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Skills2026-03-19 · source-backed
Treat each fact as a content-hashed tuple with typed metadata and a retrieval interface. Retrieve relevant subsets on demand instead of stuffing everything into context. 100% accuracy at 7,000+ facts where in-context approaches lose 60%. The database approach to LLM memory. arXiv
Each link below shares sources, entities, or timing with this story.
Shared entities / Same source / Shared topic
Both cover Accuracy, Hash, LLM; cite the same source (arXiv); overlapping topics (accuracy, approach, context, cost, database).
Simon Willison released LLM / Shared entity: LLM / What happened next / Tension
Linked by a graph relationship (Simon Willison released LLM); both cover LLM; picks up the LLM thread on 2026-07-27.
Linked by a graph relationship (Simon Willison released LLM); both cover LLM; picks up the LLM thread on 2026-08-16.
Linked by a graph relationship (Simon Willison released LLM); both cover LLM; picks up the LLM thread on 2026-06-19.
Linked by a graph relationship (Simon Willison released LLM); both cover LLM; picks up the LLM thread on 2026-06-18.
Simon Willison released LLM / Shared entity: LLM / What happened next
Linked by a graph relationship (Simon Willison released LLM); both cover LLM; picks up the LLM thread on 2026-07-31.
Simon Willison released LLM / Shared entity: Treat / What happened next
Linked by a graph relationship (Simon Willison released LLM); both cover Treat; picks up the Treat thread on 2026-07-31.
Simon Willison released LLM / Shared entity: LLM / What happened next
Linked by a graph relationship (Simon Willison released LLM); both cover LLM; picks up the LLM thread on 2026-06-19.