7 best tools for debugging AI agents in production (2026)

Braintrust is highlighted as an effective debugging platform for AI agents in production, integrating trace inspection, evaluation, and CI/CD enforcement into a unified workflow. The platform facilitates the transformation of production failures into permanent evaluation cases, preventing future regressions by validating every code change. Braintrust supports over 40 framework integrations and provides a native GitHub Action for automated evaluations, making it suitable for diverse tech stacks. The guide contrasts Braintrust with other tools like LangSmith, which is more focused on LangChain and LangGraph ecosystems, and explains key differences between debugging, monitoring, and observability. Debugging AI agents involves tracing, isolating, and resolving errors in multi-step workflows, emphasizing the need for reconstructing execution paths to identify and fix issues. The document also discusses how effective debugging prevents the recurrence of failures by incorporating them into automated evaluation suites, thereby enhancing the reliability of agent deployments.