Letta

letta-ai/letta-code

Stateful agents that are like people, with memory, identity, and the ability to learn and adapt

MemGPT: Towards LLMs as Operating Systems

Letta is the platform for building stateful agents: AI with advanced memory that can learn and self-improve over time.

LettaBot - Your personal AI that remembers

Your personal AI with living memory. Remembers everything. Runs on your computer. Grows with you.

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.

Layers of Memory, Layers of Compression

AI superpower = strategic amnesia. Letta caches memory like a CPU, Anthropic spreads it across agent swarms, Cognition warns of chaos. Curious how forgetting makes machines smarter? Dive in.

pguso/ai-agents-from-scratch

Demystify AI agents by building them yourself. Local LLMs, no black boxes, real understanding of function calling, memory, and ReAct patterns.

Building a Semi Autonomous Bluesky Agent with Persistent Memory - Brady Hawkins

Part 1 of building an Agentic AI with augmented memory

Titans + MIRAS: Helping AI have long-term memory

Ali Behrouz, Student Researcher, Meisam Razaviyayn, Staff Researcher, and Vahab Mirrokni, VP and Google Fellow, Google Research

Hermes Agent — Open-Source AI Agent with Memory, Skills, and Cron

The open-source AI agent from Nous Research with persistent memory, reusable skills, tools, cron jobs, GitHub workflows, and multi-platform messaging.

Environments Hub: A Community Hub To Scale RL To Open AGI

RL environments are the playgrounds where agents learn. Until now, they’ve been fragmented, closed, and hard to share. We are launching the Environments Hub to change that: an open, community-powered platform that gives environments a true home.Environments define the world, rules and feedback loop of state, action and reward. From games to coding tasks to dialogue, they’re the contexts where AI learns, without them, RL is just an algorithm with nothing to act on.

Import AI 455: AI systems are about to start building themselves.

The first step towards recursive self improvement

r/Letta_AI

Community for developers building agents with the Letta agents framework.

Supermemory

The memory layer for AI agents. Context engineering platform powering enterprise APIs, developer plugins, and a personal app that remembers everything.

Learning to Continually Learn via Meta-learning Agentic Memory Designs

The statelessness of foundation models bottlenecks agentic systems' ability to continually learn, a core capability for long-horizon reasoning and adaptation. To address this limitation, agentic systems commonly incorporate memory modules to retain and reuse past experience, aiming for continual learning during test time. However, most existing memory designs are human-crafted and fixed, which limits their ability to adapt to the diversity and non-stationarity of real-world tasks. In this paper, we introduce ALMA (Automated meta-Learning of Memory designs for Agentic systems), a framework that meta-learns memory designs to replace hand-engineered memory designs, therefore minimizing human effort and enabling agentic systems to be continual learners across diverse domains. Our approach employs a Meta Agent that searches over memory designs expressed as executable code in an open-ended manner, theoretically allowing the discovery of arbitrary memory designs, including database schemas as well as their retrieval and update mechanisms. Extensive experiments across four sequential decision-making domains demonstrate that the learned memory designs enable more effective and efficient learning from experience than state-of-the-art human-crafted memory designs on all benchmarks. When developed and deployed safely, ALMA represents a step toward self-improving AI systems that learn to be adaptive, continual learners.