{
  "id": 13242778,
  "title": "6 context types for agent memory",
  "url": "https://urgent.news/2026/10/09/6-context-types-for-agent-memory",
  "topic": "ai",
  "section": "AI",
  "published": "2026-10-09T22:55:40.000Z",
  "source": {
    "name": "Daily Dose of DS",
    "slug": "daily-dose-of-ds",
    "url": "https://github.com/getzep/graphiti"
  },
  "original_language": "en",
  "account": null,
  "summary": "Graphiti is an open-source framework designed for building and querying temporal context graphs, which are temporal graphs of entities, relationships, and facts that track how information changes over time. Unlike traditional knowledge graphs, Graphiti context graphs maintain provenance to source data and support both prescribed and learned ontologies, making them ideal for AI agents operating on evolving, real-world data. The framework is particularly well-suited for applications that require real-time interaction and precise historical queries, as it continuously integrates user interactions, structured and unstructured enterprise data, and external information into a coherent, queryable graph. Unlike traditional retrieval-augmented generation (RAG) methods, Graphiti does not require complete graph recomputation for incremental data updates, ensuring efficient retrieval and precise historical queries without the need for extensive computational resources.",
  "key_points": [],
  "editors_take": null,
  "illustration": null,
  "coverage": {
    "outlets": 1,
    "also_reported_by": []
  },
  "ai_generated": true,
  "disclaimer": "Summaries, key points and the editor’s take are written by software from other outlets’ reporting and may contain errors — always check the linked original."
}