Self-Evolving AI System with Full Observability
Built an autonomous AI platform that can discover and integrate new capabilities at runtime. Key technical points:
Event-driven core: NATS message bus handles tool discovery, registration, and execution. System observes its own operations and adapts.
Self-improvement loop: AI agents can create and deploy new tools/agents to extend system capabilities—"AI building AI" without human intervention.
Full transparency: Real-time visibility into decision trees, reasoning chains, and inter-agent communication (rare in production AI systems).
Production-ready stack: Docker isolation, Redis for state, K8s orchestration, REST APIs. News feeds trigger autonomous goal generation.
The interesting bit: Unlike typical agent frameworks that are statically configured, this learns new domains by spinning up specialized sub-agents and tools dynamically. Zero-config onboarding of new capabilities.
Trade-offs worth discussing: Event-driven complexity vs. debuggability, autonomous evolution vs. drift/instability, observability overhead at scale.
Help welcome: https://github.com/stevef1uk/artificial_mind.git
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A FOSS project to create an Artificial Mind | Heykuki News