Jürgen Leschner on Twitter / X

Wiki Memory

Memory for agents is still early, with little to no standards. “Memory” means something different to everyone. But one common pattern is emerging: wiki memory.

Memory Models: Towards Agents That Learn

Agents that truly learn from experience will be powered by memory models: models that create and curate token-space memory across model generations, trained with memory-native RL.

The rebel alliance

This blog is co-authored with Zoe Weinberg and Matt Hawes at ex/ante, and is a follow-up to our first blog post on the topic, 'You don't own your memory.' We need an open architecture that puts us in control of our memories while making their exploitation technically impossible. But how will this shift happen? In order to discover possible implementations, we must understand how our data informs LLMs. The three predominant context engineering techniques are prompt design, retrieval-augmented ...

Agent Memory Patterns

A short HOW TO guide for agent memory systems. Especially the difference between blocks, files and skills.

ellen livia ᯅ on Twitter / X

here's how Claude Code actually handles memory : all 8 phases 🧵Our team at @mem0ai use @claudeai a lot, we deeply care about memory. here is a summary of how it works 👇User Input -> Context Assembly -> History System -> API / Query -> Response -> SummaryPhase 1: session… pic.twitter.com/hcZbJzbUxB— ellen livia ᯅ (@ellen_in_sf) March 31, 2026

Utkarsh on Twitter / X

Another reason why you want an ambient memory agent is TIME. Your other coding agents understand time differently depending on who or which company writes them. Your machine however should live and breathe with you in your timeline. With Claude, I often find myself begging… pic.twitter.com/XVAvzciplY— Utkarsh (@saxenauts) May 4, 2026

Karpathy's LLM Wiki as Agent Memory - Agentic AI Foundation (AAIF)

At work, I’m building agents to handle various operational tasks and have found Karpathy’s LLM Wiki design to be an excellent solution for implementing most ty…

Memory in Agents: What, Why and How

LLM memory gives language models persistent context across sessions. Learn how it works, how it differs from RAG and context windows, and how to add LLM memory to your agents with Mem0.

Memora scales agent memory to boost long-horizon productivity

AI agents can't remember past conversations. They must constantly reload or retrieve context, which grows less efficient as tasks get longer and more complex. Memora solves this with a scalable memory system separating what’s stored from how it's retrieved.

Letta

Making machines that learn. Create stateful agents that remember everything, learn continuously, and improve themselves over time.

How to forget

Most agent frameworks optimize for recall. Open-strix optimizes for forgetting — and that turns out to be the whole trick.

Claude Memory: A Different Philosophy

A breakdown of Claude's memory implementation, how it differs from ChatGPT, and what these opposite approaches reveal about each company's philosophy.

Claude carries memory into work - Sensemaker

Chat and cloud Cowork now share remembered topics; continuity improves, but so can the reach of a mistake.

gowtham0992/link

Local personal memory for LLM agents