[
  {
    "id": "the-graph-web",
    "kind": "Project",
    "content": "The Graph Web is an experiment with two faces: a Canonical Representation of the project's knowledge, published at thegraphweb.com/cr for direct consumption by AI agents, and AISwise, the chat at thegraphweb.com through which people ask about the project. AISwise answers only from that Canonical Representation, so what people can learn here is exactly what agents can read there.",
    "relationships": [
      {
        "kind": "authoredBy",
        "target": "iban-rios"
      },
      {
        "kind": "hasProblem",
        "target": "problem"
      },
      {
        "kind": "investigates",
        "target": "hypothesis"
      },
      {
        "kind": "hasVision",
        "target": "vision"
      },
      {
        "kind": "implementedBy",
        "target": "architecture"
      },
      {
        "kind": "exposesAction",
        "target": "contact"
      }
    ]
  },
  {
    "id": "problem",
    "kind": "Problem",
    "content": "AI agents increasingly consume and act on digital systems authored for human readers. Structure — what a piece of content relates to, and how — exists only in prose, and an agent must infer it rather than query it directly. This is not an abstract concern: it recurs directly in the practice of building AI-native products and automations, where the same implicit structure has to be re-derived from prose again and again instead of being queried once.",
    "relationships": [
      {
        "kind": "motivates",
        "target": "hypothesis"
      }
    ]
  },
  {
    "id": "hypothesis",
    "kind": "Hypothesis",
    "content": "This project investigates whether a graph-based Canonical Representation allows AI agents to understand and act on digital systems more effectively than traditional human-oriented representations. A narrower, isolated benchmark on representation format alone (graphs vs. documents) found no measurable advantage between the two. The question this project now tracks is broader and harder to game: can an AI-native interface operate for months using only a Canonical Representation as its knowledge source, with no parallel knowledge base.",
    "relationships": []
  },
  {
    "id": "vision",
    "kind": "Vision",
    "content": "If a graph-based Canonical Representation is confirmed to be more effective, digital systems can be authored directly for AI agents, instead of being authored for humans and inferred by agents afterward. AISwise, built on top of this project's own Canonical Representation, has operated in production this way since its launch — a live, ongoing test of that vision rather than a hypothetical one.",
    "relationships": [
      {
        "kind": "dependsOn",
        "target": "hypothesis"
      }
    ]
  },
  {
    "id": "iban-rios",
    "kind": "Person",
    "content": "Iban Rios builds the systems that run go-to-market operations — currently AI GTM Engineering at Sesame HR, previously seven years managing paid media for global brands at Dentsu International and Omnicom/PHD, and a founder (Chat Ergo Bot, 2021-2023). The throughline across those roles is treating a business function as a system to be architected, not a set of manual campaigns to be run. ibanrios.com is his personal website; his other live projects are aiswise.com, validwise.com (a compliance scanner for EU regulations), ficharjornada.com (a comparison site for time-tracking software) and geoadsfinder.com (a SERP checker and ad-spy tool).",
    "relationships": [
      {
        "kind": "builds",
        "target": "aiswise"
      }
    ]
  },
  {
    "id": "aiswise",
    "kind": "Project",
    "content": "aiswise.com is an AI chatbot platform.",
    "relationships": [
      {
        "kind": "consumes",
        "target": "the-graph-web"
      }
    ]
  },
  {
    "id": "architecture",
    "kind": "Architecture",
    "content": "AISwise runs as a Cloudflare Pages Function on Workers AI (Llama 3.3 70B), streaming each reply as it is generated. The whole Canonical Representation is placed in every prompt as the model's only knowledge source — no retrieval, no embeddings, no vector database — and every conversation turn is logged as evidence of which Nodes were used. The chat itself is plain HTML, CSS and JavaScript with no framework or build step; the Canonical Representation is a TypeScript file serialized to JSON at deploy time.",
    "relationships": [
      {
        "kind": "implements",
        "target": "the-graph-web"
      }
    ]
  },
  {
    "id": "contact",
    "kind": "Action",
    "content": "Submitting a message writes it to storage with a timestamp for manual review; there is no automated reply.",
    "relationships": []
  }
]