@prefix : <https://oreillyradar.substack.com/p/why-open-source-matters-for-ai#> .
@prefix schema: <http://schema.org/> .
@prefix xsd: <http://www.w3.org/2001/XMLSchema#> .
@prefix rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#> .
@prefix rdfs: <http://www.w3.org/2000/01/rdf-schema#> .
@prefix owl: <http://www.w3.org/2002/07/owl#> .
@prefix prov: <http://www.w3.org/ns/prov#> .

<> a schema:CreativeWork ;
    schema:name "Why Open Source Matters for AI — RDF Knowledge Graph"@en ;
    schema:description "RDF-Turtle knowledge graph describing the O'Reilly Radar guest post 'Why Open Source Matters for AI' by Tim O'Reilly, published 2026-08-10."@en ;
    schema:dateCreated "2026-08-10T00:00:00Z"^^xsd:dateTime ;
    schema:dateModified "2026-08-10T00:00:00Z"^^xsd:dateTime ;
    schema:author <https://linkedin.com/in/kidehen#this> ;
    schema:about :article ;
    prov:wasGeneratedBy :kgGeneratorSkill .

:kgGeneratorSkill a schema:SoftwareApplication ;
    schema:name "kg-generator skill"@en ;
    schema:url <https://github.com/OpenLinkSoftware/ai-agent-skills/tree/main/kg-generator> ;
    schema:description "Skill for generating comprehensive, standards-compliant knowledge graphs from file: or http(s): URLs, using schema.org terms and curated prompt templates."@en .

# ── Core article entity ────────────────────────────────────────────────────

:article a schema:Article, schema:BlogPosting ;
    schema:name "Why Open Source Matters for AI"@en ;
    schema:url <https://oreillyradar.substack.com/p/why-open-source-matters-for-ai> ;
    schema:headline "Why Open Source Matters for AI"@en ;
    schema:description "Tim O'Reilly argues that open source's value for AI lies not in open weights alone but in architecture, composability, and the ability to extend a platform without permission — the lesson of Apache versus Netscape and Microsoft."@en ;
    schema:abstract "Open source won the 1990s web wars through modularity and a clean extension layer, not license purity. As frontier models push behavior into opaque weights, the same lesson applies to AI: open protocols, harnesses, and composable components — not weights alone — keep the market open."@en ;
    schema:articleSection "Open Source and AI"@en ;
    schema:datePublished "2026-08-10"^^xsd:date ;
    schema:dateModified "2026-08-10"^^xsd:date ;
    schema:author :timOReilly ;
    schema:publisher :oreillyRadar ;
    schema:isPartOf :oreillyRadar ;
    schema:about :topicOpenSource, :topicArchitectureOfParticipation, :topicOpenWeights,
        :topicAgenticAI, :topicModelContextProtocol, :topicComposability ;
    schema:keywords "open source, artificial intelligence, open weights, Model Context Protocol, composability, architecture of participation, Apache, LAMP stack, AI sovereignty"@en ;
    schema:hasPart :sectionApacheLesson, :sectionOpenWeights, :sectionComposability,
        :sectionOpenEcosystem, :sectionKeepingItWeird, :sectionConcluding,
        :faqSection, :glossarySection, :howtoSection ;
    schema:relatedLink <https://en.wikipedia.org/wiki/LAMP_(software_bundle)>,
        <https://www.oreilly.com/pub/a/tim/articles/architecture_of_participation.html>,
        <https://learning.oreilly.com/live-events/escaping-the-prompt-debt-trap-drew-breunig-live-with-tim-oreilly/0642572421878/>,
        <https://x.com/dbreunig/status/2083410286997131432>,
        <https://michaelpollan.com/books/in-defense-of-food/>,
        <https://aaif.io/>,
        <https://www.oreilly.com/radar/protocols-and-power/>,
        <https://www.letta.com/>,
        <https://nousresearch.com/>,
        <https://goose.ai/>,
        <https://pi.dev/>,
        <https://www.aipotluck.org/map>,
        <https://vllm.ai/>,
        <https://pytorch.org/>,
        <https://ollama.com/>,
        <https://www.currentai.org/>,
        <https://www.aipotluck.org/>,
        <https://x.com/trq212>,
        <https://www.oreilly.com/AI-Codecon/>,
        <https://en.wikipedia.org/wiki/Joy%27s_law_(management)> .

