knowledge-flywheel-amplifier

Cross-source knowledge merging combines article-derived and conversation-derived signals to form cohesive topic surfaces while preserving provenance boundaries. It generates amplifier reports, topic updates, and candidate research seeds without overhauling original source signals.

You can automate nightly research context updates by running the 04:00 amplifier stage of the knowledge flywheel. This merges Stage A and Stage B outputs to produce amplifier reports and open-question updates with explicit ownership and traceability.

Yes, conservative cross-source merging preserves provenance and boundaries between sources. It writes provenance-preserving updates to Brain indexes, surfaces only high-value changes, and commits changes with explicit ownership to prevent uncontrolled deep research.

The best way to generate candidate research seeds is to merge cross-source signals using the nightly amplifier workflow. This process creates context-pack drafts and pattern surfaces that guide downstream exploration and knowledge graph updates.

You should avoid using an automated knowledge flywheel amplifier when you need to overhaul or directly alter source signals, as it is designed for conservative updates. It only surfaces high-value changes and prevents uncontrolled deep research through strict traceability.