AI Engineering
Learn LLMs, RAG, agents, secure tools, and production AI through practical insurance examples.
What is RAG?
RAG retrieves relevant external evidence and gives it to a model before answering. It lets the insurance assistant use current private policy documents and produce source-backed explanations instead of relying only on learned knowledge.
RAG or long context?
If the task already identifies a small permitted document set, long context may be simpler. For a large changing corpus, retrieval selects relevant evidence more efficiently. Both need access control, applicability checks, and answer evaluation.
How do you debug wrong RAG answers?
I inspect parsing, document version and permissions, chunk boundaries, candidate recall, ranking, supplied context, and answer support in that order. I score retrieval and generation separately, then improve the failing stage rather than automatically using a…
An answer cites a real document but is wrong. Why?
The cited document may be irrelevant, expired, inapplicable, or missing an exception; the answer may also misinterpret it. I validate source eligibility and claim support, not just whether the link exists.
Difficulty is an editorial estimate. Completion means you chose to mark a question as understood.