:topicOpenSource a schema:DefinedTerm ;
    schema:name "Open Source"@en ;
    schema:termCode "open-source" ;
    rdfs:seeAlso <http://dbpedia.org/resource/Open_source> .

:topicArchitectureOfParticipation a schema:DefinedTerm ;
    schema:name "Architecture of Participation"@en ;
    schema:termCode "architecture-of-participation" ;
    rdfs:seeAlso <http://dbpedia.org/resource/Architecture_of_participation> .

:topicOpenWeights a schema:DefinedTerm ;
    schema:name "Open Weights"@en ;
    schema:termCode "open-weights" .

:topicAgenticAI a schema:DefinedTerm ;
    schema:name "Agentic AI"@en ;
    schema:termCode "agentic-ai" ;
    rdfs:seeAlso <http://dbpedia.org/resource/Artificial_intelligence> .

:topicModelContextProtocol a schema:DefinedTerm ;
    schema:name "Model Context Protocol"@en ;
    schema:termCode "model-context-protocol" .

:topicComposability a schema:DefinedTerm ;
    schema:name "Composability"@en ;
    schema:termCode "composability" .

# ── People ─────────────────────────────────────────────────────────────────

:timOReilly a schema:Person ;
    schema:name "Tim O'Reilly"@en ;
    schema:description "Author of the guest post. Founder and CEO of O'Reilly Media, Partner at O'Reilly AlphaTech Ventures, Co-director of the AI Disclosures Project, and co-chair of the O'Reilly AI Codecon."@en ;
    schema:jobTitle "Founder and CEO"@en ;
    schema:worksFor :oreillyMedia ;
    schema:url <https://substack.com/@timoreilly> ;
    schema:image :timAvatar ;
    owl:sameAs <https://en.wikipedia.org/wiki/Tim_O%27Reilly>,
        <http://dbpedia.org/resource/Tim_O%27Reilly> .

:drewBreunig a schema:Person ;
    schema:name "Drew Breunig"@en ;
    schema:description "Technologist and O'Reilly live-events speaker who prompted Tim O'Reilly to think about frontier models moving behavior into the weights and coined the framing 'trading diversity for reliability'."@en ;
    schema:url <https://x.com/dbreunig> ;
    owl:sameAs <https://x.com/dbreunig> .

:bobYoung a schema:Person ;
    schema:name "Bob Young"@en ;
    schema:description "Founder of Red Hat, quoted for the business insight that 'what we really sell to our customers is control.'"@en ;
    owl:sameAs <https://en.wikipedia.org/wiki/Bob_Young_(businessman)> .

:isobelMoure a schema:Person ;
    schema:name "Isobel Moure"@en ;
    schema:description "Co-author with Tim O'Reilly and Ilan Strauss of the O'Reilly Radar essay 'Protocols and Power.'"@en .

:ilanStrauss a schema:Person ;
    schema:name "Ilan Strauss"@en ;
    schema:description "Co-author with Tim O'Reilly and Isobel Moure of the O'Reilly Radar essay 'Protocols and Power.'"@en .

:addyOsmani a schema:Person ;
    schema:name "Addy Osmani"@en ;
    schema:description "Co-chair of the O'Reilly AI Codecon; notes that participation today happens by rewriting the harness — skills, subagents, hooks, and context files — rather than tinkering with weights."@en ;
    owl:sameAs <http://dbpedia.org/resource/Addy_Osmani> .

:marioZechner a schema:Person ;
    schema:name "Mario Zechner"@en ;
    schema:description "Creator of the Pi open source agentic harness, famous for shipping a '/quit' command instead of '/exit' so users modify Pi for their own install."@en .

:billJoy a schema:Person ;
    schema:name "Bill Joy"@en ;
    schema:description "Sun Microsystems co-founder, quoted via Joy's Law: 'No matter who you are, most of the smartest people work for someone else.'"@en ;
    owl:sameAs <http://dbpedia.org/resource/Bill_Joy> .

:trq212 a schema:Person ;
    schema:name "@trq212 (CAIS)"@en ;
    schema:description "Center for AI Safety-affiliated voice quoted for the observation 'If it's not in your prompt, you're getting what's in-distribution.'"@en ;
    schema:url <https://x.com/trq212> ;
    owl:sameAs <https://x.com/trq212> .

# ── Organizations & publications ───────────────────────────────────────────

:oreillyRadar a schema:Periodical ;
    schema:name "O'Reilly Radar"@en ;
    schema:description "O'Reilly Media's technology and industry trend publication, published on Substack."@en ;
    schema:url <https://oreillyradar.substack.com> ;
    schema:publisher :oreillyMedia ;
    schema:hasPart :article .

