A Practitioner's Guide to Graphs - Tim Ainge, Good Collective
Jul 18, 2026 · 14:18
Tim Ainge from Good Collective presents a practitioner's guide to graphs, covering extraction from unstructured text, schema-first design, and graph-native algorithms to make AI applications smarter, cheaper, and more reliable. He demonstrates that giving extractors a schema (e.g., recipe with ingredients and steps) yields more meaningful graphs, and using ontology instructions standardizes units and ingredient names. Embedding models solve the potato–potato problem by flexibly matching duplicate nodes. Personalized PageRank, inspired by Pinterest's Pixie paper and HIPORAG, finds authoritative nodes in dense graphs, e.g., identifying Miranda v. Arizona as a landmark case not directly cited. Shortest path algorithms reduce tool calls by 40% in code search by retrieving intermediate nodes missed by vector search. Subgraph matching detects software design patterns like the decorator by querying graph shape without specific node details.
