Ever wonder how search engines seem to know exactly what you're looking for? It's not magic, it's advanced AI. New research explores how Large Language Models (LLMs), the brains behind modern search, are getting even better at understanding your needs by using your past search history. The challenge? LLMs are great at general knowledge, but struggle with the specific nuances of individual search queries. This research introduces "ProRBP," a clever system to make LLMs smarter. Imagine it like this: ProRBP looks at what you’ve searched for in the past and finds similar searches from other users. It then uses this information to give the LLM extra clues about what you really mean. This helps the LLM bridge the gap between general knowledge and your unique search intent. ProRBP also guides the LLM step-by-step, showing it different aspects of the search query and gradually improving its understanding. Think of it as teaching the LLM to "think like a human." The result? More accurate, relevant search results. This technology isn't just theory; it's being used right now in real-world search engines, making searches faster and more effective. This advancement signifies a big leap in how search engines use AI, offering a glimpse into a future where finding information is easier and more intuitive than ever before.