:oreillyMedia a schema:Organization ;
    schema:name "O'Reilly Media"@en ;
    schema:description "Publisher of technology books, conferences, and online learning; founded by Tim O'Reilly."@en ;
    schema:url <https://www.oreilly.com> ;
    owl:sameAs <http://dbpedia.org/resource/O%27Reilly_Media> .

:apache a schema:SoftwareApplication ;
    schema:name "Apache HTTP Server"@en ;
    schema:description "The open source web server that won the 1990s server wars over Netscape and Microsoft by staying a web server with a clean extension layer."@en ;
    owl:sameAs <http://dbpedia.org/resource/Apache_HTTP_Server> .

:netscape a schema:Organization ;
    schema:name "Netscape"@en ;
    schema:description "1990s browser and web server company that raced Microsoft to control both ends of the internet connection; its server was overtaken by Apache."@en ;
    owl:sameAs <http://dbpedia.org/resource/Netscape> .

:microsoft a schema:Organization ;
    schema:name "Microsoft"@en ;
    schema:description "Tech giant whose Internet Information Server (IIS) and browser ambitions lost the web server war to Apache."@en ;
    owl:sameAs <http://dbpedia.org/resource/Microsoft> .

:redHat a schema:Organization ;
    schema:name "Red Hat"@en ;
    schema:description "Open source software company whose founder, Bob Young, framed the open source business model around selling control."@en ;
    owl:sameAs <http://dbpedia.org/resource/Red_Hat> .

:openai a schema:Organization ;
    schema:name "OpenAI"@en ;
    schema:description "Frontier AI lab; Tim O'Reilly casts it, with Anthropic, in the role Netscape and Microsoft played in the 1990s — a closed platform whose defaults increasingly live in opaque weights."@en ;
    owl:sameAs <http://dbpedia.org/resource/OpenAI> .

:anthropic a schema:Organization ;
    schema:name "Anthropic"@en ;
    schema:description "Frontier AI lab and creator of the Model Context Protocol; its default outputs are described as 'distribution convergent.'"@en ;
    owl:sameAs <http://dbpedia.org/resource/Anthropic> .

:mcp a schema:SoftwareApplication ;
    schema:name "Model Context Protocol (MCP)"@en ;
    schema:description "An open standard that lets any application reach any tool or data source without a custom integration per pairing; now hosted at the Agentic AI Foundation."@en ;
    schema:url <https://aaif.io/> ;
    schema:publisher :agenticAIFoundation .

:agenticAIFoundation a schema:Organization ;
    schema:name "Agentic AI Foundation"@en ;
    schema:description "A subproject of the Linux Foundation giving open agentic protocols such as MCP a neutral home outside any single lab."@en ;
    schema:url <https://aaif.io/> .

:linuxFoundation a schema:Organization ;
    schema:name "Linux Foundation"@en ;
    schema:description "Nonprofit consortium that hosts the Agentic AI Foundation."@en ;
    owl:sameAs <http://dbpedia.org/resource/Linux_Foundation> .

:currentAI a schema:Organization ;
    schema:name "Current AI"@en ;
    schema:description "Public-private partnership born from the Paris AI Action Summit; publisher of the Open Source Gap Map and the AI Potluck project."@en ;
    schema:url <https://www.currentai.org/> .

:aiPotluck a schema:Product ;
    schema:name "AI Potluck"@en ;
    schema:description "A public project to build a vertically integrated AI product assembled entirely from open source components, described as 'a viable alternative to proprietary AI that isn't owned by any one company or country.'"@en ;
    schema:url <https://www.aipotluck.org/> ;
    schema:producer :currentAI .

:openSourceGapMap a schema:CreativeWork ;
    schema:name "Open Source Gap Map"@en ;
    schema:description "Current AI's map of the open source AI stack covering more than 24,600 projects, 421 scored in depth across openness, capability, and adoption, organized into three layers: models, product/UX, and infrastructure."@en ;
    schema:url <https://www.aipotluck.org/map> ;
    schema:publisher :currentAI .

:letta a schema:Organization ;
    schema:name "Letta"@en ;
    schema:description "Company working on portable memory for AI agents."@en ;
    schema:url <https://www.letta.com/> .

