Debugging AI API Failures in Multi-Model Systems

Multi-model AI apps face complex failures beyond simple errors, including latency spikes, invalid JSON, and cost creep. A failure taxonomy and full request logging help teams identify whether issues stem from providers, models, routing, or workflows. Debugging by workflow rather than by model alone is key to maintaining production reliability.