AI Memory
A practical map of durable AI memory, RAG limits, graph-backed recall, provenance, and conflict handling.
Quick answer
AI memory is the durable context layer behind an assistant or workflow. Useful memory needs more than vector search: it needs source evidence, structured claims, promotion gates, stale-fact handling, conflict resolution, and retrieval policy.
Best for
Use this path if you are comparing RAG, vector search, graph memory, and long-term assistant memory for real AI workflows.
Questions This Answers
- Why is RAG not enough for long-term AI memory?
- When should memory use vectors, graphs, or both?
- How do AI systems avoid silently overwriting stale facts?
- What belongs in memory versus prompts or skills?
Articles
Stop Teaching Every AI From Scratch
A personal Dense-Mem reflection on the problems that pushed me beyond static skills and stale files toward dynamic shared memory, read-only automation context, import/export, and governed knowledge graphs.
I Feel Sorry for AI
Why both AI hype and anti-AI hostility miss the same point: LLMs behave more like straight-A new graduates than senior experts, and useful agents need onboarding, skills, and maintained memory rather than impossible first-attempt expectations.
Skills + Dense-Mem: Making AI Workflows Learn From Experience
A hypothesis for combining AI skills with Dense-Mem: keep workflow, safety rules, and acceptance criteria in skills, while memory stores expectations, examples, corrections, failures, and portable skill-pack knowledge.
Try Dense-Mem in 5 Minutes With the Hosted Demo
A quick tutorial for using the hosted Dense-Mem test instance, connecting Claude Code and Codex to the same temporary memory, and seeing how shared context helps AI work smarter.
Dense-Mem Quick Start: Give Claude Code and Codex the Same Memory
A beginner-friendly tutorial for spinning up a local Dense-Mem server, creating your first memory key, and connecting Claude Code and Codex to one shared AI memory brain.
Secure Dense-Mem on Vultr with Traefik
A nontechnical walkthrough for launching Dense-Mem on a Vultr cloud server with Traefik, HTTPS, private control-portal access, and shared memory for personal, family, or work AI tools.
AI Memory Beyond RAG: Vectors, Graphs, and Dense-Mem
RAG is not magic memory. A practical explanation of chunks, embeddings, vector search, graph-backed memory, and why durable AI memory needs provenance, conflict handling, and retrieval policy.
Manuals
Projects
Dense-Mem
Standalone HTTP MCP memory server for LLM hosts with durable graph memory, typed claims and facts, server-side embeddings, team/profile isolation, and recall.