Opik has enhanced its platform by integrating an AI-powered analysis tool, OpikAssist, into its LLM observability product to make complex trace data more understandable and actionable for AI developers. Initially focused on capturing and organizing data, Opik recognized the necessity of helping users interpret large volumes of trace data to understand why certain behaviors in AI applications occurred. By building OpikAssist, the company undertook a 'dogfooding' challenge, using its own platform to test and refine the AI agent through 91 experiments, ultimately enhancing the platform's capability to transition AI projects from prototype to production-ready systems. This process involved comprehensive tracing, human feedback, and creating a golden evaluation dataset to systematically improve the AI feature, demonstrating that with the right tools and processes, AI projects can successfully evolve from pilots to reliable production systems. The result is a feature that not only provides intelligent trace interpretation and actionable recommendations but also validates Opik's platform as a critical tool for AI development, helping users move from understanding what happened in their AI systems to why it happened and how to resolve it.