Close the loop: User feedback for AI capabilities
Blog post from Axiom
Axiom introduces a comprehensive user feedback capture system designed to enhance AI capabilities by linking user feedback directly to AI traces, thus allowing teams to identify and address issues more effectively. This system collects both explicit feedback, such as thumbs up/down and comments, and implicit signals like regenerations or copies, integrating them into a dedicated view in Axiom's Console for analysis. By associating feedback with specific AI traces, domain experts can prioritize and examine problematic interactions, transforming them into test cases to prevent future occurrences. This feedback-driven approach not only aids in immediate issue triage but also informs the development of a robust evaluation suite based on real-world edge cases, fostering a continuous improvement loop. Axiom's strategy combines this feedback mechanism with existing observability and offline evaluations, creating a holistic system that bridges the gap between user experience and quality assurance, ultimately leading to more reliable AI deployments.