Large Language Models (LLMs) power many of today's chatbots, but they often struggle with complex, real-world conversations. Why? Because finding the right information online isn't as straightforward for AI as it is for humans. Researchers have been trying to solve this by giving LLMs search tools, but existing methods are often inefficient, returning irrelevant information that muddies the chatbot's responses. A new research paper introduces SRSA (Strategy-Router Search Agent), a clever framework designed to make chatbot searches smarter and more cost-effective. SRSA works like a personalized search strategy advisor for the LLM. It analyzes the user's question and then picks the best search approach from three options: a quick rewrite of the original question (Direct Search), breaking the question into smaller parts and searching them simultaneously (Parallel Search), or planning a sequence of searches where each one builds on the previous results (Planning Search). To test SRSA, the researchers created a special dataset called CQED (Contextual Query Enhancement Dataset) filled with the kind of long, nuanced questions people actually ask chatbots. They pitted SRSA against two baseline models: a simple, single-round search and a ReAct-based search agent. The results? SRSA delivered more informative and complete answers, especially for the tricky, multi-part questions. It even surpassed the ReAct agent, which often gets bogged down by too much irrelevant information. Interestingly, just rewriting the user’s initial query led to significantly better search results, demonstrating the importance of framing the right search terms. While SRSA showed promising improvements, the research also identified areas for future exploration. The study primarily focused on one specific LLM (Mistral), and expanding to other LLMs could reveal more about SRSA's general effectiveness. Additionally, future work could explore more advanced search engine APIs beyond the one used in the study. The development of SRSA, along with the new CQED dataset, marks a crucial step toward more intelligent and efficient chatbot interactions. As AI continues to weave itself into the fabric of our daily lives, innovations like SRSA offer exciting possibilities for smoother, more natural conversations with our digital companions.