self-improve

Automating AI governance for reasoning traces involves scheduling a weekly review routine to curate learning, evaluate dreaming proposals, and promote approved changes to your brand's knowledge base. The process requires human oversight to ensure decisions align with brand objectives and values.

Curating brand learning from previous AI interactions is best handled by running a scheduled self-improvement routine that reviews reasoning traces from the previous week, identifies valuable insights, and promotes them to update the brand's knowledge base.

Dreaming proposals in a brand AI system are potential improvements generated from reasoning traces. A weekly governance process manages these proposals by evaluating them against brand objectives and using human input to decide whether they should be promoted or dismissed.

Automating self-improvement governance requires human oversight to ensure that decisions regarding reasoning traces and dreaming proposals align with brand objectives and values. The automation streamlines the weekly review process but relies on human input for final approvals.

Reasoning trace curation can be run as a scheduled weekly routine to keep a brand's knowledge base up-to-date. This routine automatically reviews the previous week's traces, identifies valuable learning, and prepares dreaming proposals for human evaluation and promotion.

Fully automating the promotion of dreaming proposals is not recommended because decisions must align with brand objectives and values. The governance workflow is designed to streamline evaluation but requires human input to dismiss or implement proposals safely.