When would you store a summary of a document in the vector DB but retrieve the full text for the LLM?

You can't use a standard debugger on an LLM's "thought process." How do you build observability into an agentic loop to find where a logic error occurred?

How does the "Extraction, Transformation, and Loading" process differ when preparing data for a Vector Database versus a traditional SQL database?

How does the model actually "call" a tool? Explain the back-and-forth between the Assistant message and the Tool/Function message in an API loop.