Most retellings of the modern AI wave start with ChatGPT arriving out of nowhere in November 2022. Ross Taylor has a different vantage point: he shipped a competing language model two weeks earlier, watched it get torn apart in public, and spent the following four years working out exactly why. This talk is the compressed version of that education — half war story, half technical agenda for what comes after the current generation of agents....

Weekly Paper Notes — one of the top picks from the 2026-08-01 CS paper digest. Area: Operating Systems / Formal Methods. Authors: Qian Cheng, Ruize Tang, Yu Huang (Nanjing University); Saad Mohammad Rafid Pial, Yiming Su, Tianyin Xu (University of Illinois Urbana-Champaign); Emilie Ma, Finn Hackett, Ivan Beschastnikh (University of British Columbia) arXiv: 2607.25333 · PDF · Code TL;DR Formal verification of real systems has always been bottlenecked by the same thing: writing a good TLA+ specification takes a domain expert months, and the specification immediately begins drifting away from the code it describes....

Weekly Paper Notes — 🔁 Seminal Paper of the Week, 2026-08-01. Area: Operating Systems / Storage. Authors: Mendel Rosenblum, John K. Ousterhout (University of California, Berkeley) Published: ACM Transactions on Computer Systems, Vol. 10, No. 1, February 1992 (SOSP ‘91) DOI: 10.1145/146941.146943 Why this paper still matters Almost every high-performance storage system built in the last fifteen years is a log-structured file system wearing a different name. LevelDB, RocksDB, Cassandra, HBase, Kafka, every SSD’s flash translation layer, ZFS’s copy-on-write, btrfs, WiredTiger, Lucene’s segment merges — all of them convert random writes into sequential appends and then run a background process to reclaim space....

Two and a half years after the Devin demo went viral at 13% on SWE-bench, Cognition president Russell Kaplan sits down with Harrison Chase for the most candid accounting yet of what running coding agents at enterprise scale actually costs — and why the industry’s incentives are quietly pointed in the wrong direction. The central claim: a lot of the ecosystem is structurally motivated to get customers to token-max, and the bill is now coming due....

In 2014 at NeurIPS in Montreal, Ilya Sutskever, Oriol Vinyals, and Quoc Le presented “Sequence to Sequence Learning with Neural Networks” — the paper that showed encoder–decoder LSTMs could translate French to English end-to-end and, in doing so, planted the seed of the scaling hypothesis. In December 2024 the paper won the NeurIPS Test of Time Award and Sutskever came back on stage to look at that decade with 10 more years of hindsight....

Jason Lopatecki, founder of Arize, opens by noting that his own team’s first agent “frankly sucked” — and that everything they’ve built since is downstream of debugging that failure in production. His AI Engineer talk lays out a concrete pattern for agents that repair themselves: production signal (traces, evals, human labels) feeds a second agent that opens pull requests against the first agent’s own prompts, tools, and skills. It’s the operational shape of the “self-improving system” idea, minus the hand-waving....

Weekly Paper Notes — one of the top picks from the 2026-07-25 CS paper digest. Area: AI / ML (Agent Training). Authors: Xiao Yu, Baolin Peng, Ruize Xu et al. arXiv: 2607.21557 · PDF TL;DR Modern agents are shaped less by their base model and more by the harness wrapped around it — Claude Code, Codex, OpenClaw, GUI-use scaffolds. But those harnesses are stateful, multi-process, and full of tool orchestration, which means existing open SFT/RL stacks (veRL, TRL, OpenRLHF) can’t natively express a rollout inside one....

Prompt engineering was the primitive of 2023, context engineering owned 2024–2025, and 2026 is settling on a new one: loop engineering — the discipline of designing the feedback loops that surround an agent, not just the agent itself. Sydney Runkle (PM on LangChain’s open-source team) makes the case in this webinar that the durable advantage is never the agent, it’s the loops built around it. Why loops, not agents Runkle opens with a simple framing: a model has some fixed level of intelligence; a harness wrapped around it converts that intelligence into useful work on a specific problem....

Weekly Paper Notes — 🔁 Seminal Paper of the Week for the 2026-07-25 CS paper digest. Area: Distributed Computing. Authors: Leslie Lamport, Robert Shostak, Marshall Pease (SRI International) Venue: ACM Transactions on Programming Languages and Systems, Vol. 4, No. 3, July 1982, pp. 382–401. DOI: 10.1145/357172.357176 · PDF (SRI copy) Why the paper still matters Almost every distributed system in production today — Spanner, etcd, ZooKeeper, Kafka, every blockchain, every consensus protocol with a Greek letter in its name — is a descendant of the impossibility and possibility results in this 20-page paper....

Weekly Paper Notes — one of the top picks from the 2026-07-25 CS paper digest. Area: NLP / LLM Inference. Author: Alagappan Valliappan arXiv: 2607.21535 · PDF TL;DR Frontier LLMs increasingly ship a built-in Multi-Token-Prediction (MTP / NEXTN) draft head for speculative decoding, based on the assumption that the draft is negligibly cheap. Windowed-MTP shows that assumption breaks catastrophically at million-token context: the native MTP head does full attention over the entire KV cache at every draft step, so its cost grows linearly with context and comes to dominate — precisely where speculation is supposed to matter most....