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I love Claude Code, but there are a few capabilities I kept wishing it had. So I built an experimental fork/extension to explore what those might look like.

  Three main additions I wanted:

  1. Persistent Domain Memory
  Claude Code starts fresh each session. I wanted an environment that remembers domain-specific patterns. LLMos adds a three-volume system
  (System/Team/User) where successful workflows automatically become reusable skills. Work on quantum chemistry for a week, and the system
  learns molecular Hamiltonians, ansatz selection heuristics, convergence criteria—domain fluency that compounds over time.

  2. Self-Improving Sub-Agents
  Claude Code has great tool use, but I wanted agents that could observe and improve themselves. LLMos agents literally rewrite their own
  code based on what works. Example: A circuit optimizer starts basic, but after 50+ sessions, it's learned adaptive gradient descent, smart
  initialization, and error mitigation strategies—all from watching successful runs.

  3. Client-Side Code Execution
  Claude Code writes files but doesn't run them directly. I added Pyodide for browser-based Python execution with live preview. Edit code →
  auto-run → see matplotlib plots/quantum circuits in