[matiasmolinas]

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 <1 second. No deployment, just pure flow state for scientific computing.

  Current focus: Quantum computing (VQE, QAOA, quantum chemistry) because it's a perfect test bed—rapidly evolving field, requires deep
  domain expertise, complex workflows, high-value automation.

  The "evolving OS" concept: Instead of a static tool, what if your development environment learned your field, extracted patterns into
  reusable skills, and improved its agents based on what actually works in practice?

  Technical: Next.js + Pyodide + Qiskit + OpenRouter. All volumes are Git repos (preserving Claude Code's file-first philosophy). Code
  execution is 100% client-side.

  GitHub: https://github.com/agustinazwiener/evolving-agents-labs/tree/main/llmunix

  Obviously this is rough/experimental—missing lots of polish, limited to Python, quantum-focused. But I'm curious:

  - Would persistent domain memory be useful in Claude Code itself?
  - Are self-modifying agents too weird, or genuinely helpful?
  - Is browser-based execution worth the complexity for scientific/research workflows?

  Feedback welcome, especially from Claude Code users or anyone working in specialized technical domains.