:nousResearch a schema:Organization ;
    schema:name "Nous Research"@en ;
    schema:description "Research organization working on open and portable agent memory."@en ;
    schema:url <https://nousresearch.com/> .

:goose a schema:SoftwareApplication ;
    schema:name "Goose"@en ;
    schema:description "Open source agentic harness giving developers control over their AI tooling."@en ;
    schema:url <https://goose.ai/> .

:pi a schema:SoftwareApplication ;
    schema:name "Pi"@en ;
    schema:description "Open source agentic harness by Mario Zechner, deliberately optimized to be modifiable; ships a '/quit' command instead of '/exit.'"@en ;
    schema:url <https://pi.dev/> .

:vllm a schema:SoftwareApplication ;
    schema:name "vLLM"@en ;
    schema:description "Open source high-throughput inference framework for large language models."@en ;
    schema:url <https://vllm.ai/> .

:pytorch a schema:SoftwareApplication ;
    schema:name "PyTorch"@en ;
    schema:description "Core open source machine learning framework, part of the infrastructure layer of the open source AI stack."@en ;
    owl:sameAs <http://dbpedia.org/resource/PyTorch> ;
    schema:url <https://pytorch.org/> .

:ollama a schema:SoftwareApplication ;
    schema:name "Ollama"@en ;
    schema:description "Open source deployment tool for running models locally."@en ;
    schema:url <https://ollama.com/> .

:protocolsAndPower a schema:CreativeWork ;
    schema:name "Protocols and Power"@en ;
    schema:description "O'Reilly Radar essay by Tim O'Reilly, Isobel Moure, and Ilan Strauss arguing that as models commoditize, competition moves up the stack to context."@en ;
    schema:url <https://www.oreilly.com/radar/protocols-and-power/> .

:joyLaw a schema:CreativeWork ;
    schema:name "Joy's Law"@en ;
    schema:description "Management adage attributed to Bill Joy: 'No matter who you are, most of the smartest people work for someone else.'"@en ;
    schema:url <https://en.wikipedia.org/wiki/Joy%27s_law_(management)> .

:lampStack a schema:CreativeWork ;
    schema:name "LAMP Stack"@en ;
    schema:description "Linux, Apache, MySQL, and (Perl | Python | PHP) — the open source web platform that demonstrated modularity and composability as the moat."@en ;
    schema:url <https://en.wikipedia.org/wiki/LAMP_(software_bundle)> .

# ── Media objects ──────────────────────────────────────────────────────────

:timAvatar a schema:ImageObject ;
    schema:name "Tim O'Reilly avatar"@en ;
    schema:description "Profile avatar of Tim O'Reilly used in the post byline."@en ;
    schema:contentUrl <https://bucketeer-e05bbc84-baa3-437e-9518-adb32be77984.s3.amazonaws.com/public/images/29a45924-f486-4a2c-b017-edcba86c40f1_5976x3984.jpeg> ;
    schema:representativeOfPage true .

:oreillyAvatar a schema:ImageObject ;
    schema:name "O'Reilly Radar avatar"@en ;
    schema:description "Publication avatar for O'Reilly Radar."@en ;
    schema:contentUrl <https://substackcdn.com/image/fetch/$s_!n2VI!,w_36,h_36,c_fill,f_auto,q_auto%3Agood,fl_progressive%3Asteep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F5711c4e4-a6b7-4c16-a0b0-a80bfc37a8e5_1200x1200.png> ;
    schema:representativeOfPage true .

# ── Article sections (entity groups) ───────────────────────────────────────

:sectionApacheLesson a schema:ArticleSection ;
    schema:name "The Apache lesson"@en ;
    schema:description "In 1995 the question was whether Netscape or Microsoft would control the web. The answer was neither. Apache won by being modular rather than feature-packed, and the LAMP stack showed that modularity, not features, was the moat."@en ;
    schema:articleBody "Both Netscape and Microsoft aimed to dominate the web server and browser market, racing to build every feature into the product. The open source Apache web server took the opposite bet: a clean extension layer that anyone could bolt onto without asking permission. Within a few years Apache was the most popular web server and the LAMP stack — Linux, Apache, MySQL, and (Perl | Python | PHP) — became a legitimate platform. Tim O'Reilly called this pattern 'the architecture of participation' in 2004. Open source wasn't just about licenses but about architecture: a small kernel with standard interfaces that lets people extend your work without permission."@en ;
    schema:hasPart :lampStack, :apache ;
    schema:isPartOf :article .

