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Developer Builds Self-Auditing AI Memory Agent Mnemo for Global Hackathon

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A developer created Mnemo, an AI memory agent submitted to Track 1 of the Global AI Hackathon powered by Qwen Cloud, designed to audit and verify its own stored beliefs before acting on them. Unlike most memory agents that optimize for retaining more information, Mnemo focuses on trustworthiness by grading recalled memories in real time and blocking the agent from acting on unreliable ones. The system uses Qwen Cloud models for reasoning and retrieval, with a cost-efficient architecture that runs roughly 90% of development offline using a deterministic stand-in to avoid unnecessary API spend. A key design feature is contradiction-driven forgetting, which discards outdated memories rather than allowing the agent to act on stale or incorrect information. Ironically, during the build the developer discovered their own committed evidence file contained a confident but incorrect assertion, a real-world example of the exact problem Mnemo was built to solve.

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