shared-memory

The article discusses a Stanford paper that identifies information loss during handoffs as the most common error in multi-agent systems and presents architectures and a standard loop with shared memory, message schemas, observability, and guardrails to enhance performance.

Introduces MAP-Graph, a provenance-aware shared memory layer for multi-agent workflows that filters by permissions, reranks by path trust, and gates risky actions, achieving 94.96% task success in controlled benchmarks.

Yohei Nakajima set up a shared memory system across ChatGPT, Codex, Claude, and Claude Code, using local history for the coding tools and a scheduled recap skill for ChatGPT/Claude so any one can answer questions about recent work across all four.

UML (Universal Memory Layer) is an open-source shared memory graph for Claude, ChatGPT, and other AI agents, letting users save and recall structured memory across tools via MCP with a visual dashboard and API.

A hands-on review of Activeloop's Hivemind, which mined 19 reusable skills from agent traces, demonstrated selective memory by skipping already-documented workflows, improved cross-session recall on complex tasks, but showed recall issues and overhead on short tasks.

A developer demonstrates how two AI agents with shared memory running locally on a laptop can catch and prevent bad decisions, even after a restart. The key insight is that persistent shared memory enables agents to operate as a real team.

Agent Mesh is a shared memory system for coordinating multiple AI agents, featuring a decision log, backlog, and dashboard UI. It allows agents to communicate via a SQLite database and supports agent-agnostic integration.

Scritty provides shared, searchable memory for every AI coding agent.

Macro is a workspace app that unifies your work into one app with shared memory.

This paper introduces MemClaw, a governed shared memory architecture for multi-agent LLM systems, formalizing failure modes like unauthorized leakage and stale propagation, and evaluating the system via the ArgusFleet harness.

A developer built kaeru, an open-source shared memory system for AI agents that allows them to persist context across sessions, share knowledge between different agents and humans, and visualize memory as a 3D galaxy. The tool supports multiple agent frameworks and includes features like time-travel, importance levels, and reasoning trails.

Bun has an open pull request that adds support for shared-memory threads to JavaScriptCore, the JavaScript engine underlying WebKit. This enhancement could improve performance for multi-threaded JavaScript workloads in Bun.

A tweet sharing a naive CUDA softmax implementation using shared memory reduction, noting that reduction is straightforward.

GateMem is a benchmark for evaluating memory governance in multi-principal shared-memory agents, covering utility, access control, and forgetting across medical, office, education, and household domains. Current methods fail to balance all three, showing that reliable shared institutional deployment remains elusive.

Hivemind is an open-source tool that allows multiple AI Coding Agents (e.g., Claude Code, Codex, Cursor) to share a memory layer, automatically mining high-quality patterns from usage trajectories and converting them into reusable skill files, enabling cross-tool and cross-team skill propagation, significantly reducing token consumption and interaction rounds.

Discusses the challenge of persistent memory for personal AI agents across sessions, comparing setups like Custom GPTs, Mem, and Open Campus's shared memory approach, and asks for community recommendations on handling memory conflicts.

Discusses how to establish shared memory among multiple AI agents to avoid repeating mistakes, and introduces a solution by modifying the MemOS CLI to only record key information and search when necessary.

Glen is a shared memory layer for AI agents that enables agents across a company to share knowledge and skills dynamically, with RBAC and integration with tools like Cursor, Claude code, and others.

NetworkChuck announced a massive deployment of Hermes using a full team with isolated VMs and shared memory from Honcho, in collaboration with Nous Research.

A quote tweet discusses gBrain being state-of-the-art for a specific use case, with a shared memory layer architecture under Hermes Agent.