I found this approach very interesting and was wondering if it could be applied to grep-based search for coding agents to increase speed and reduce LLM turns, but the part im not quite understanding is how the model will know enough about the codebase to construct a complicated multi-stage search pipeline based just on the prompt.
Maybe this is just different from web search, but it seems like the model needs sequential tool calls to know where to look next, and coding agents have already put in a lot of work to encourage parallel tool calling.
Maybe this is just different from web search, but it seems like the model needs sequential tool calls to know where to look next, and coding agents have already put in a lot of work to encourage parallel tool calling.