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?

If your user queries are short "slang" phrases but your documents are formal legal texts, how do you ensure the embedding model can bridge that semantic gap?

How would you design an orchestration layer for a system with multiple specialized AI agents (e.g., planner, retriever, executor) where partial failures are common?

Why do we typically include a 10–20% overlap between text chunks? What happens to the retrieval quality if the overlap is zero?