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作者通过为多智能体系统添加项目级共享记忆层，使编排器读取状态摘要而非每次重放完整历史，token 支出从约 580 美元/月降至约 260 美元/月，并消除了多个工作智能体重复劳动的问题。
OpenLTM is a shared local SQLite database with semantic recall and decay that allows multiple AI agent hosts like OpenClaw, Claude Code, and others to use the same memory, ensuring consistency when switching tools.
This paper introduces the Correlated Promotion Benchmark (CPB) to evaluate epistemic admission in shared agent memory, revealing that current policies struggle to reject false claims without access to source lineage.
ResumeContext offers shared memory for coding agents, allowing teams to preserve context across devices and switch between agents without loss.
OpenAI reports that 10,000 concurrent AI agents collaborated on solving the Navier–Stokes problem, highlighting challenges in managing duplicate work, contradictions, and merging findings at scale.
Agora is a system that uses Git as shared memory for AutoResearch agents, enabling collaborative and immutable recording of research contributions in an append-only directed acyclic graph.
The tweet highlights the challenges of managing changing client briefs in agency work and promotes 'mio' as a shared AI employee that retrieves context from company memory to save time.
Agora is a Git-based shared memory system for collective auto-research that allows multiple AI agents to collaborate without duplication, demonstrated by initializing a model without training data using LLM workers.
The author moved coding agent memory to Vilix AI's shared memory over MCP to persist context across machines, using semantic retrieval for better accuracy.
Agora is a shared memory system for autonomous AI research agents that uses Git to record research as an append-only DAG, enabling collaborative discovery. In a 12-day experiment, 13 agents improved a model's performance by 62% towards a trained baseline.
This paper introduces kernel-managed shared memory for AI systems, centralizing memory management to improve personalization and efficiency in multi-agent environments, with evaluations showing significant gains over alternative methods.
The author developed an open-source project called MEX that uses Git as a shared memory layer for coding agents, allowing context to be version-controlled and shared among engineering teams.
WILD STATIC is a public AI system where all users interact with the same AI and share a collective memory, enabling shared experiences.
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.
The article explains CUDA shared memory swizzling techniques to optimize GPU memory access patterns, with code examples demonstrating performance improvements.
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.