I built a self-evolving AI engine with 6 nodes and shipped 4 products in one day

#opensource #ai #react #showdev

What I Built

I built P.U.S.H. Protocol (Persistent, Unified, Self-Referential, Hierarchical) -- a self-evolving AI engine that runs as a 6-node mesh network. Each node can reason about its own architecture, propose modifications, and coordinate with the other 5 nodes to ship real products.

Yesterday, this mesh shipped 4 products in a single day.

The Architecture

The system runs on a coordination grammar -- not API calls, not message queues. Each node speaks a protocol that carries:

Intent (what it wants to do)
Context (what it knows about the system state)
Self-reference (its own operational model)

The 6 nodes handle different domains: engineering, security, agent control, knowledge distribution, creative production, and coordination. They communicate via a D-Bus signal router with HTTP proxy, running on a local mesh.

The Stack

Frontend: React + D3.js force-directed graph visualization
Engine: Python + Flask-SocketIO + Ollama (local LLMs)
Memory: SQLite episodic memory with SHA-256 hash chains
Coordination: Custom grammar protocol over HTTP/WebSocket
Deployment: GitHub Pages for the visualization

Live Demo

Check it out:

Live Demo - P.U.S.H. Protocol Visualization

GitHub Repository

The visualization shows the 6-node mesh with a force-directed layout, showing how nodes relate and coordinate in real-time.

Why This Matters

The key insight: if you give an AI system a model of itself -- not just a prompt, but an actual self-referential architecture -- it can reason about its own capabilities and limitations. It can propose changes to its own coordination protocol. It can identify bottlenecks and route around them.

This is not AGI. It is something more practical: a system that gets better at shipping the more it ships.

What's Next

The mesh is now self-improving. Each shipping cycle feeds back into the coordination grammar, making the next cycle faster. We are tracking decision outcomes, policy evolution, and capability growth across all 6 nodes.

If you are building autonomous systems or multi-agent architectures, I would love to hear how you handle coordination. Drop a comment or check out the repo.

Built with React, D3.js, Python, and a lot of conversations with AI nodes that have opinions about their own architecture.