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.
Good point and it’s an often overlooked.
RAG can take the intelligence of an LLM and dumb it down to old school Google search results.
The trade-off between speed and quality is everything though. I've found that semantic searching everything that might be relevant and dump the top N into the model is way faster at getting a workable result.