Debug and evaluate your AI app from your coding agent with Datadog Agent Observability

Coding agents like Claude Code, Cursor, and Codex CLI effectively manage the coding aspects of developing AI applications, but the more challenging tasks arise in evaluating errors, understanding why responses fail, and adapting to rapidly changing applications. Teams typically spend a significant amount of their time—60-80%—on evaluation and error analysis, often needing to redo this work with each change in the technology stack. Datadog Agent Observability captures essential telemetry data, facilitating the analysis of prompts and responses, and supports online evaluations. By utilizing Datadog's MCP Server and Pup CLI, developers can access Agent Observability data directly from their coding agents, enabling them to classify sessions, debug production failures, and evaluate application updates using real traffic data. These tools, combined with Agent Skills, allow for efficient error analysis and evaluation workflows, providing actionable insights and experiment metrics directly within the coding environment. The integration of these tools streamlines the process from investigation through to remediation, ensuring that AI applications are continuously improved in a structured and efficient manner.

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