Operate local AI responsibly
Map the complete data flow
Follow prompts, files, tool results, logs, telemetry, and backups before claiming that a local AI feature is private.
Running the weights locally removes one network dependency. It does not prove the complete application is private.
Draw every place data can travel:
input -> application -> local model -> output
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logs telemetry tools backupsA local agent may call web search. A desktop application may send crash reports. Your own application may log prompts to a hosted service. A backup may copy generated files to cloud storage.
Classify the data before choosing the model. Decide which fields may enter prompts, which must be removed, how long outputs remain, and which tools may receive derived information.
Bind a local server to the smallest network boundary possible. Add authentication and isolation when several users or devices share it.
Privacy is a property of the whole data flow, not a label attached to the model.
Lesson completed