:sectionOpenWeights a schema:ArticleSection ;
    schema:name "Open weights are just table stakes"@en ;
    schema:description "The public debate over open source AI fixates on model weights, but Apache and Linux never competed over source availability. Open source meant a platform your application depended on was a layer you could extend and build a business on without permission."@en ;
    schema:articleBody "Each new version of the frontier models moves more of the product's behavior out of an editable layer and into the weights, where nobody outside the lab can see or change it. Drew Breunig calls post-training 'trading diversity for reliability.' Bob Young of Red Hat framed the open source business model: 'What we really sell to our customers is control.' Every wave of computing runs the same cycle — distributed innovation at the start, then the winner closes down offerings to build a moat. What keeps a market open is how easy it is to swap one component for another."@en ;
    schema:hasPart :drewBreunig, :bobYoung, :redHat, :openai, :anthropic ;
    schema:isPartOf :article .

:sectionComposability a schema:ArticleSection ;
    schema:name "Protocols and composability"@en ;
    schema:description "Unix utilities, the shell, TCP/IP, and HTTP kept the internet open and composable. In AI, Anthropic's Model Context Protocol is a disruptive step in that direction, and it now has a neutral home at the Agentic AI Foundation."@en ;
    schema:articleBody "Unix utilities expected stdin and stdout and the shell acted as a harness connecting them, which is why they are the lingua franca of agentic tooling more than 50 years later. In 'Protocols and Power,' Tim O'Reilly, Isobel Moure, and Ilan Strauss argue that as models commoditize, competition moves up the stack to context, and opening access to that context opens the market regardless of whether open or closed weights sit underneath. This is an unbundling of model from harness from context, the way Apache unbundled web server from web application."@en ;
    schema:hasPart :mcp, :agenticAIFoundation, :protocolsAndPower, :linuxFoundation ;
    schema:isPartOf :article .

:sectionOpenEcosystem a schema:ArticleSection ;
    schema:name "The open source AI ecosystem"@en ;
    schema:description "Portable memory players like Letta and Nous Research, open harnesses like Goose and Pi, and Current AI's Open Source Gap Map and AI Potluck project chart the scale of open source AI."@en ;
    schema:articleBody "Agentic skills may be a critical element of the open source AI future, though like Perl and PHP in the LAMP stack they may be replaced when something better comes along — and that is fine, because composability makes switching easy. Pi is deliberately optimized to be modifiable: creator Mario Zechner gives Pi a '/quit' command rather than '/exit,' telling users to ask Pi to add it to their install. Current AI's Open Source Gap Map covers more than 24,600 open source AI projects, 421 scored in depth, organized into three layers: models, product and UX, and infrastructure. AI Potluck is backed by roughly $400 million of a five-year, $2.5 billion commitment from the French government, DeepMind, Salesforce, and major philanthropies including Omidyar's AI Collaborative, the MacArthur Foundation, and the Ford Foundation."@en ;
    schema:hasPart :letta, :nousResearch, :goose, :pi, :marioZechner, :vllm, :pytorch, :ollama,
        :currentAI, :openSourceGapMap, :aiPotluck ;
    schema:isPartOf :article .

:sectionKeepingItWeird a schema:ArticleSection ;
    schema:name "Keeping it weird"@en ;
    schema:description "Drew Breunig argues it is our job to make it weird — to push models deliberately out of distribution rather than settle for the labs' default outcomes — and Addy Osmani notes participation now happens by rewriting the harness."@en ;
    schema:articleBody "One or two big closed models locking personality, business goals, and guardrails into the weights would reduce the diversity at the heart of innovation. Drew Breunig's team chose not to build in React precisely because every model knows it too well, and he uses GLM and Kimi because they are more malleable inside a custom harness. Anthropic named default outputs 'distribution convergent'; as @trq212 of CAIS put it, 'If it's not in your prompt, you're getting what's in-distribution.' Addy Osmani: 'Almost nobody I work with is tinkering with weights, but they're rewriting the harness and what sits around it pretty constantly — skills, subagents, hooks, context files.' We need real separation between the model, the harness, and the application so that someone who wants to build something weird can do it without a lab's roadmap and guardrails."@en ;
    schema:hasPart :drewBreunig, :addyOsmani, :trq212 ;
    schema:isPartOf :article .

