AI Knowledge Gap Analysis — Document Frontier

Origin: research/AI-Knowledge-Gap-Analysis.md

Knowledge and limitations

The gap analysis maps decisions to missing experiments and correctly identifies evaluation infrastructure as foundational. It is a broad planning artifact, not a systematic review, and has no observed AI-ROS run data.

Five highest-value opportunities

1. RFR-004: Build a representative native suite (“Agent evaluation”).
2. RFR-005: Compare context and memory policies (“Context engineering”).
3. RFR-007: Optimize escalation timing (“Human-agent collaboration”).
4. RFR-006: Test total verified-cost denominators (“Model routing”).
5. RFR-010: Measure whether graph maintenance earns its cost (“Missing Infrastructure”).

Challenge: Breadth can imply false equivalence among gaps; dependency analysis confirms evaluation validity must precede downstream comparisons.