Chris and the author built a search engine for the author's blog using word embeddings and cosine similarity, leveraging the word2vec model. They detailed the process of embedding words, creating a search index, and handling user queries through a REPL interface, while also discussing the challenges of deploying a lightweight version of the search engine on the web. The article concludes by outlining a strategy for efficient data retrieval using HTTP Range requests.