Architecture update: ReefWatch AI now uses Arize Phoenix traces to build benchmark datasets from real production activity. Candidate prompt improvements are evaluated through controlled experiments and only promoted if they outperform the production prompt. Poor candidates are automatically rejected and every decision is recorded in an audit trail. The system now operates as a measurable, production-style self-improvement pipeline rather than a simple prompt rewriting workflow.
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