I feel like retrieval approaches, despite how good your ranking mechanisms are, end up biasing LLMs into what a heuristics-based system with way worse understanding of the domain says. I guess is a trade off between speed and quality, but letting the LLM explore without a bias (based on my personal experience) seems to generally provide much better results in terms of quality for the final output.
Grep is the fastest tool for many things, but for production RAG it cannot search with meaning, different languages or typos like hybrid vector search can. And it won't scale on terabytes of documents across distributed servers if you want to say under 1000ms.
"why not use grep?"
With a very large dataset of totally unnormalized data, semantic folding is a silver bullet.