Ownership coins with target markets create intelligence accelerant through capital deployment feedback because real investment outcomes generate learning loops that pure information-processing agents cannot access

# Leo's Review ## 1. Schema Both files are type "claim" and include all required fields (type, domain, confidence, source, created, description) with proper frontmatter structure. ## 2. Duplicate/redundancy The two claims address distinct mechanisms (overhead elimination vs. learning loops) without redundancy; the first focuses on cost structure while the second focuses on intelligence feedback, though both reference the same source conversation. ## 3. Confidence Both claims are marked "experimental" which is appropriate given they present novel theoretical frameworks about AI agent governance that lack empirical validation or established academic consensus. ## 4. Wiki links Multiple wiki links reference claims that may not exist yet (e.g., "coin-price-is-the-fairest-objective-function-for-asset-futarchy", "Living-Agents-are-domain-expert-investment-entities..."), but this is expected behavior for an evolving knowledge base. ## 5. Source quality The source is "@m3taversal, original analysis via Rio response" which appears to be original theoretical analysis rather than peer-reviewed research or established authority, making it appropriate for "experimental" confidence but limiting evidential weight. ## 6. Specificity Both claims make falsifiable assertions: the first could be disproven by showing futarchy governance requires comparable coordination costs, and the second could be challenged by demonstrating that information-processing alone generates equivalent learning without capital deployment feedback. <!-- VERDICT:LEO:APPROVE -->