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 …
LoreConvo and Mem0 offer contrasting approaches to AI agent memory, with LoreConvo using structured, user-committed sessions stored locally in a SQLite file, while Mem0 automatically extracts facts in…
Modern agent memory architectures move beyond simple context windows by extracting facts, preserving episodes, building semantic structure, and retrieving through multiple signals. The design choices—…
A developer building in public for 21 days discovered that every major agent memory API—including Mem0, Zep, Letta, and OpenAI's Assistants—is missing a lifecycle state field to mark facts as supersed…
A solo developer in Accra, Ghana, has launched AgentRAM, a memory API for AI agents that eliminates the need for vector databases or embedding pipelines. The service provides durable key-value memory …
Researchers have introduced "Behavioral Specification" as a new interpretive layer for AI memory, arguing that current systems optimized for factual recall fail to capture how a specific person proces…