From Traction to Production: Maturing your GenAIOps step by step

Your concept of a product that leverages the power of Large Language Models is gaining traction, and your initial API calls to the selected LLM vendor show promising results. What’s next? Should you look forward to ensure your app is scalable, maintainable, safe, secure, and ready for the introduction and monitoring of quality metrics like groundedness, as well as operational metrics such as latency and token consumption? Or should you look back to reconsider model selection or fine-tuning, refine prompts, and improve RAG techniques? And how do you close the continuous improvement loop?