Local First AI and Agent Operations
This planned 13-part series follows the work of turning a local-first collection of AI models, agents, services, memory, and developer tools into an environment I can inspect, recover, and improve without hiding the hard parts behind another layer of automation.
The main installments appear in Technology. Runnable companion articles appear in Hands-On. The companions are optional: they sit beside the main sequence instead of interrupting it, so you can follow the engineering argument straight through or pause when you want to build the smaller working example.
Main Series
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When a Local AI Stack Becomes an Operations System
The model may be running while the system around it is still broken. This is how a local-first AI experiment became an operations problem involving ownership, dependencies, readiness, recovery, and rollback.
Hands-On Companions
Across the Series
Later installments also cover measuring token optimization, passive model-proxy instrumentation, multimodal context hygiene, operator-ready packaging, cross-host voice services, Apple Silicon inference, installable skills, safe multi-agent operation on one LAN, and an honest public-release readiness assessment.