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The graph companies: what changed in v1.1.0
From v1.0.0 (2026-10-19, 5448d200e) to v1.1.0 (2026-10-19, this release), paragraph by paragraph.
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Summary: ReadingSomething I have been looking at while reading my book, I keep coming back to one idea:book: some of the biggest and most successful companies in the world are graph companies. Google started from a graph of links and built a Knowledge Graph of things, not strings. Facebook is a social graph, LinkedIn calls itself an economic graph, Amazon builds a product graph on top of a supply chain, and Visa and Mastercard are networks that move trillions. Four of the ten most valuable companies today are, at heart, graphs, worth about $12.8 trillion together. Around them are the companies and consultancies that sell ontologies and taxonomies, a digital twin of an organisation, and the old ones too: legal research has been a citation graph since 1873. Even a spreadsheet, a relational database and a language model are graphs. Once a graph has the right connections, and you remove the nodes that do not matter, the answer becomes obvious, like the end of a whodunit. So why did graphs not scale for everyone else? Because building one took a lot of technology, and whoever built it used it to lock the customer in and keep competitors out: no shared schemas, no shared code. Fractal semantic graphs, where nobody has to share a schema, and agents that maintain them, are how they can scale now.
10 unchanged paragraphs, under In short {#in-short}, Graph companies {#companies}
ReadingSomething I have been looking at while reading my book, I keep coming back to this idea:book: some of the biggest and most successful companies in the world, especially the ones that do not sell physical resources, are graph companies. Nodes and edges. Connecting A to B to C to D.
37 unchanged paragraphs, under Logistics is a graph {#logistics}, Ontologies are a business {#ontologies}, Everything is a graph {#everything}…