A different set of trade-offs
Running an assistant on your own computer changes the conversation. Instead of asking only about capability, you start asking about memory, power, setup, and what can work without a network connection. These are practical constraints, and they can be useful ones.
Privacy is a system property
Local inference can keep a prompt away from a remote model provider, but local does not automatically mean private. The application may still use telemetry, download assets, or contact external tools. File permissions, logging, and software updates remain part of the picture.
A sensible first step is to understand the complete data path. Where are documents indexed? Where are conversations saved? Does a search feature make network requests? The answers matter more than a label on a download button.
Find a repeatable use
Local tools are easiest to assess with a small, repeatable task: summarizing a folder of notes, drafting text from a template, or searching a personal reference collection. Keep the original material available so that generated claims can be checked.
The takeaway
Local AI is not a universal replacement for hosted services. It is an option with a different balance of control and convenience. For the right workload, that balance is the feature.
