I have spent the last few months tuning how I actually run AI day-to-day. The result is a setup that mixes a cloud subscription for the heavy lifting with a local model as a safety net, all wired through a single coding agent that can route different sub-tasks to different models. In this post I will walk through the pieces: the Ollama Cloud subscription, the Pi agent, and the multi-model subagent configuration I use for project development and local hosting tasks — with the local model fallbacks for outages, subscription exhaustion, or remote work.

Google’s Gemma 4 is a surprisingly powerful local agentic AI model that can run on local hardware, making it a very welcome addition to my programming suite of tools. In this Blog I will cover my experience with Gemma 4, how to set it up, and some of the things I have been using it for. I will also cover some of the limitations and challenges I have faced with using a local agentic AI model.