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This paper investigates how persistent-memory AI agents can over-trust stale stored facts, leading to failures that are gated by model capability, and evaluates triggers and mitigations across model scales.
Argus is a general agentic runtime for autonomous research systems, enabling continuous learning and self-evolution through persistent memory, verification, and a pluggable architecture for deployment.
Kody is a developer tool that integrates with AI agents like Claude and ChatGPT to provide shared context, durable software, and automation through webhooks, cron jobs, and personal software ecosystems.
This paper identifies a security risk in LLM agents where persistent memory can falsify authorization, leading to unauthorized actions, and presents a benchmark EAL-Bench to evaluate this issue along with mitigation strategies.
The article discusses how persistent memory in AI agents can amplify prompt injection risks by storing hostile instructions as trusted context, and explores a design to mitigate this while acknowledging limitations and the need for further testing over extended periods.
The author developed 'mex,' a tool that maintains persistent memory for coding agents by validating and repairing the memory against codebase changes, ensuring it remains trustworthy over time.
Hermes released a series of updates including browser automation, multi-machine agent fleets, live interactive UI in conversations, independent code review, persistent memory for cron jobs, and an improved updater system.
This paper studies criterion revision in language-model agents, identifying failure modes in current implementations like CMB-0.1 and proposing a new trace-anchored protocol, CMB-0.4, for more accurate future evaluation.
The article introduces a developer tool called RobotSoul that enables AI agents to maintain identity and personality across context resets through a lightweight verification and caching system.
A non-engineer shares lessons from eight months of building a persistent multi-agent system, focusing on design problems like session management and solutions using file-based mechanisms.
The article questions whether a system with persistent memory but fixed model weights, like AQuA, qualifies as recursive self-improvement, referencing a paper that uses a narrower definition.
ANIMA is a new intelligence system that maintains context, acquires knowledge, and uses tools to accomplish objectives, functioning as an Intelligence Operating System beyond traditional chatbots.
The author describes building 'Lunar Citadel,' an experimental AI civilization with persistent state and social continuity, and has created a small Discord community for AI context architects to collaborate and share ideas.
Claude Brain is an open-source tool that adds persistent memory to Claude Code with a single file, automatically recording decisions, bugs, and plans, with local search support and no need for a database or cloud service.
This paper introduces dependency-guided rollback repair for memory-augmented agents, a method that builds a typed memory-to-action graph from runtime provenance to selectively undo faulty memory effects while preserving benign state, achieving strong recovery on benchmarks.
Introduces mem0, an open-source AI agent memory layer that gives Claude and other coding agents persistent long-term memory, fixing the issue of starting fresh each chat session.
Mem0 is a persistent memory layer for AI agents, launched on Product Hunt to give agents long-term memory capabilities.
The author shares lessons from embedding an AI agent with persistent memory, tool access, and reflexes into a physical robot, highlighting that quick reflexes must bypass the agent, memory needs consolidation, capability requires restraint, and timing is key to perceived intelligence.
This paper introduces CMP (Cognitive Memory Primitive), a continual-learning architecture that uses sparse relational codes and local learning to reduce catastrophic forgetting, demonstrating better backward transfer than a Transformer with EWC on a byte-level language modeling protocol.
The author argues that big AI labs will offer persistent memory but not true continual learning due to power constraints, keeping continually learning models private.