In the world of modern software development, observability has long been the practice of understanding system behavior by examining outputs, particularly in complex distributed environments. But when it comes to artificial intelligence, and especially autonomous AI agents, traditional observability falls short. You cannot simply monitor CPU usage and call logs to understand why an AI model...

As artificial intelligence evolves from simple predictive models to autonomous agents capable of executing complex, multi-step workflows, the challenge of understanding what these systems are doing grows exponentially. An agent doesn't just generate a single response; it plans, reasons, takes actions, observes results, and adjusts its approach based on what it learns. It might call external...