Sparse Notes

Most conversations about making agents better are really conversations about making models better. Alex Krentsel — a Berkeley systems PhD student working with Martin Casado and Ankur Goyal — spends this Latent Space episode arguing the opposite: the model is fine, and the leverage now lives in the harness, the “body we provide to the brain.” Exo, the project he introduces, is an agent that can safely edit every aspect of itself at runtime....

Weekly Paper Notes — one of the top picks from the 2026-08-22 CS paper digest. Area: Operating Systems / Serving Systems. Authors: Chaokun Chang, Yukun Zhou, Kaihua Fu, Dakai An, Tianyu Feng, Hanfeng Lu, Sheng Yao, Pu Guo (HKUST), Yinghao Yu (Alibaba Group), Yizhou Shan (ByteDance), Bo Li, Binhang Yuan, Wei Wang (HKUST) arXiv: 2608.15127 · PDF TL;DR Every serving system in production today — vLLM, SGLang, TensorRT-LLM — was designed around a single assumption: the unit of work is a token-generation request, and the GPU is where the time goes....

Andy Pavlo opens CMU’s database systems course with a claim that reframes most of what practitioners argue about online: the problems are not new. The hardware changed; the problems didn’t. This week’s Classic of the Week is his Lecture 1 — course information plus a compressed history of database systems from the 1960s to the present. It’s the single best hour for understanding why databases look the way they do, and it comes with an implicit warning: if you don’t know this history, you will spend your career re-litigating settled debates....

When Anthropic announced it would watermark text output from Claude models, Sebastian Raschka posted a short explanation of the mechanism. The post went unexpectedly viral — not because watermarking is exciting, but because almost nobody could say concretely what it does. He planned a ten-slide follow-up. It became fifty. The result is one of the better explainers of the year, and it doubles as a clean walkthrough of how LLM sampling actually works....

Weekly Paper Notes — one of the top picks from the 2026-08-22 CS paper digest. Area: AI / ML. Authors: Nayeon Kim, Hojin Lee, Yunju Bak, Jaesun Park, Boseop Kim, et al. arXiv: 2608.20061 · PDF · Published at COLM 2026 TL;DR Choosing the learning rate for a frontier pretraining run is one of the highest-stakes, least-principled decisions in the field. At trillion-token scale a single sweep is unaffordable, so labs guess, extrapolate by folklore, or burn compute they’d rather spend on tokens....

Weekly Paper Notes — the Seminal Paper of the Week. Area: Distributed Computing. Authors: Douglas B. Terry, Marvin M. Theimer, Karin Petersen, Alan J. Demers, Mike J. Spreitzer, Carl H. Hauser — Xerox Palo Alto Research Center Published: SOSP ‘95 — Proceedings of the 15th ACM Symposium on Operating Systems Principles, pp. 172–182 DOI: 10.1145/224056.224070 Why the paper still matters There is a version of distributed systems history in which “eventual consistency” arrives with Dynamo in 2007, gets popularised by the NoSQL wave, and is eventually formalised by CRDTs....

Weekly Paper Notes — Seminal Paper of the Week. Area: Databases. Author: E. F. Codd (IBM Research Laboratory, San Jose) Published: Communications of the ACM, Vol. 13, No. 6, June 1970, pp. 377–387 DOI: 10.1145/362384.362685 Why the paper still matters Codd’s paper is eight pages long, contains no system, no benchmark, and no evaluation section. It would very likely struggle to get past a modern program committee. It is also, by a wide margin, the most economically consequential paper in the history of computer science — the entire relational database industry, SQL, the query optimizer as a discipline, and by extension most of what we call “data infrastructure” descend from it....

Weekly Video Notes — a short article distilling one talk from the weekly digest. Source video and key frames embedded throughout. Memory was the theme running through the whole conference, and this 19-minute talk is the most empirically grounded take on it. Shlok Khemani, working independently, did something nobody else bothered to do: he sat down and reverse-engineered the memory systems of the major consumer AI products — ChatGPT, Claude, Gemini, Poke — by probing them, extracting raw profiles, and reading the tool calls....

Weekly Paper Notes — one of the top picks from the 2026-08-15 CS paper digest. Area: AI / ML. Authors: Julian Minder, Viktor Moskvoretskii, Raghav Singhal (equal contribution), Difan Jiao, Andy Arditi, Shaobo Cui, Jannik Brinkmann, Ashton Anderson, Roland Aydin, Robert West, and others — EPFL, MATS, University of Toronto, Saarland University, Northeastern, SJTU, DFKI, Ontocord AI, Hereon/TUHH arXiv: 2608.13482 · PDF · Models & data TL;DR Every production language model today learns what the world is like during pretraining and only learns who it is supposed to be afterwards, during post-training....

Weekly Video Notes — Classic of the Week. A foundational talk revisited, with source video and key frames embedded throughout. Most Turing Award lectures are a victory lap through the technical contribution. Stonebraker refuses. He shows up without the tie the videographer asked for (“that just isn’t me”), announces that the audience isn’t a database crowd so he’ll have to teach them some database first, and then delivers 75 minutes braiding two stories together: the design and near-death of Postgres, and a tandem bicycle trip he and his wife rode across America....