Sep 22, 2025

The Death of Classical Computer Science • Matt Welsh & Julian Wood • GOTO 2025

Matt Welsh, former Harvard professor and AI researcher, posits that Large Language Models (LLMs) are not just tools but are evolving into new, general-purpose computers. He argues this signifies the "death of classical computer science," as direct, natural language problem-solving will replace human-written code. This shift promises to democratize computing, moving beyond a "programming priesthood" to empower everyone, while also raising critical challenges regarding job displacement, societal equity, and our adaptation to this powerful technology.

Sep 10, 2025

Chris Dixon on How to Build Networks, Movements, and AI-Native Products

a16z partners Chris Dixon and Anish Acharya discuss the exponential forces shaping technology, including network effects, composability, and Moore's Law. They explore how these principles apply to the age of AI, covering strategies for founders like 'come for the tool, stay for the network,' the nature of defensibility, investing in movements, the shift to native AI platforms, and the crucial role of open-source AI.

Aug 28, 2025

The $10 Trillion AI Revolution: Why It’s Bigger Than the Industrial Revolution

Sequoia Capital's Konstantine Buhler presents an investment thesis on the AI-driven "Cognitive Revolution," framing it as a transformation larger and faster than the Industrial Revolution. The core of the thesis is the $10 trillion opportunity in automating the US services market and the shift in work from certainty to high leverage. Buhler outlines five current investment trends, including real-world validation over academic benchmarks and compute as the new production function, and five future themes Sequoia is betting on, such as persistent memory, AI-to-AI communication, and AI security.

Aug 15, 2025

The Current Reality of American AI Policy: From ‘Pause AI’ to ‘Build’

a16z's Martin Casado and Anjney Midha detail the dramatic shift in U.S. AI policy from a 'pause AI' stance, fueled by doomerism and flawed analogies, to a pro-innovation 'win the race' strategy. They discuss how China's progress shattered illusions of a U.S. lead, the strategic business case for open source AI, and the pragmatic promise of the new AI Action Plan.