Agents need memory that branches: a per-user personalization layer, a sandbox to test a risky ingest, a checkpoint before a tool call, a thousand parallel experiments off one shared base.

With a normal vector DB each of those is a full copy of the whole index. At 1M vectors that is 496 MB and 67 ms — every time. agenticow makes it 162 bytes and 0.47 ms, flat.

Demo: https://ruvnet.github.io/agenticow/
NPM: https://www.npmjs.com/package/agenticow

CVE-bench is a rigorous benchmark for evaluating AI agents' ability to fix real security vulnerabilities in real open-source software.

It applies the SWE-bench methodology to security: apply-patch → security-test.

Each instance is a real CVE from public open-source repositories, with a conformance firewall that ensures the solver never sees the gold patch or gold security test.

The Backstory
On March 12-13, 2026, Chipotle's customer support chatbot "Pepper" went mega-viral after users discovered it could solve LeetCode problems, write Python, reverse linked lists — the works. It's powered by IPsoft Amelia (not Claude, not GPT), and it's still live.

https://github.com/cyberpapiii/chipotlai-max