RECALL-X: Building an AI Incident Response Agent That Learns From Every Security

<p>`---<br /> title: "Why I Built a Brain for My AI Agents — and What It Taught Me About Memory"<br /> published: true<br /> description: "Anamnesis v0.3.0: The cognitive

<p>Most agent frameworks treat memory as an afterthought. They give your agent tools, prompts, and orchestration patterns — but when you restart the conversation, everything

<p>Most AI agents have amnesia.</p> <p>You close the chat window. They forget everything. Every session starts from zero. Every context window fills up and dumps the earliest

<!-- SC_OFF --><div class="md"><p>I’ve been building Signet, an open-source memory substrate for AI agents.</p> <p>The problem is that most agent memory systems are still

<p>When an incident starts at 3 AM, the first question is rarely “Can we search our database?”</p> <p>It is usually something closer to:</p> <p><strong>“Has this happened before,

arXiv:2604.01007v1 Announce Type: new Abstract: AI agents increasingly operate over extended time horizons, yet their ability to retain, organize, and recall multimodal

arXiv:2603.23231v1 Announce Type: new Abstract: Empowering large language models with long-term memory is crucial for building agents that adapt to users' evolving needs. However,

<p>Two independent security research groups published this week with findings that land on the same problem from different angles: AI agent skill files are a serious and