:sectionConcluding a schema:ArticleSection ;
    schema:name "Don't shut down the options"@en ;
    schema:description "The big labs are making the same strategic mistake as Netscape and Microsoft: build more reliability, but do not shut down options for developers outside the labs to push the state of the art forward."@en ;
    schema:articleBody "Tim O'Reilly returns to the Apache story: the big labs should make models more reliable for ordinary users but must not shut down the options for developers who do not work for them to push the state of the art forward. As Bill Joy put it decades ago, 'No matter who you are, most of the smartest people work for someone else.' No one should have a monopoly on innovation, and no one should be building a moat to hold it back. The post closes by inviting readers to AI Codecon: Building with Open Source AI on August 31."@en ;
    schema:hasPart :billJoy, :joyLaw ;
    schema:isPartOf :article .

# ── FAQ section ─────────────────────────────────────────────────────────────

:faqSection a schema:FAQPage ;
    schema:name "Frequently Asked Questions"@en ;
    schema:description "Questions and answers drawn from Tim O'Reilly's 'Why Open Source Matters for AI.'"@en ;
    schema:mainEntity :q1, :q2, :q3, :q4, :q5, :q6, :q7, :q8, :q9, :q10 ;
    schema:isPartOf :article .

:q1 a schema:Question ;
    schema:name "Why did open source win the 1990s web server wars?"@en ;
    schema:text "Why did open source win the 1990s web server wars?"@en ;
    schema:acceptedAnswer :a1 ;
    schema:isPartOf :faqSection .

:a1 a schema:Answer ;
    schema:text "Apache won because it stayed a web server with a clean extension layer, so anyone could bolt something new onto it without asking permission or waiting for a release cycle. Modularity, not features, was the moat."@en ;
    schema:isPartOf :faqSection .

:q2 a schema:Question ;
    schema:name "What is the architecture of participation?"@en ;
    schema:text "What is the architecture of participation?"@en ;
    schema:acceptedAnswer :a2 ;
    schema:isPartOf :faqSection .

:a2 a schema:Answer ;
    schema:text "Tim O'Reilly's 2004 name for the pattern where a small kernel with standard interfaces lets people extend your work without asking permission. It explains why modular open projects thrived while monolithic ones like OpenOffice never built much community."@en ;
    schema:isPartOf :faqSection .

:q3 a schema:Question ;
    schema:name "Why are open weights only 'table stakes'?"@en ;
    schema:text "Why are open weights only 'table stakes'?"@en ;
    schema:acceptedAnswer :a3 ;
    schema:isPartOf :faqSection .

:a3 a schema:Answer ;
    schema:text "The license on any single component is not what keeps a market open. Apache never competed over whose source was more available; it competed over control — a platform you can extend and build a business on without asking permission. What keeps a market open is how easy it is to swap one component for another."@en ;
    schema:isPartOf :faqSection .

:q4 a schema:Question ;
    schema:name "What does 'trading diversity for reliability' mean?"@en ;
    schema:text "What does 'trading diversity for reliability' mean?"@en ;
    schema:acceptedAnswer :a4 ;
    schema:isPartOf :faqSection .

:a4 a schema:Answer ;
    schema:text "Drew Breunig's description of post-training: models get more reliable for lazy prompts but less diverse in their outputs. It is a good trade for many people, but it is the same kind of trade that gives us highly processed foods when real food is better."@en ;
    schema:isPartOf :faqSection .

:q5 a schema:Question ;
    schema:name "What keeps an open market open?"@en ;
    schema:text "What keeps an open market open?"@en ;
    schema:acceptedAnswer :a5 ;
    schema:isPartOf :faqSection .

:a5 a schema:Answer ;
    schema:text "Easy component substitutability plus open protocols. Unix stdin/stdout conventions, the shell, TCP/IP, and HTTP kept the internet composable. In AI, open protocols and harnesses keep competition moving up the stack to context."@en ;
    schema:isPartOf :faqSection .

:q6 a schema:Question ;
    schema:name "What is the Model Context Protocol?"@en ;
    schema:text "What is the Model Context Protocol?"@en ;
    schema:acceptedAnswer :a6 ;
    schema:isPartOf :faqSection .

:a6 a schema:Answer ;
    schema:text "An open standard by Anthropic that lets any application reach any tool or data source without a custom integration per pairing. MCP now has a neutral home at the Agentic AI Foundation, a subproject of the Linux Foundation."@en ;
    schema:isPartOf :faqSection .

