In your point you said "There is more to searching than building a basic similarity search." which assumed and implied all kinds of things and which was completely unnecessary.

> In practice tools like Claude Code, Codex, Gemini, Kimi Code, etc are getting away with searching for code with grep / find and understanding code by loading a sufficient amount of code into the context window

Getting away is the formulation I would use as well. "Sufficient amount" OTOH is arguable and subjective. What suffices in one usage example, it does not in another, so the perception of how sufficient it really is depends on the usage patterns, e.g. type and size of the codebases and actual queries asked.

The crux of the problem is what amount and what parts of the codebase do you want to load into the context while not blowing up the context and while still maintaining the capability of the model to be able to reason about the codebase correctly.

And I find it hard to argue that building the vector database would not help exactly in that problem.