[matiasmolinas]

Built a browser-based AI OS where a master agent creates/evolves specialized sub-agents defined in markdown, executes Python via WebAssembly, and learns from past executions via persistent memory.

Key features: - Agent reuse & evolution (80% match rule) - Python runtime in browser (Pyodide: numpy, scipy, matplotlib) - Memory system that improves over time - Virtual file system (localStorage) - Completely client-side

Example: Ask for "FFT signal analysis" → system checks memory → finds/evolves SignalProcessorAgent → generates Python → executes in browser → saves results → records experience → next time runs in seconds.

Try it: https://github.com/EvolvingAgentsLabs/llmos

Started as a weekend project exploring self-improving AI systems. Core features working, some rough edges.

Feedback welcome, especially on the agent evolution approach and memory structure.