:q7 a schema:Question ;
    schema:name "What is AI Potluck and who backs it?"@en ;
    schema:text "What is AI Potluck and who backs it?"@en ;
    schema:acceptedAnswer :a7 ;
    schema:isPartOf :faqSection .

:a7 a schema:Answer ;
    schema:text "A public project by Current AI to build a vertically integrated AI product entirely from open source components — a viable alternative to proprietary AI not owned by any one company or country. It is backed by roughly $400 million of a five-year, $2.5 billion commitment from the French government, DeepMind, Salesforce, and philanthropies including Omidyar's AI Collaborative, the MacArthur Foundation, and the Ford Foundation."@en ;
    schema:isPartOf :faqSection .

:q8 a schema:Question ;
    schema:name "Why does model diversity matter for innovation?"@en ;
    schema:text "Why does model diversity matter for innovation?"@en ;
    schema:acceptedAnswer :a8 ;
    schema:isPartOf :faqSection .

:a8 a schema:Answer ;
    schema:text "Diversity is at the heart of innovation. If one or two closed labs lock their desired personality, business goals, and guardrails into the weights, outputs converge into a monoculture. Deliberately pushing a model out of distribution — keeping it weird — is how teams ship something genuinely their own."@en ;
    schema:isPartOf :faqSection .

:q9 a schema:Question ;
    schema:name "What does 'distribution convergent' mean?"@en ;
    schema:text "What does 'distribution convergent' mean?"@en ;
    schema:acceptedAnswer :a9 ;
    schema:isPartOf :faqSection .

:a9 a schema:Answer ;
    schema:text "Anthropic's term for default model output: labs must ship 'good enough' results for a layperson's lazy prompt, so without direction the model returns the in-distribution average. As @trq212 of CAIS put it, 'If it's not in your prompt, you're getting what's in-distribution.'"@en ;
    schema:isPartOf :faqSection .

:q10 a schema:Question ;
    schema:name "What strategic mistake are the big labs repeating?"@en ;
    schema:text "What strategic mistake are the big labs repeating?"@en ;
    schema:acceptedAnswer :a10 ;
    schema:isPartOf :faqSection .

:a10 a schema:Answer ;
    schema:text "The same mistake Netscape and Microsoft made: building a sealed, integrated platform to build a moat. Labs should make models more reliable for ordinary users, but not shut down options for outside developers to push the state of the art forward. As Bill Joy said, 'No matter who you are, most of the smartest people work for someone else.'"@en ;
    schema:isPartOf :faqSection .

# ── Glossary section ────────────────────────────────────────────────────────

:glossarySection a schema:DefinedTermSet ;
    schema:name "Glossary"@en ;
    schema:description "Key terms used in 'Why Open Source Matters for AI.'"@en ;
    schema:hasDefinedTerm :termOpenSource, :termArchitectureOfParticipation,
        :termOpenWeights, :termMCP, :termAgenticAI, :termHarness, :termComposability,
        :termDistributionConvergence, :termAISovereignty, :termLampStack ;
    schema:isPartOf :article .

:termOpenSource a schema:DefinedTerm ;
    schema:name "Open Source"@en ;
    schema:description "Software whose source is available for modification and redistribution; in this essay, more importantly, a platform you can extend and build on without permission."@en ;
    schema:url <https://en.wikipedia.org/wiki/Open_source> ;
    schema:inDefinedTermSet :glossarySection .

:termArchitectureOfParticipation a schema:DefinedTerm ;
    schema:name "Architecture of Participation"@en ;
    schema:description "A system designed so users and third parties can extend it through standard interfaces without asking permission."@en ;
    schema:url <https://www.oreilly.com/pub/a/tim/articles/architecture_of_participation.html> ;
    schema:inDefinedTermSet :glossarySection .

:termOpenWeights a schema:DefinedTerm ;
    schema:name "Open Weights"@en ;
    schema:description "Publicly released model weights. The essay argues they are table stakes — the real value is in architecture and composability."@en ;
    schema:inDefinedTermSet :glossarySection .

:termMCP a schema:DefinedTerm ;
    schema:name "Model Context Protocol (MCP)"@en ;
    schema:description "Open standard letting any application reach any tool or data source without custom per-pairing integrations."@en ;
    schema:url <https://aaif.io/> ;
    schema:inDefinedTermSet :glossarySection .

:termAgenticAI a schema:DefinedTerm ;
    schema:name "Agentic AI"@en ;
    schema:description "AI systems that act on tasks using tools, harnesses, and context; the frontier where composability and open protocols now matter most."@en ;
    schema:inDefinedTermSet :glossarySection .

