Came across an early open-source project aiming to fix a big gap in current LLMs: statelessness. Every conversation resets to zero. LLM-OS tries to give AI sys

Came across an early open-source project aiming to fix a big gap in current LLMs: statelessness. Every conversation resets to zero. LLM-OS tries to give AI systems persistent, evolving memory by treating everything as a memory artifact: Crystallized tools: repeated patterns auto-convert into executable Python tools (deterministic memory). Markdown agents: editable behavioral memory. Execution traces: procedural memory the system can replay/learn from. Promotion layers: memory flows from user → team → organization via background “crons.” The idea is that organizations accumulate AI knowledge automatically, and new members inherit it. Repo: https://github.com/EvolvingAgentsLabs/llmos https://github.com/EvolvingAgentsLabs/llmos Article: https://www.linkedin.com/pulse/what-your-ai-remembered-everything-got-smarter-mat%C3%ADas-molinas-esvgf https://www.linkedin.com/pulse/what-your-ai-remembered-every... Curious whether HN thinks persistent AI memory is workable