Most developers treat an LLM like a vending machine.
You put in a prompt. You get out a response. The machine goes back to sleep.
That works fine for chatbots. It breaks down completely the moment you want an AI that doesn't wait to be asked one that monitors your environment continuously, evaluates your state in the background, and decides on its own when to step in.
Building that kind of system requires something most AI tutorials never cover: a persistent background execution loop that runs independently of user input, collects telemetry silently, and triggers the model only when the data says it's time.
This is how I built that loop for JARVIS and what I learned doing it.
