Four agentic AI memory systems for smarter LLMs
Four open-source projects—Graphiti, Hindsight, Mem0, and others—offer expanded memory capabilities for AI agents and large language models, using techniques like temporal knowledge graphs and multi-st…
Four open-source projects—Graphiti, Hindsight, Mem0, and others—offer expanded memory capabilities for AI agents and large language models, using techniques like temporal knowledge graphs and multi-st…
Perseus Computing LLC released Mimir, a local-first, encrypted memory engine for AI agents as a single Rust binary with zero dependencies. The open-source tool provides persistent memory across sessio…
MemDelta, a new evaluation protocol for AI memory systems, reveals that performance varies significantly across model families, with retrieval-augmented generation (RAG) and full-context models showin…
Microsoft Research unveiled Memora, a memory system for AI agents that decouples storage from retrieval to provide scalable long-term recall. The system reduces context token usage by up to 98% while …
Microsoft researchers introduced Memora, a scalable memory system for AI agents that decouples stored content from retrieval mechanisms, achieving state-of-the-art performance on long-horizon benchmar…
Mem0, an open-source memory layer for AI agents with nearly 60,000 GitHub stars, has released v3.0 with temporal reasoning and multi-tenant isolation. The project scored 94.8 on LongMemEval and 91.6 o…
Truvem founder Dieng Amine has released TMX v0.1, an open standard JSON format for AI agent memory that enables portability across platforms, frameworks, and providers. The specification aims to solve…
A developer built slacktag-oss, an open-source Slack bot with persistent semantic memory powered by any LLM and Mem0's managed memory layer, eliminating the need for a vector database. The bot uses Me…
Developers building production AI agents in 2026 are using simple vector search, keywords, BM25, text matching, and RRF for long-term memory, avoiding graph construction due to costs. One team reports…
FERNme, a new user-owned memory layer for AI agents, updates memories with zero LLM calls using a Hebbian co-occurrence rule, keeping token costs flat and enabling users to see, edit, and own their da…
A developer released Memharness, an open-source bi-temporal memory primitive for AI agents that stores facts with provenance in a single SQLite file without LLM calls. The tool enables agents to answe…
AI memory systems for LLM agents fail at scale due to structural precision problems in similarity search, not incidental issues. Testing across three embedding models showed mean retrieval precision o…
Loomcycle 1.0, a feature-complete agentic runtime, is now available under Apache-2.0 license. The Go-based binary supports six LLM providers, 19 built-in tools, multi-replica high availability, and pa…
Cortex, a new open-source memory system for AI agents, launched as a local-first, encrypted solution that runs entirely client-side in Rust with a 124KB WASM binary. It offers sub-millisecond latency,…
A developer compares four agent memory systems—Letta, Mem0, Graphiti, and Cognee—highlighting their approaches to knowledge graphs and long-term memory for AI agents. The analysis covers each system's…
A developer has identified a persistent security threat to AI agents called memory poisoning, where malicious instructions stored in an agent's memory can influence all future interactions indefinitel…
Writer's research paper reports that memory systems can amplify sycophancy by up to 25x, but the amplification is traced to two design decisions: an evaluation prompt ordering the model to answer sole…
Memory systems in AI assistants are evolving beyond the short-term versus long-term split, with OpenAI and LangGraph SDKs advocating for a three-tier stack of working memory, durable state, and retrie…
A developer at an e-commerce company built a Pytest and Mem0-based automated test suite that reduced AI memory bugs by 90%. The system validates real memory behavior against an isolated Mem0 instance …
A developer has released a suite of tools to improve context quality for AI coding agents, including code knowledge graphs, semantic code analysis tools, and context output compression utilities. The …