Creators

Software developer, AI educator, and founder of Dynamous AI, known for practical, hands-on YouTube tutorials on building AI agents, RAG pipelines, MCP servers, and local AI deployments. Creator of Archon, an open-source “operating system” for AI-assisted coding that manages knowledge, context, and tasks across human/agent workflows.

Science fiction author, journalist, and digital rights activist (former EFF special advisor). Writes “Pluralistic,” a daily link-aggregation blog combining tech-policy essays with curated commentary, built around his “enshittification” framework for how platforms decay as they extract value from users, business customers, then shareholders in sequence. Covers DRM/anticircumvention, antitrust and monopoly power, copyright and IP overreach, surveillance pricing, and right-to-repair.

A software engineer with over a decade of industry experience who has focused since early in the generative AI wave on practical, battle-tested patterns for AI-assisted and agentic coding. His YouTube channel and “Principled/Tactical Agentic Coding” courses cover multi-agent orchestration, spec-driven development, and autonomous (“AFK”) coding workflows built around tools like Claude Code.

Tech industry commentator and CEO of the PR firm EZPR, writing sharply critical analysis of AI industry economics, unit economics, and hype cycles. A former games/tech journalist, he has become one of the most prominent skeptical voices on generative AI’s business fundamentals, data center economics, and “the rot economy.”

Cognitive scientist, NYU Professor Emeritus, and entrepreneur who has been one of the most persistent and prominent critics of large language models and AGI-timeline hype. Argues that scaling compute and data cannot overcome deep architectural limitations of deep learning, and has authored six books including “Rebooting AI” and “Taming Silicon Valley.” Frequently responds in near-real-time to claims from labs and executives about AGI/superintelligence progress.

TypeScript educator and author of Total TypeScript — the leading advanced TypeScript course and workshop series. Known for making complex type-level concepts approachable through tips, tutorials, and interactive exercises. Active on X/Twitter (@mattpocockuk).

20-year product leader and AI strategist. Former Head of Product, Amazon Prime Video. Daily AI briefings across YouTube, Substack, and podcast. ~450k+ followers across platforms.

ML researcher at the Allen Institute for AI (Ai2) who leads post-training work and has authored prominent open-model research including OLMo, Tulu 2/3, RewardBench, Zephyr-Beta, and the Open LLM Leaderboard, and wrote the first RLHF textbook. Through Interconnects he provides technical, insider-level analysis of frontier AI lab economics, training methods, and reasoning models, positioned against industry hype. A leading voice on the open-vs-closed model ecosystem, including geopolitical dynamics.

Finance educator, former hedge fund portfolio manager, and adjunct professor at Queen Mary University of London. Known for deeply-researched, dryly humorous essays on financial history, fraud, market crises, monetary policy, and macroeconomics — skeptical, de-hyped analysis of trending financial narratives (crypto, private credit, AI-bubble talk, etc.). Publishes matching video essays on YouTube and audio episodes on the Patrick Boyle On Finance podcast, generally covering the same story on both platforms within a day of each other.

Geopolitical strategist and former Stratfor analyst. Forecasts driven by demographics, energy, and geography — argues globalization was a temporary, US-security-guarantee-dependent anomaly now unwinding, producing regional deglobalization, demographic collapse across most industrialized and Asian economies, and a wave of resource, food, and finance crises through the 2030s. Publishes near-daily video/audio analysis of current events through that framework on his own channel and podcast, and frequently appears as a guest on other shows — entries here combine both, guest appearances tagged accordingly.

An independent software engineer and open-source maintainer who blogs near-daily about hands-on LLM/AI tooling, prompt injection risks, and practical model evaluation. Known for rigorous, first-hand testing of new models and tools rather than punditry, plus a running “TIL” log of technical discoveries. His long track record building Django and Datasette gives his commentary on AI-assisted coding and data tooling particular credibility in developer circles.

A former professional Magic: The Gathering player and Jane Street trader turned full-time writer, deeply embedded in the rationalist and AI-safety-adjacent community around LessWrong. Writes some of the most exhaustive and widely-cited synthesis coverage of frontier AI model releases, lab announcements, and policy developments, blending detailed technical summary with strong, explicitly-stated opinions. His numbered “AI #NNN” weekly roundup is a fixture read by researchers, journalists, and policymakers.

Hosts the Dwarkesh Podcast, a long-form interview show featuring deeply researched conversations with frontier AI researchers, lab leaders, scientists, and historians. Known for unusually well-prepared, technically substantive interviews that probe AI capabilities, timelines, and scientific/historical topics. Named one of TIME’s 2024 most influential figures in AI.

Arvind Narayanan (Princeton CS professor, director of the Center for Information Technology Policy) and Sayash Kapoor (Princeton CITP researcher) write empirically-grounded critiques of AI capability claims and vendor hype. Authors of the 2024 book “AI Snake Oil”; their newsletter was renamed “AI as Normal Technology” in 2025 to reflect a shift toward analyzing AI as transformative-but-ordinary technology rather than existential risk or hype.

AI alignment researcher and the single most-watched AI safety communicator on YouTube — explains alignment, corrigibility, instrumental convergence, specification gaming, and existential risk from AI in accessible, technically grounded videos. Also appears on Computerphile and founded AISafety.info (Stampy), a community-maintained AI safety FAQ.

Associate Professor of Management and co-director of Generative AI Labs at Wharton (University of Pennsylvania), and author of the bestselling book Co-Intelligence. Known for the “jagged frontier” framing of AI capability — the uneven, unpredictable boundary between tasks AI handles well and tasks it doesn’t. Writes research-grounded analysis of AI’s practical impact on work, management, education, and productivity.

William S. Sims University Professor Emerita of History and Grand Strategy at the U.S. Naval War College. Historian of WWII and Cold War Asia-Pacific grand strategy — Japan/China/Russia continental-vs-maritime power dynamics, Taiwan, and the structural causes of great-power miscalculation. Publishes no channel of her own; tracked guest-only via appearances on other podcasts (most prominently the Dwarkesh Podcast) and recorded lecture series.