Mechanistic interpretability

Oct 18, 2026

A mind-expanding conversation on how models actually work | Emmanuel Ameisen (Anthropic)

Emmanuel Ameisen, an interpretability researcher at Anthropic, explains how the team looks inside models like Claude to understand how they actually think. The conversation covers why next-token prediction hides real planning and conceptual representation, why models are grown rather than built, how intermediate activations reveal structure, why anthropomorphic framing can be useful, how smooth scaling produces sudden capability thresholds, and how interpretability ties into alignment, safety, and the broader question of what these systems are.

Sep 23, 2026

🔬Bio-security is an AI Arms Race - Eric Nguyen (CEO, Radical Numerics)

Eric Nguyen, CEO of Radical Numerics, details the journey from early genome language models to Omni, a system that excels in DNA reading, writing, and reasoning. Omni outperforms specialized models in disease-variant prediction, particularly in previously challenging non-coding regions. The discussion also covers the critical need for AI-native biosecurity defenses, addressing how models can design biological sequences that evade current detection systems, and the broader vision for General Biological Intelligence.

Sep 16, 2026

The Watchdogs of AGI — Rune Kvist of AI Underwriting Company

AIUC co-founder Rune Kvist discusses their $40M Series A, emphasizing that AI adoption's biggest constraint is trust, not capability. He details AIUC-1, their quarterly-updated standard for agent security and reliability, and their expansion into model certification to bridge the trust gap between frontier labs and governments. Kvist highlights the critical role of standards and insurance (partnering with Lloyds of London) in quantifying and mitigating AI risks, from agent liability to national security concerns, and preparing for future challenges in robotics and multi-agent systems.

Jul 31, 2026

AI Security Costs Rise: Cost of a Data Breach Report & Claude Opus 5

The podcast explores key AI developments, beginning with IBM's 2026 Cost of a Data Breach Report, highlighting AI's increasing role in both cyberattacks and defense, and the economic asymmetry it creates. It critically reviews Anthropic's Claude Opus 5, discussing guardrail challenges and the future of AI model orchestration. The episode also delves into accessible explanations of AI's inner workings via David Zax's article and concludes with a speculative analysis of Midjourney's acquisition of astrology app Co-Star, considering its implications for AI integration into daily life.

Jul 27, 2026

Boris Cherny: Building Claude Code

Boris Cherny, creator of Claude Code, discusses the transformative capabilities of Opus 5, highlighting its prompt injection resistance and long-task execution. He delves into Claude Code's empirical development philosophy of "unhobbling" AI by constantly adapting to new model generations, and shares insights on how to build advanced AI products using higher-level tasks, self-verification, and dynamic workflows to orchestrate thousands of agents.

Jul 23, 2026

Coding Agents Are Secretly General Agents

Jay Hack, head of AI at ClickUp, discusses the evolution of AI from early computer vision to generalist coding agents, highlighting how 'positive transfer' makes coding an 'AGI-complete' domain. He delves into the brutal economics of AI startups facing foundation model giants, ClickUp's strategy for convergence and first-party data as a moat, and the challenges of verifiability and catastrophic forgetting. The conversation also explores LLMs at the scientific frontier, the 'car wash test' revealing limits of world models, and speculative future applications like LLM resorts and game integration.