https://video.ut0pia.org/videos/watch/853f9087-61b6-48c0-adfc-4acb6ad04b86 Stephen Chin gave two copies of the same agent the same facts about his home network, one storing them as a vector database, the other as a graph. He asked both what was running end of life software exposed to the internet. The vector agent said it could not find specific details. The graph agent traced the connections and flagged his daughter's Minecraft server running an out of date OS, then found real open management ports he quietly patched after the demo. Same data, and only one of them could actually answer. That gap is the whole talk. Most assistants, OpenClaw included, keep their memory as markdown files, which is why Chin's agents burn over 100,000 tokens a round loading everything in case some of it matters. It holds at small scale and breaks at large scale, because similarity in vector space is not a real relationship, so multi hop questions hallucinate. A graph stores entities and the edges between them, seeds the search with vectors, then traverses, so answers come back precise, explainable, and auditable. And if you do not know graphs, Claude writes Cypher better than he does. Speaker info: https://x.com/steveonjava, https://www.linkedin.com/in/steveonjava/, https://www.oreilly.com/library/view/graphrag-the-definitive/9798341630147/, Timestamps: 0:00 - Meet Crab D and the agent memory problem 2:34 - Why markdown memory wastes tokens 4:43 - Skills are just markdown too 5:49 - Goose: memory as an MCP server 7:44 - Vector databases and why similarity is not a relationship 9:54 - Enter graphs: precise, explainable, auditable 11:38 - You do not need to be a graph expert, Claude writes Cypher 12:04 - The demo: a home lab digital twin, vector versus graph 13:23 - Live: finding end of life software on the network 15:30 - Live: finding exposed management ports 16:49 - Why large scale needs graph memory 18:05 - Resources: the GraphRAG book and GraphAcademy Thu, 23 Jul 2026 09:43:00 GMT https://validator.w3.org/feed/docs/rss2.html PeerTube - https://video.ut0pia.org https://video.ut0pia.org/lazy-static/avatars/0287a09a-aae7-4840-9843-b416426e7046.webp https://video.ut0pia.org/videos/watch/853f9087-61b6-48c0-adfc-4acb6ad04b86 All rights reserved, unless otherwise specified in the terms specified at https://video.ut0pia.org/about and potential licenses granted by each content's rightholder.