Both is usually the right answer, since you can use LLMs to do query expansion and effectively increase the recall performance of your retrieval algo

Exactly this, and this tool called qmd is what I use for the hybrid search portion. It also uses local LLMs to provide summaries on your own markdown data too. My agents use both depending on what type of search they are doing, and both provide good results.

https://github.com/tobi/qmd

That assumes that the agent knows which one is better. And to bake in which one is better via post-training would require a study like this to establish where each one works well

it will only use tools it was trained on? what's the benfit of givig it all the tools.

I'm still disappointed that ai can't use ctags, its used for finding strings and patterns, its right there.