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There are perhaps a trillion active SQLite databases in the world. Roughly half the filesystem I/O on the phone in your pocket goes through it. And it is maintained by three committers. That ratio — planetary deployment, three-person team — is the actual subject of this talk. Richard Hipp, SQLite’s creator, spends 54 minutes explaining the machinery that makes it possible, and the answer is not cleverness. It is a testing regime borrowed wholesale from the avionics industry, plus a willingness to redesign the product itself so it can be tested at all....

Stanford’s CS329A is one of the few graduate courses aimed squarely at the thing practitioners are actually building right now: agents that improve themselves. This first lecture is the map — a compressed tour from GPT-3-era scaling laws to the agentic loop inside Claude Code, delivered by two instructors who worked on the models in question. Akanksha Chowdhery is an adjunct professor at Stanford and researcher at Reflection AI; Azalia Mirhoseini is an assistant professor in the CS department who worked on Gemini at Google DeepMind and on Claude at Anthropic....

Almost every distributed database you touch today inherited something from a single 2007 SOSP paper. Cassandra is essentially its open-source descendant; Riak, Voldemort, and a decade of “eventually consistent” architecture trace back to the same document. This Papers We Love Tokyo session — the chapter’s inaugural talk, presented by Corrina Sivak — is a rare thing: a walkthrough by someone reading it as a working engineer rather than as an authority, complete with audience interruptions, honest “this might be a gap in my understanding,” and a genuinely useful comparison of what the paper described versus what AWS actually ships today....

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....

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....

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....

Agent “skills” — reusable folders of instructions, scripts, and assets that a model loads on demand — have quietly become the packaging unit of the agent ecosystem. Philipp Schmid opens this AI Engineer talk with a brutal statistic from Skills Bench v1.1: of 50,000+ published skills, almost none have evals. Most were AI‑written and never tested. And because agents are non‑deterministic, without evals you have no way to tell whether a failing task is your skill’s fault, the model’s fault, or just noise....

Jonathan Blow gave this hour-long talk at DevGAMM in 2019, and in the seven years since it has quietly become one of the most-cited critiques of modern software engineering. Blow — the game designer behind Braid and The Witness, and the creator of the Jai programming language — makes a claim most programmers instinctively resist: technological knowledge is not on a monotonic climb. Civilizations lose capabilities all the time. Ours is probably losing them right now, and software is one of the leading indicators....