John Schulman on dead ends, scaling RL, and building research institutions

Simon Eskildsen on scaling Shopify, building turbopuffer, and the future of databases

Sualeh Asif (Co-Founder of Cursor) sits down with Simon Eskildsen (CEO of turbopuffer) to discuss scaling Shopify through flash sales, why a new database company emerges every 15 years, and what makes a P99 engineer.0:00 - Scaling Shopify through flash sales and outages7:11 - How the Shopify infrastructure team evolved8:13 - How top infrastructure teams collaborated in the 2010s10:35 - Engineering principles from Logrus and on-call17:38 - The story behind Simon’s famous-ish blog, Napkin Math23:05 - Why new database companies keep winning32:21 - How Simon became a fan of databases35:45 - AI coding, and where agents still fail38:44 - What it would take for turbopuffer to become Google-scale42:10 - Hiring P99 engineers in the AI era48:45 - What's next for databases

John Schulman on dead ends, scaling RL, and building research institutions

A conversation with John Schulman on the first year LLMs could have been useful, building research teams, and where RL goes from here. 00:00 [https://www.youtube.com/watch?v=29BYxvvF1iM] - Speedrunning ChatGPT 09:22 [https://www.youtube.com/watch?v=29BYxvvF1iM&t=562s] - Archetypes of research managers 11:56 [https://www.youtube.com/watch?v=29BYxvvF1iM&t=716s] - Was OpenAI inspired by Bell Labs? 16:54 [https://www.youtube.com/watch?v=29BYxvvF1iM&t=1014s] - The absence of value functions 18:23 [https://www.youtube.com/watch?v=29BYxvvF1iM&t=1103s] - Continual learning 21:09 [https://www.youtube.com/watch?v=29BYxvvF1iM&t=1269s] - Brittle generalization 24:05 [https://www.youtube.com/watch?v=29BYxvvF1iM&t=1445s] - Co-training generators and verifiers, GANs 27:06 [https://www.youtube.com/watch?v=29BYxvvF1iM&t=1626s] - John’s personal use of AI for research 28:54 [https://www.youtube.com/watch?v=29BYxvvF1iM&t=1734s] - Day in the life 33:01 [https://www.youtube.com/watch?v=29BYxvvF1iM&t=1981s] - Slowdowns in consequential ML ideas 36:21 [https://www.youtube.com/watch?v=29BYxvvF1iM&t=2181s] - "Peer review" within the labs 39:19 [https://www.youtube.com/watch?v=29BYxvvF1iM&t=2359s] - Distribution shift in researchers 43:33 [https://www.youtube.com/watch?v=29BYxvvF1iM&t=2613s] - Future of RL 45:33 [https://www.youtube.com/watch?v=29BYxvvF1iM&t=2733s] - Will the labs coordinate if the world needs them to? 44:46 [https://www.youtube.com/watch?v=29BYxvvF1iM&t=2686s] - Forecasting ills in AGI and engineering 47:53 [https://www.youtube.com/watch?v=29BYxvvF1iM&t=2873s] - Thinking Machines

Patrick Collison on programming languages, AI, and Stripe's biggest engineering decisions

Michael Truell (CEO of Cursor) sits down with Patrick Collison (CEO of Stripe) to discuss programming languages, the role of AI in programming, and building long-lasting software. 00:15 [https://www.youtube.com/watch?v=motX94ztOzo&t=15s] Why Patrick wrote his first startup in Smalltalk 03:35 [https://www.youtube.com/watch?v=motX94ztOzo&t=215s] LISP chatbots 06:09 [https://www.youtube.com/watch?v=motX94ztOzo&t=369s] Good ideas from esoteric programming languages 09:12 [https://www.youtube.com/watch?v=motX94ztOzo&t=552s] Brett Victor and Dynamicland 16:37 [https://www.youtube.com/watch?v=motX94ztOzo&t=997s] Programming human organizations 20:28 [https://www.youtube.com/watch?v=motX94ztOzo&t=1228s] A codebase's "Big Bang" moment and MongoDB 25:49 [https://www.youtube.com/watch?v=motX94ztOzo&t=1549s] Rewriting Stripe 32:00 [https://www.youtube.com/watch?v=motX94ztOzo&t=1920s] How do you, Patrick Collison, use AI? 38:25 [https://www.youtube.com/watch?v=motX94ztOzo&t=2305s] Changes to GDP/TFP 41:56 [https://www.youtube.com/watch?v=motX94ztOzo&t=2516s] Programming human biology 46:10 [https://www.youtube.com/watch?v=motX94ztOzo&t=2770s] Unexpected beneficiaries of AI

Training superhuman coding models at Cursor

What does it really take to train an AI to write great code? In this roundtable conversation, some of the founders and researchers at Cursor explore the process of building superhuman AI coding agents — from infinite context models and the best rewards to real-time RL and scaling to millions of environments.This is an inside look at some of the work behind Cursor and what AI-assisted coding might look like in the future.