mindset-dev is where DevOps discipline evolves into cognitive automation — a living laboratory for exploring how infrastructure can reason, adapt, and collaborate.

We're building AI-native systems that blend:

• 🐳 Container Orchestration (Docker Compose, Kubernetes KIND)
• 🧠 Cognitive Frameworks (Flowise, LangChain, LangGraph, n8n)
• 💾 Intelligent Data Layers (Supabase, Qdrant, Neo4j)
• 🌐 Production Infrastructure (Caddy, Cloudflare, Self-Hosted)

"Infrastructure is not just automation — it's cognition."

Our infrastructure operates as a distributed intelligence system where each component contributes to collective reasoning:

graph TD
    subgraph Edge["🌍 Edge & Routing"]
        CF[Cloudflare DNS]
        CA[Caddy Reverse Proxy]
    end
    
    subgraph Orchestration["🐳 Orchestration Layer"]
        DC[Docker Compose Projects]
        K8S[Kubernetes KIND]
    end
    
    subgraph AI["🧠 Cognitive Systems"]
        FL[Flowise]
        LC[LangChain / LangGraph]
        N8[n8n Automation]
    end
    
    subgraph Data["💾 Memory Fabric"]
        SB[Supabase - Relational]
        QD[Qdrant - Vector]
        N4[Neo4j - Graph]
    end
    
    CF --> CA
    CA --> DC
    CA --> K8S
    DC --> FL
    DC --> N8
    FL --> SB
    FL --> QD
    FL --> N4
    N8 --> LC

We don't just automate — we build systems that think, learn, and adapt.

Principles:

1. 🧠 Modularity — Every component is a replaceable cognitive unit
2. 📊 Observability — Insight is the feedback loop of intelligence
3. 🔄 Resilience — Cognitive systems heal through orchestration
4. 🏠 Locality — Self-hosted intelligence within our control

Traditional DevOps automates infrastructure.
Cognitive DevOps creates infrastructure that reasons about itself.

• Pipelines that understand context
• Agents that deploy other agents
• Systems that introspect and evolve

Current explorations include:

• 🤖 AI-Driven K8s Management — Self-healing clusters via LangGraph agents
• 🧬 Cognitive Memory Systems — Vector + Graph hybrid reasoning
• 🔁 Agentic Workflows — n8n + Flowise orchestration chains
• 🏥 Healthcare AI — OpenMRS integration with cognitive layers
• 📊 Observability as Reasoning — Langfuse for LLM introspection

👉 ai-infra-hostinger Docs — Architecture, network topology, and system design

👉 local-ai-packaged — Full Docker Compose setup with installation guide

This is an open exploration of AI-native infrastructure. Watch our repos, try our setups, and contribute ideas.

Phase 1: Foundation ✅

• Core AI stack deployment
• Comprehensive documentation
• Multi-project orchestration

Phase 2: Expansion 🔄

• LangGraph control plane
• FastMCP integration
• Public observability dashboard
• MkDocs documentation site

Phase 3: Cognitive Systems 🔮

• Self-learning infrastructure
• Agent-to-agent orchestration
• Federated multi-server mesh
• AI-driven network routing