A systems engineering reference library built through intensive study of infrastructure, distributed systems, and production architecture patterns.
This repository contains design patterns, reference implementations, and experimental infrastructure concepts developed while mastering systems engineering from first principles.
- Distributed AI Systems: Multi-node Ollama orchestration, agent coordination, memory management
- Custom Development Tooling: Scaffolding systems, environment managers, deployment automation
- Security Architecture: GPG/SSH management, encryption patterns, secrets handling
- Container Orchestration: Docker configurations, service management, networking patterns
- ai-agency: Distributed AI orchestration for lead generation and business automation (active development)
- openhwy: Trucking industry AI platform with specialized agent architecture
- zbox-environment: Agent environment with PostgreSQL memory system and ZSH orchestration
- bookmark-studio: Custom knowledge management system architecture (design phase)
- Authentication Service: User auth, session management, security patterns (Go)
- Payment Service: Transaction processing, webhook handling (Go)
- Email Service: Template rendering, delivery management (Go)
- User Service: Profile management, CRUD operations (Go)
Extensive documentation covering:
- Database design (DuckDB, SurrealDB, PostgreSQL, vectorization)
- Programming languages (Rust internals, Go patterns, Python, TypeScript)
- Security practices (encryption, backups, sandboxing, GPG workflows)
- System architecture (distributed systems, microservices, orchestration)
- Development environments (ZSH configuration, shell optimization, tooling)
These projects serve as a personal knowledge base - each built to understand specific concepts at a deep level:
Learning Method:
- Build systems from scratch to understand fundamentals
- Intentionally break and rebuild to learn failure modes
- Document patterns and architectures for future reference
- Work in terminal, avoid GUIs, master underlying systems
Current Status: Most projects are reference implementations or partially complete learning vehicles. They demonstrate understanding of concepts and serve as patterns for production work. The codebase is a goldmine of tested approaches, reusable components, and architectural patterns.
Active Development:
ai-agency- Near production-ready, operational on 4-node distributed system- Windmill workflow integration for business automation
- Infrastructure consulting for trucking/logistics industry
Systems: Linux (Arch, Debian, Rocky), NixOS exploration, custom kernel compilation
Languages: Rust, Go, Python, TypeScript, Dart/Flutter, Lua
Infrastructure: Docker, PostgreSQL, SurrealDB, Redis, Nginx, Caddy
AI/ML: Ollama, OpenVINO, distributed model orchestration
Security: GPG, SSH, encryption, secure secrets management
Built by a systems engineer with 10 years of trucking operations experience, now specializing in infrastructure and custom software for the logistics industry. Deep understanding of both domain operations and technical implementation.
This is a reference repository for studying system design patterns and architectural approaches. Components can be adapted for production use but would require proper testing, hardening, and validation for specific use cases.
Philosophy: Understand every layer before building production systems. These projects represent that understanding.
☕ Grab a coffee and explore the architecture
Take your time diving into the patterns, designs, and implementations. Each project teaches something specific about building robust systems.
All code and documentation in this repository is provided as-is for educational and reference purposes. Use, adapt, and learn from it freely - just understand what you're working with before deploying to production.