Notes from the machine room.

Raffael architects AI and agent platforms by day, and builds decentralised compute, language tooling, local-first apps, simulations, and games by night. Writing about agents and the platforms they run on, trust and determinism in software, and the history and economics of technology. Languages and models are tools. They serve humans, not the other way around.

Selected writing

  1. articleLearning to PlayEN中한

    A chess prodigy's handbook, three old games and one laptop: rebuilding the ideas behind game-playing AI in Rust for a browser on my phone, and measuring them.

    Game AIMachine learningReinforcement learningGamesRustWebAssemblyHistory of technologyChessShogiGo

  2. articleThe River and the CanalEN中한

    Agents explore the rugged world; workflows are what exploration leaves behind. Chess, StarCraft, a factory under the sea, and why I build an engine.

    AgentsGame AIFractalsAbstractionDeterminismDurable executionTrustFactoriesPost-scarcityLegibilityFinanceInsuranceChessGoStarCraftInternet culture

  3. reviewWin Everything, Control No OneEN中한

    Sebastian Mallaby's biography of Demis Hassabis is the best history of modern AI I know, and an honest study of a man who hates control and exercises it.

    IntelligenceReinforcement learningGamesResearch labsAI alignmentHistory of technologyTechnology racesPost-scarcityChessShogiGoStarCraft

Latest writing

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  1. noteMemory that dreams

    A colleague showed me that agent memory should dream before Anthropic published on it. Replay the day, and check the notes against what happened.

    External memoryContext engineeringAgentsNeuroscienceKnowledge management

  2. reviewIts Own Metaphor

    Philip Ball's How Life Works is the popular science book I wish every other one were: deep, clear, and honest about how we came to know what we know.

    Life sciencesGeneticsEmergenceComplex systemsPhilosophy of scienceSynthetic biology

  3. reviewAn Empire of PeopleEN中한

    Karen Hao's Empire of AI tells the story of OpenAI through its people. Gripping as reporting, and uneven where it argues.

    Research labsTechnology racesHubrisTraining dataCapital allocationBureaucracy

  4. noteSomething closer to a religion

    In 2013 Sam Altman wrote that great founders create something closer to a religion. Karen Hao reads it as a warning; I read it as a forecast.

    ReligionEntrepreneurshipFuture of workResearch labs

  5. noteSmall, focused, high-trust

    Altman wanted OpenAI to stay small. Every large group spends more of its work holding itself together, and AI may change that arithmetic.

    BureaucracyResearch labsEntrepreneurshipFuture of work

  6. noteIts magic crumbles away

    Weizenbaum said a program's magic crumbles once it is explained. Karen Hao ends her book on it. True of ELIZA, not of language models.

    LanguageIntelligenceHistory of technologyPsychology

  7. noteIntelligence is compression

    Ilya Sutskever's internal slogan at OpenAI: a model that must predict the world has to compress it. I think it is the most useful definition we have.

    IntelligenceLanguageNeural networksMathematics

  8. noteHow CRISPR works

    Bacteria keep mug shots of the viruses that attacked them, and Cas9 uses them to cut. A 3D model to step through, from the discovery to the tool.

    GeneticsSynthetic biologyLife sciencesHistory of science

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