As we go about moving LLM enabled products into production we definitely see a bunch of what is being spoken about resonate. We also see the below as areas whic

As we go about moving LLM enabled products into production we definitely see a bunch of what is being spoken about resonate. We also see the below as areas which need to be expanded upon for developers building in the space to take products to production : I would love to see this article also expand to touch upon things like : - data management - (tooling, frameworks, open vs closed data management, labelling & annotations) - inference as a pipeline - frameworks for breaking down model inference into smaller tasks & combining outputs (do DAG's have a role to play here?) - prompts - areas like caching, management, versioning, evaluations - model observability - tokens, costs, latency, drift? - evals for multimodality - how do we tackle evals here which in turn can go into loops e.g. quality of audio, speech or visual outputs