:termHarness a schema:DefinedTerm ;
    schema:name "Harness"@en ;
    schema:description "The software shell around a model — prompts, tools, context, hooks — where participation and modification increasingly happen."@en ;
    schema:inDefinedTermSet :glossarySection .

:termComposability a schema:DefinedTerm ;
    schema:name "Composability"@en ;
    schema:description "The ease of combining or swapping components so a better one can replace an existing one when it appears."@en ;
    schema:inDefinedTermSet :glossarySection .

:termDistributionConvergence a schema:DefinedTerm ;
    schema:name "Distribution Convergence"@en ;
    schema:description "The tendency of untuned model output to fall into the in-distribution average; reliable for lazy prompts but a source of monoculture."@en ;
    schema:inDefinedTermSet :glossarySection .

:termAISovereignty a schema:DefinedTerm ;
    schema:name "AI Sovereignty"@en ;
    schema:description "National or corporate control over AI capability and infrastructure, a motivation behind open source AI efforts like AI Potluck."@en ;
    schema:inDefinedTermSet :glossarySection .

:termLampStack a schema:DefinedTerm ;
    schema:name "LAMP Stack"@en ;
    schema:description "Linux, Apache, MySQL, and (Perl | Python | PHP) — the open web platform that proved modularity and composability beat integrated feature walls."@en ;
    schema:url <https://en.wikipedia.org/wiki/LAMP_(software_bundle)> ;
    schema:inDefinedTermSet :glossarySection .

# ── HowTo section ───────────────────────────────────────────────────────────

:howtoSection a schema:HowTo ;
    schema:name "How to Build with Open Source AI"@en ;
    schema:description "Practical steps for teams who want the control, composability, and diversity that open source AI architectures provide."@en ;
    schema:step :step1, :step2, :step3, :step4, :step5, :step6, :step7 ;
    schema:isPartOf :article .

:step1 a schema:HowToStep ;
    schema:position "1"^^xsd:integer ;
    schema:name "Choose open-weight or open models that fit your constraints"@en ;
    schema:text "Start from the open source gap map and evaluate open-weight models against your cost, privacy, and control requirements. Open weights are table stakes; choose the base that keeps your options open."@en ;
    schema:isPartOf :howtoSection .

:step2 a schema:HowToStep ;
    schema:position "2"^^xsd:integer ;
    schema:name "Separate the model, the harness, and the application"@en ;
    schema:text "Follow the Apache unbundling: keep the model, the harness, and your application as distinct layers so you can swap or extend any one without rebuilding the rest."@en ;
    schema:isPartOf :howtoSection .

:step3 a schema:HowToStep ;
    schema:position "3"^^xsd:integer ;
    schema:name "Build on open protocols like MCP"@en ;
    schema:text "Wire your tools and data through open standards such as the Model Context Protocol so any application can reach them without custom per-pairing integrations."@en ;
    schema:isPartOf :howtoSection .

:step4 a schema:HowToStep ;
    schema:position "4"^^xsd:integer ;
    schema:name "Fork and modify skills, subagents, and hooks"@en ;
    schema:text "Most participation happens by rewriting the harness: fork a skill instead of adopting the default, and keep memory and constitution files that travel with your agent rather than living in a vendor account."@en ;
    schema:isPartOf :howtoSection .

:step5 a schema:HowToStep ;
    schema:position "5"^^xsd:integer ;
    schema:name "Use portable memory"@en ;
    schema:text "Adopt portable memory from open players like Letta and Nous Research so your agent's state is yours to move, inspect, and edit."@en ;
    schema:isPartOf :howtoSection .

:step6 a schema:HowToStep ;
    schema:position "6"^^xsd:integer ;
    schema:name "Pick the unfashionable framework on purpose"@en ;
    schema:text "To stay out of distribution, deliberately choose tools models do not over-fit to — as Drew Breunig's team did by skipping React and using more malleable models like GLM and Kimi inside a custom harness."@en ;
    schema:isPartOf :howtoSection .

:step7 a schema:HowToStep ;
    schema:position "7"^^xsd:integer ;
    schema:name "Participate in the open source AI community"@en ;
    schema:text "Contribute to open harnesses like Goose and Pi, join projects like AI Potluck, and keep pushing the state of the art from outside the labs. Per Joy's Law, most of the smartest people work for someone else."@en ;
    schema:isPartOf :howtoSection .