rethinking Legacy Data Infrastructure with Eon Co-Founders Ofir Ehrlich and Gonen Stein

Eon co-founders Ofir Ehrlich and Gonen Stein discuss the critical role of data as a protective moat in the AI era, exemplified by Google's purchase of Spirit Airlines' data. They explain how Eon addresses the challenges of scattered enterprise data by providing tools for mapping, classification, and secure access, enabling its use in AI workflows. The conversation also delves into the emerging threat of autonomous AI agents with legitimate system permissions, the fundamental shifts required in enterprise data infrastructure, and how the rapid, fear-driven adoption of AI contrasts sharply with the slower cloud migration era.

Aug 26, 2026

The Death of Developer Advocates — Stephanie Jarmak, Sourcegraph

Stephanie Jarmak argues that Developer Relations (DevRel) isn't dead, but its audience has shifted to include AI agents. She introduces the "Agent Advocate" role, focusing on measuring agent experience (e.g., through CodeScaleBench), optimizing for "Generative Engine Optimization" (GEO), and adapting traditional DevRel principles like enablement and community for this new user. The core message is that designing for agents, like a curb cut, ultimately improves the experience for all human developers.

Aug 26, 2026

🔬 The Physical World Is More Forgiving Than You Think — Anima Anandkumar, Caltech

Anima Anandkumar discusses her vision for AI in science, moving beyond language models to apply machine learning to the physical world. She introduces neural operators, especially Fourier neural operators, as a solution to data scarcity and resolution challenges in domains like weather, climate, and fusion. These models integrate physical constraints and data to achieve unprecedented speed and accuracy, even on consumer hardware, enabling capabilities from early hurricane prediction to digital twins for fusion reactors and inverse design for advanced materials. The conversation highlights the need for principled AI design for scientific discovery and advocates for distinct regulatory approaches for AI in science.

Aug 26, 2026

Knowledge Systems: The New GTM Stack — Jeffrey Wang, Exa

Jeffrey Wang, co-founder of Exa, details how "go to market" (GTM) is transforming into an AI engineering problem. He showcases Exa's agent-first approach, using tools like an ICP dashboard for market intelligence and a personal AI clone (Jeffbot) to automate and optimize sales, emphasizing the need for robust APIs and arbitrarily customizable systems in this new AI-driven landscape.

Aug 26, 2026

The mathematics of AI uncertainty

Zoubin Ghahramani, a leading researcher at Google DeepMind and professor at Cambridge, argues that incorporating uncertainty is a missing piece for ever-improving AI. He discusses the critical difference between correctness and confidence in AI, tracing the historical evolution of probabilistic models from early neural networks to modern Bayesian approaches. Ghahramani highlights how current large language models often 'fake' uncertainty and explores successful implementations in areas like weather forecasting and AlphaFold, ultimately advocating for architectural innovations over pure scale to build more robust, trustworthy, and human-aligned intelligent systems that understand their own limitations.

Aug 26, 2026

The State of AI: Models, Moats, and the Consumer Renaissance

Anish Acharya and Jen Kha delve into the evolving AI landscape, dissecting the model layer with its emerging multiple winners and the strategic choice between frontier and open-weight models. They explore how the application layer captures value through model aggregation and specialization, ultimately ushering in a renaissance for consumer AI with personal agents, coding tools, and new economic models, urging founders to think big.