The blog post discusses the development and functionality of a search-based Discord bot, called co_search, which uses language models to answer questions by integrating web search. Unlike typical language models that generate responses solely from prompts, co_search enhances its answers by conducting a web search using APIs like SerpApi, and then identifying the most relevant information from search results through semantic comparison. The process involves several steps: contextualizing the question within the conversation, searching the web for information, embedding and comparing search result sections to find the most relevant content, and finally, generating an answer with low creativity to ensure factual accuracy. The bot is triggered by a question mark emoji in the Discord channel, but the system's design allows for alternative triggers and customizations. This multi-step pipeline approach expands the possibilities for creating intelligent conversational agents and emphasizes the importance of responsible use of large language models.