How to debug production AI agents with Signal in Arize AX

Signal is a managed agent integrated within Arize AX that aids in debugging production AI agents by continuously reviewing production traces, identifying recurring failure patterns, and converting them into prioritized issues with supporting evidence, a likely cause, and recommended next steps. It operates within a controlled loop where production behavior is evaluated, investigations are conducted, and proposed changes are tested before deployment. Signal's investigations can delve into the codebase with repository access, proposing pull requests that developers review. It is particularly useful for identifying failures that are difficult to spot through dashboards alone, such as incorrect agent or tool selection, silent fallback to model memory, or cost and latency regressions. Evaluations help pinpoint runs that do not meet an application's quality criteria, and Signal's findings can be used to create regression datasets to prevent the recurrence of similar failures. While Signal handles the time-consuming investigation process, developers retain control over validating causes and evaluating proposed changes before any are merged into production. Signal's capabilities are accessible across all Arize AX plans, with repository-backed features and broader managed-agent workflows available as Enterprise capabilities.

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