When Linus posted Linux 0.01 in 1991, he wrote: "I'm doing a (free) operating system (just a hobby, won't be big and professional)." It wasn't complete. It wasn't polished. But the core ideas were there.

  I've been thinking about what an "operating system" for LLMs would look like. Not an agent framework – an actual OS with
  memory hierarchies, execution modes, and something I'm calling a "Sentience Layer."

  LLM OS v3.4.0 is my attempt. It's incomplete and probably over-ambitious, but the architecture is interesting:

  Four-Layer Stack:
  - Sentience Layer – Persistent internal state (valence variables: safety, curiosity, energy, confidence) that influences
  behavior. The system develops "moods" based on task outcomes.
  - Learning Layer – Five execution modes (CRYSTALLIZED → FOLLOWER → MIXED → LEARNER → ORCHESTRATOR) based on semantic trace
  matching
  - Execution Layer – Programmatic Tool Calling for 90%+ token savings on repeated patterns
  - Self-Modification Layer – System writes its own agents (Markdown) and crystallizes patterns into Python

  What makes it different:
  - Agents are Markdown files the LLM can edit (hot-reloadable, no restart)
  - Traces store full tool calls for zero-context replay
  - Repeated patterns become pure Python (truly $0 cost)
  - Internal state persists across sessions and influences mode selection

  Working examples:
  - Quantum computing IDE backend (Qiskit Studio)
  - Educational platform for kids (Q-Kids Studio)
  - Robot control with safety hooks (RoboOS)

  Is it production-ready? No. Will it work as envisioned? I'm figuring that out. But the ideas feel right, and building it is
  genuinely fun.

  GitHub: https://github.com/EvolvingAgentsLabs/llm-os

  Looking for feedback on the architecture, collaboration on making it actually work, and honest criticism. What's missing?
  What's overengineered? What would you want from an LLM OS?