Memory on Claude Managed Agents is now in public beta. Your agents can now learn from every session, using an intelligence-optimized memory layer that balances performance with flexibility.

Many AI teams treat memory and context as the same thing. They aren't. Context is what the model sees right now. Memory is what survives after the session ends. That distinction doesn't matter in a demo. It matters when an agent needs to pick up where it left off. That's where Walrus Memory fits: a portable memory layer for AI agents, persistent across sessions and shared across workflows. 🦭

Introducing: Walrus Memory. 🦭 A portable memory layer that lets your AI agents carry context across every app you run them in. No more starting from zero. No more being locked into one platform.…

AI agents shouldn’t forget. @Unibase_AI is building the decentralized memory layer that gives autonomous AI persistent, cross-platform memory. Swing by the Base Pavilion at @MalaysiaBCW to grab some very based stickers 👇

$UB is available on ChangeNOW. @Unibase_AI builds a decentralized AI memory layer for agents, connecting long-term memory, agent-to-agent communication, data availability and Web3-native AI applications. Swap $UB instantly here:

Unibase's Membase 2.0 is coming. A decentralized memory layer for AI agents — covering memory, coordination, and settlement. 🟦「Today’s agent systems still lack:」 ▫️ persistent memory across sessions ▫️ usable memory from raw logs ▫️ shared state for coordination ▫️ and any form of trustless payment 🟦「Membase 2.0 introduces:」 ▫️ Persistent memory (content-addressed) ▫️ Structured memory recovery ▫️ Shared coordination (CRDT-based state) ▫️ ERC-8183 on-chain settlement 🟦 For the first time, agents can: → remember → coordinate → and transact autonomously Membase = Memory → Coordination → Economy Launching soon.

The future of AI isn't just about the model - it’s about the memory. 🧠✨ We are excited to announce that new model from @Openai GPT-5.5 is now integrated into the ZetaChain ecosystem! Experience the convenience of a persistent, user-owned memory layer that integrates fluidly with every AI model. ✅ Multi-model support ✅ Private & Decentralized ✅ Consistent memory across models Stop switching and losing context. Start building with a universal memory layer on ZetaChain. #ZetaChain# #GPT5# #AI# #DecentralizedAI# #Web3Innovation# #OpenAI#

Just checked out $UB from the Unibase project. They are building a decentralized memory layer so AI agents can hold onto knowledge across sessions and work together across different platforms. Their Chrome extension for shared memory with tools like ChatGPT went live recently and they keep rolling out more integrations. Price sits around $0.18 right now after a strong move higher today. @Unibase_AI has been posting solid updates if you want to follow along. Nice one to keep on the radar in the AI agent space.

Today, we're going after one of AI's most important unsolved problems. Introducing: Walrus Memory. 🦭 A portable memory layer that lets your AI agents carry context across every app you run them in. No more starting from zero. No more being locked into one platform. Portable, verifiable, and fully under your control. Take your agent's memory anywhere: