Daily Brief

Ali Ghodsi never wanted the CEO job. In 2015, Databricks had a wildly successful open source project, $1.5 million in revenue, and a board quietly interviewing other candidates behind his back. He got the seat as a trial run. They didn't even give him a CEO salary. When I had Ben Horowitz on this podcast and asked him who the best CEO in Silicon Valley is outside his own portfolio, he didn't hesitate. He said Ali. We get into how he actually runs the place: find the single biggest bottleneck in the company, then put an absurd, disproportionate amount of attention on it for two or three years.

John Ousterhout, Stanford Professor and author of A Philosophy of Software Design, turns our attention to the evolving nature of AI networking workloads and why traditional protocols like TCP and RDMA are becoming bottlenecks in modern data center environments! The Shift in Workloads Historical context: AI traffic was dominated by massive, long-running transfers (gigabytes of gradients), where throughput was the primary metric (2:19-2:42). Modern AI: Workloads, especially inference and agentic applications, now rely on frequent, small coordination messages (e.g., KV cache lookups, barrier sy

Ignacio Martinez registered the domain for this workshop on the Saturday before he gave it, and then asked the room not to request the biggest machines on offer, because he was paying for everyone's GitHub Codespace out of his own pocket. That improvisation sits oddly beside the argument underneath it, which is one of the more carefully built cases for harness engineering here. A language model, he says, is the frozen part of the reasoning. The weights do not change, you rent them, and you have no say in what you are offered. Everything you control lives in the layer around it. So an agent is

A beautiful puzzle that eluded AI, and the intuition it requires. Check out our virtual career fair: https://3b1b.co/talent See new videos early: https://3b1b.co/support An equally valuable form of support is to simply share the videos. Home page: https://www.3blue1brown.com Evan Chen also wrote up nice solution notes for this problem, along with all the others on that year's test. https://web.evanchen.cc/exams/IMO-2025-notes.pdf The channel Dedekind Cuts has a video about this solution: https://youtu.be/fgXg9CdCDcs Timestamps: 0:00 - The one that AI missed 4:09 - Problem statement 6:45 - F

Full video: https://youtu.be/Nbwv5wHQoj0

Full episode: https://www.youtube.com/watch?v=6AgOfiZOWiY Me on twitter: https://x.com/dwarkesh_sp

Raindrop is building the safety layer for AI agents. As agents get more capable and take on more complex work, Raindrop detects when they go wrong in production, from failed tool calls and hallucinations to problems companies didn’t even know to look for. They’re already used by companies including Vercel, Clay, Framer, and Speak, and just raised a Series A, bringing their total funding to $50 million. In this episode of Founder Firesides, the founders sat down with YC's Diana Hu to share how a tool they originally built to debug their own coding agent became the company, why better AI agents

Kastle is building the AI employee for banks. Their agents automate operations across mortgage servicing, consumer lending, and other parts of the bank back office. Today they work with 10 of the top 25 mortgage servicers and have processed more than $2 billion in transactions using AI agents. They just raised a $24M Series A, two years after going through YC. In this episode of Founder Firesides, Kastle founders Rishi and Nitish sat down with YC's Diana Hu to share how they went back to zero one month before Demo Day and found their way to one of the hardest places to deploy AI: banking. The

Sponsorship and business inquiries: business@latent.space

法治建设，它不可能一蹴而就，无法毕其功于一役，法治的每一个进步背后都有许多沉甸甸的故事，这些故事不应该被人遗忘，因为牢记历史就是为了避免重蹈覆辙。 参考文献： 1.陈永生，我国刑事误判问题透视———以20起震惊全国的刑事冤案为样本的分析，中国法学2007年第3期 2.对我国死刑复核程序之检讨———以中国古代及国外的死刑救济制度为视角，陈永生，比较法研究2004年第4期。