The Creator Studio is the content-generation frontend; the learning loop is demonstrated by the dedicated MemoryAgent judge lab included in the hackathon build. Judge test scenario: Start with Reset memory. The agent displays: “No performance history yet — the agent is exploring.” Select the outcome “Brazil · TikTok · Luxury Reveal drove $800 in mints.” Observe that:the reinforced-outcome counter increases; the TikTok, Brazil and Luxury Reveal memory weights increase; the next content batch is re-ranked; the exact Qwen prompt changes to include the newly learned preference.
Select “Argentina · Instagram · Unboxing ASMR drove $1,500 in mints.” The memory, rankings and Qwen prompt adapt again toward the stronger revenue signal. Press Reset memory to return to the original baseline. This demonstrates the complete loop: on-chain mint outcome → persistent creator memory → learned weights → re-ranked content → updated Qwen prompt The interactive lab uses deterministic simulated mint outcomes, with no API key or cost, but it runs the same tested MemoryAgent functions as the hosted scheduler. In production, the reinforcement signal comes from indexed XDC Minted events. Judge-lab source: https://github.com/chris-blvck/rwa.dao/blob/main/frontend/components/rwa/screens/HackathonScreen.tsx Memory core: https://github.com/chris-blvck/rwa.dao/blob/main/frontend/lib/rwa/agent_memory.ts Alibaba judge-lab route: https://rwadao-hackaton-ardhtlwfjj.ap-southeast-1.fcapp.run/hackathon Note: Alibaba’s shared fcapp.run domain may download the HTML instead of displaying it. The same interactive scenario should therefore be shown clearly in the public demo video. We should not claim that the current Netlify Creator Studio page visibly demonstrates the learning loop by itself.
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