It's the trick where a user asks you a question: "Who worked on the billing UI refresh last year?" - and you turn that question into a search against a bunch of private documents, find the top matches, copy them into a big prompt to an LLM and ask it to use that data to answer the user's question.
There's a HUGE amount of depth to building this well - it's one of the most actively explored parts of LLM/generative-AI at the moment, because being able to ask human-language questions of large private datasets is incredibly useful.
It's the trick where a user asks you a question: "Who worked on the billing UI refresh last year?" - and you turn that question into a search against a bunch of private documents, find the top matches, copy them into a big prompt to an LLM and ask it to use that data to answer the user's question.
There's a HUGE amount of depth to building this well - it's one of the most actively explored parts of LLM/generative-AI at the moment, because being able to ask human-language questions of large private datasets is incredibly useful.