Who I Follow: Top Ten
I spend several hours a day trying to keep up with what’s going on in the parts of AI that I’m interested in. It’s a ridiculous amount of work: I don’t recommend it unless you’re doing something silly like writing a newsletter about AI.
But if you’d like to keep up with AI without spending your entire life on it, I have advice about who to follow. My recommendations center on the areas I’m most interested in: AI safety and strategy, capabilities and evaluations, and predicting the trajectory of AI.
Let’s start with the top 10.
Zvi Mowshowitz
Substack: Don’t Worry About the Vase
Best for: comprehensive coverage, opinionated insight
Example: AI #163: Mythos Quest
If I could only follow one person, it would unquestionably be Zvi. He’s comprehensive in his coverage and has consistently solid insight into everything that’s happening in AI.
Zvi has one huge downside: he’s staggeringly prolific. In the first half of April he posted 11 times, for a total of about 97,000 words (roughly a novel). I read everything he writes because I’m insane, but I recommend you just skim his posts looking for the most interesting parts.
AI Futures Project
Substack: AI Futures Project
Best for: epistemically rigorous predictions
Example: AI-2027
The AI Futures Project is best known for AI-2027, a scenario of how AI might unfold over the next few years. They are epistemically rigorous and very thoughtful in how they approach some very hard questions. By far the best source of useful predictions about where we’re headed.
Jack Clark
Substack: Import AI
Best for: weekly analysis of a few topics
Example: Import AI 452
Jack (who in his spare time runs the Anthropic Institute) writes an excellent weekly newsletter. He doesn’t try to be comprehensive, but picks a few papers or topics each week to go deep on. Excellent curation, outstanding analysis.
Dean Ball
Substack: Hyperdimensional
Best for: Insightful analysis of AI progress and strategy
Example: On Recursive Self-Improvement (Part I)
Dean is an insightful writer who describes his focus as “emerging technology and the future of governance”. He has perhaps thought harder than anyone about how to integrate transformative AI into a classical liberal framework, as well as how government should and shouldn’t manage AI.
Ryan Greenblatt
Less Wrong: Ryan Greenblatt
Best for: deep technical analysis of AI capabilities and progress
Example: My picture of the present in AI
Ryan’s an AI researcher and prolific writer with deep insight into the technical side of AI. I appreciate both his technical understanding of capabilities as well as his willingness to make informed guesses and extrapolations.
80,000 Hours podcast
80,000 Hours podcast
Best for: well-curated interviews
Example: Ajeya Cotra
80,000 Hours is best known for giving career advice to people who want to help solve the world’s most pressing problems. But on the side, they run an excellent podcast. The guests and topics are well-chosen and I appreciate that they not only provide a transcript, but also a detailed summary of the interview. The world would be a better place if every podcast provided such comprehensive supplementary materials.
Dwarkesh Patel
Substack: Dwarkesh Patel
Best for: long, well-researched interviews
Example: AI-2027 with Daniel Kokotajlo and Scott Alexander
Dwarkesh is an outstanding interviewer who clearly does extensive preparation before each interview. He gets excellent guests and makes the most of them, although his interviews often run very long. Also, his beard is magnificent.
Anton Leicht
Substack: Threading the Needle
Best for: US and global AI politics
Example: Press Play to Continue
I don’t always agree with Anton, but I always come away from his writing feeling smarter about something important. He occupies an interesting niche: neither blow by blow political news nor abstract political philosophy, but rather thoughtful analysis of current political currents, with solid strategic advice.
Transformer
Substack: Transformer
Best for: broader coverage of AI
Example: April 10 Transformer Weekly
Transformer produces a weekly newsletter as well as articles on particular topics. I particularly like their broad coverage: they often include news that many of my other feeds don’t. The newsletter is always good, as are some of the articles.
Epoch AI
Substack: Epoch AI
Best for: hard data on industry trends
Example: The Epoch Brief—March 2026
Epoch’s a fantastic source for more technical trends: GPU production, compute usage during training, capability gaps between open and closed models, etc.