A senior Anthropic engineer just dropped 12-page PDF on "Graph Engineering" for multi-agentic systems. The shift: your agents memory dies with their context window. A knowledge graph makes it permanent. Extract → Resolve → Assemble → Query → Repeat Every agentic graph has 5 stages: • Extract: Haiku pulls entities and S-P-O triples. One call per doc. The Pydantic schema is the only training data. • Resolve: Sonnet clusters "Edwin Aldrin" → "Buzz Aldrin" - zero string overlap - using descriptions as context. • Assemble: canonical nodes, typed edges, provenance on every triple. One connected graph. • Query: serialize a subgraph → Sonnet reasons over triples → every answer cites a specific edge. Plug this into multi-agent systems as shared memory. Workers write to it, evaluators fact-check against it, loops persist overnight with it. This 12-page PDF changed how I'm building multi-agent systems today. Read it now, then explore the article below.

@0xCodez Now in English so people can actually understand what this is