Managing API data with useState + useEffect means reinventing the wheel — and doing it worse. TanStack Query handles caching, background updates, and loading/error states so you can focus on UI logic.
RAG system costs come from LLM tokens, Embedding APIs, and vector search. Every stage has room for cost reduction, but you need to verify that optimizations don't sacrifice too much quality.
Caching doesn't have to match exact query strings -- semantically similar questions can hit the cache too, skipping the entire RAG pipeline execution.