NotionHesham SalmanExplainer
Building Shared Memory for AI Agents in Notion
Summary
Lore is an open-source, MIT-licensed tool from Notion for giving AI agents shared, persistent memory backed by Notion, addressing experiential knowledge, follow-up tasks, decision records, and procedures that can disappear between sessions. A Lore vault uses five related Notion databases—Projects, Topics, Memories, Entities, and Facts—with MCP tools for agents, Notion or a CLI for humans, and hooks intended to retrieve context and save information in the background. The design emphasizes memory maintenance: facts expire by default, relationships such as supersedes and conflicts_with clarify updates, and the CLI can identify orphaned or duplicated information. In a 500-query SkillRet retrieval evaluation, Lore achieved 84% success, while a paired model evaluation found seeded memory recovered about 46% of failures on tasks never solved without memory. The results indicate that relevant, well-maintained memory can improve agent performance, while stale or irrelevant content can harm it.
Context
Agent sessions were accumulating experiential knowledge, tangential follow-up tasks, decision records, and procedures that had to be manually extracted or could disappear when nobody reviewed the transcript. Existing memory systems were described as localized to a harness, model provider, or machine, limiting sharing between agents and people across an organization.
Approach / What changed
Lore stores shared agent memory in a Notion vault composed of five related databases: Projects, Topics, Memories, Entities, and Facts. Agents access it through MCP tools, while humans use Notion or the Lore CLI. Hooks support automatic context retrieval and background saving, with expiring facts, relational updates, and maintenance tools intended to control memory quality.
Takeaways
Lore vaults organize memory across Projects, Topics, Memories, Entities, and Facts, with relations that support predictable searching and information discovery.
Facts expire by default, and relationships such as supersedes, scoped, and conflicts_with make updates explicit; the CLI can find orphaned facts, duplicates, and other memory debt.
In evaluations, Lore achieved 84% success on 500 SkillRet queries, and seeded memory recovered about 46% of failures on tasks the no-memory agent never solved.
Source and freshness
- Source
- notion.com
- Published
- Added to Yomu
Summaries are generated from the original by a language model. Check the original before relying on it.
Keep reading
Related reading
The Good Stuff
Paid picks we use ourselves. Links carry a referral code — a subscription through one earns us a commission at no extra cost to you.
The best engineering reads, once a week
One useful email. Unsubscribe anytime.