Sparse Notes
Technical notes on DevOps, Kubernetes, Software Engineering, and AI.
A Relational Model of Data for Large Shared Data Banks (Codd, 1970)
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....
Lessons from Studying Every Memory System
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....
Synthetic Persona Pretraining: Alignment from Token Zero
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....
The Land Sharks Are on the Squawk Box — Stonebraker's Turing Award Lecture
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....
Who Gets to Be at the Frontier of Discovery
Weekly Video Notes — a short article distilling one talk from the weekly digest. Source video and key frames embedded throughout. Sara Hooker has done the full tour — PhD, DeepMind, several frontier labs, a research career built on efficiency at scale. Which is what makes this talk land: it’s an insider arguing that the system that produced her is an unreasonably narrow filter, and that the economics of the current moment are finally prying it open....
Who Should Own the Expert Cache? Kernel-Managed Tiering for Trillion-Parameter MoE Inference
Weekly Paper Notes — one of the top picks from the 2026-08-15 CS paper digest. Area: Operating Systems / Systems. Authors: Yuan Si (University of Waterloo), Yufeng Lin (Independent), Daming Li (Independent), Jialu Zhang (University of Waterloo, corresponding) arXiv: 2608.12103 · PDF TL;DR A trillion-parameter mixture-of-experts model routes each token through a small, input-dependent slice of its weights — in the production model studied here, an accepted token costs on average 1585 expert reads of 17....
Architectural Implications of Agentic AI Workflows
Weekly Paper Notes — one of the top picks from the 2026-08-08 CS paper digest. Area: Distributed Computing / Computer Architecture. Authors: Jirong Yang, Peizhe Liu, Jovan Stojkovic (UT Austin); Chaojie Zhang (Microsoft Azure) arXiv: 2608.04458 · PDF TL;DR Datacenter servers have been optimized for two workload shapes: CPU-centric services (web serving, key-value stores, analytics) and monolithic LLM inference, where a GPU does dense tensor math and the host merely feeds it....
Classic of the Week: Inventing on Principle — Bret Victor
Fourteen years on, this is still the talk that most reliably rewires how an engineer thinks about their own work. It is remembered for the live-coding demos — and those demos did seed a decade of tooling, from hot reload to Swift Playgrounds to every notebook environment you use. But the demos are the setup. The talk’s actual argument arrives in the last fifteen minutes, and it is not about programming at all....
Communicating Sequential Processes (Hoare, 1978)
Weekly Paper Notes — the Seminal Paper of the Week for the 2026-08-08 CS paper digest. Area: Programming Languages / Concurrency (rotating away from a long run of distributed-systems picks). Author: C. A. R. Hoare (Queen’s University, Belfast) Published: Communications of the ACM, Vol. 21, No. 8, August 1978, pp. 666–677 DOI: 10.1145/359576.359585 Why the paper still matters If you have written ch <- v in Go, spawned an Erlang process and sent it a message, wired up an actor in Akka, or reasoned about a Rust mpsc channel, you have been programming in a dialect of a language sketched in eleven pages of CACM in 1978....
On Topology's Role in ML Training Performance
Weekly Paper Notes — one of the top picks from the 2026-08-08 CS paper digest. Area: Systems / Networking. Authors: Sarah McClure (UC Berkeley), Tegan Wilson (Northeastern), Brad Karp (UCL / Google), Michael Mitzenmacher (Harvard), Sylvia Ratnasamy (UC Berkeley), Scott Shenker (UC Berkeley / ICSI), Minlan Yu (Harvard) arXiv: 2608.01707 · PDF TL;DR Every large ML training system sits on one of two interconnect families: the fat-tree Clos that GPUs inherited from datacenter networking, or the torus that TPUs inherited from HPC....