Self-Hosting

From Chatbot to Self-Hosted AI Infrastructure My AI setup started as a model choice: GPT or Claude, local or hosted, bigger context window, cheaper tokens. That still matters, but it is not enough once an assistant can read notes, call tools, remember preferences, and interact with infrastructure. This post covers the shape of the setup. The deeper details belong in the follow-up posts. The setup in layers At home I run Hermes as the agent layer on my main Linux machine. It talks to model providers, but it also has access to local tools, memory, scheduled jobs, and messaging. Around that sits a Docker-based infrastructure stack for knowledge retrieval, memory, search, monitoring, secrets, reverse proxying, and voice experiments with Whisper, Piper, XTTS, and Ollama. ...

My Self-Hosted Docker Infrastructure Why Self-Host? Before diving into the technical details, let me explain why I chose this path. Self-hosting gives me: Control over my data - No third-party has access to my files, passwords, or personal information Privacy - Everything runs on my own hardware, behind my own firewall Learning opportunities - Running production services teaches you things you can’t learn from tutorials Cost savings - One-time hardware investment vs. ongoing subscription fees Customization - I can tweak and optimize everything to work exactly how I want But self-hosting isn’t just about avoiding Big Tech. It’s about building something you understand from the ground up. ...