Work

Local AI and intelligent scaffolding

I spent a weekend testing a practical question: how much useful agentic work can stay local when the model is surrounded by better structure?

The experiment used narrow agent responsibilities, isolated execution, observable queues and an independent supervisory path. The model was not treated as the control system. It operated inside one.

The lasting observation was that governance lives in the scaffolding around the model: context, tools, permissions, handoffs, telemetry and the ability to stop work cleanly.